From ccolo@mompou.iqs.url.es Tue Oct 22 06:16:54 1996 Received: from fletxa.iqs.url.es for ccolo@mompou.iqs.url.es by www.ccl.net (8.8.0/950822.1) id FAA05004; Tue, 22 Oct 1996 05:36:52 -0400 (EDT) Received: from mompou.iqs.url.es by fletxa.iqs.url.es (AIX 4.1/UCB 5.64/4.03) id AA37494; Tue, 22 Oct 1996 11:39:22 +0200 Date: Tue, 22 Oct 1996 11:26:49 +0100 (GDT) From: Carles Colominas To: chemistry@www.ccl.net Subject: Summary:Benchmarks Message-Id: Dear Netters, Some days ago I posted a message about new HP and SGI workstations perfomance. My original question and answers are shown below. The last part of this message is a review by Martyn F. Guest at CCLRC Daresbury Laboratory about 'Performance of Various Computers in Computational Chemistry' that includes lots of useful data. Thanks to all who answered: Steen Hammerum Bill DeSimone Jose Luis Garcia de Paz Oakley H. Crawford Marc C. Nicklaus Vikram Varma Alexander Hofmann Martyn F. Guest ========= ========= ========= ======== ****** ****** From: Steen Hammerum I recently asked the very same question, and here is the summary I posted: ------------------------------------------------------------------------ Summary: Speed of new HP and SGI workstations I recently asked this group for advice with regard to the performance of new HP and SGI workstations running the Gaussian programs ------------------------------------------------------------------------ Does anyone have or know of benchmarks for Gaussian 94 or related programs running on the new SGI and HP chips (R10000 and PA8000), or other information to assist us before we decide on new machinery? We are currently considering SGI Power Indigo 2 and HP C160 workstations that will be used predominantly for Gaussian calculations, but we are not sure how well the SPECint95 and SPECfp95 numbers allow us to assess the relative performance. ------------------------------------------------------------------------- --- Roberto Gomperts (roberto@boston.sgi.com) provided the following comparison of the SGI R8000 and R10000 chips when running test178 from the Gaussian 94 test suite (a single point, direct scf calculation with 300 basis functions), using Gaussian 94, rev. D3. Machine Chip/Frequency Sec. Cache Time(min.) Power Indigo2 r8k/75 MHz 2 MB 8.04 Power Challenge r8k/90 MHz 4 MB 6.50 Power Indigo2 r10k/195 MHz 1 MB 7.30 Power Challenge r10k/195 MHz 1 MB 7.08 Power Challenge r10k/195 MHz 2 MB 5.95 The Power Challenge runs are done on 1 processor. These are all CPU times. The Wall clock times are very similar to these (less than 20 sec. difference) --- John Brodholt (j.brodholt@ucl.ac.uk) pointed me to http://gserv1.dl.ac.uk/TCSC/disco/TechPapers/bench/bench.html This site provides a detailed, critical and very useful comparison of the performance of a wide variety of newer workstations; unfortunately, no results obtained with HP PA8000 machines are included (html version not yet available, but a postscript version can be downloaded). The comparison is based on timing data obtained with GAMESS-UK (rather than Gaussian). The results illustrate that the relative performance varies quite a bit with the type of calculation undertaken. --- Eric Billings (billings@helix.nih.gov) pointed me to http://www.ki.si/parallel/summary.html The information was designed to compare parallel architectures, but the single CPU column provides useful information. --- Finally, Glenn McEnroe (gmcenroe@crl.com) suggested that I looked elsewhere: "Regarding your question about SGI vs HP you should check out the latest issue of Journal of Computational Chem V17 No. 11 1385-86 entitled Viability of Molecular Modeling with Pentium based PCs. This article does not compare these new chips for SGI and HP but it appears that you may be better off running your application on a pentium based machine if Gaussian 94 is available for this platform." --- Many thanks to everyone who answered. ---------------------------------------------------------------- Since writing the summary, I have had the opportunity to perform trisl calculations on both new SGI and new HP machines. The results with R10k SGI machines confirm Roberto Gomperts' results (see summary), that is, the new chip is very fast but not much faster than the old chip, and cache size matters a lot. My HP results have been somewhat disappointing, insofar as the new chip in real life situations (if G94 calculations can be called "real life") does not seem to be quite as fast as the benchmarks would lead you to expect. Hope this helps, Steen -- Steen Hammerum steen@kiku.dk Department of Chemistry (+45) 35 32 02 08 University of Copenhagen, Denmark fax: (+45) 35 32 02 12 ========= ========= ========= ======== ****** ****** From: desimone@mroa.ENET.dec.com Carles, The AlphaStation 500 with the 500 MHz chip should perform at least as well if not better than HP and SGI on Gaussian and AMBER. A customer in Isreal just bought an AlphaStation 500 to run Gaussian. I can see if this customer would talk to you if you are interested. Unfortunately all my Gaussian benchmarks are on AlphaServers , which BTW, beat the competition on Gaussian benchmarks. Also, the UCSF data on AMBER is on very old AlphaStations. Bill DeSimone Science & Research Applications High Performance Computing DEC ========= ========= ========= ======== ****** ****** From: DEPAZ@ccuam3.sdi.uam.es Carles, En la Univ Autonoma de Madrid se acaba de comprar un DEC de 8 cpu, en competencia con un SGI de ocho r10000. Hicimos pruebas con el gaussian (en eso estuve yo) y EN TODAS nos salio un 20% mas repido el chip dec que el chip silicon. Hubo test del gaussian usando una sola cpu, usando varias (paralelo), etc. No hubo color. La version gaussian para dec iba mejor que la gaussian que habian modificado para silicon. Yo estuve en la comision tecnica como quimico cuantico y no tuve dudas. Un saludo Jose Luis Garcia de Paz quimica fisica aplicada 3974263-4957 ========= ========= ========= ======== ****** ****** From:crawfordoh@ornl.gov If you have access to the www, look at http://www.netlib.org/performance/html/PDStop.html for performance data on a vast array of machines. Otherwise, send the following message to netlib@ornl.gov, to receive performance data in postscript files: send performance.ps from benchmark send mp-computers.ps from benchmark Finally, if you want more info about netlib's collection, send the following message: send index Good luck, Oakley Crawford ---------------------------------------------------------------------------- Oakley H. Crawford Phone: +1-423-574-5048 Oak Ridge National Laboratory Fax: +1-423-574-6210 P. O. Box 2008, MS 6123 E-mail: crawfordoh@ornl.gov Oak Ridge, Tennessee 37831-6123 Express delivery, add: Bethel Valley Road USA ---------------------------------------------------------------------------- ========= ========= ========= ======== ****** ****** From: "M. Nicklaus" Dear Dr. Colominas, We have a four-processor Digital AlphaServer 4/275 which we use mostly to run Gaussian 94 and the Molecular Mechanics program CHARMM. We are very happy with it. We have not done benchmark comparisons with an SG R10000 system ourselves (since we don't have one), but I remember having seen quite a few postings of, or at least pointers to, benchmarks with ab initio and MM programs that included SGI, HP, and/or DEC systems, and which should be retrievable from the CCL archives. Hope this helps. Regards, Marc C. Nicklaus ------------------------------------------------------------------------ Marc C. Nicklaus Lab. of Medicinal Chemistry e-mail: mn1@helix.nih.gov National Cancer Institute, NIH Phone: (301) 402-3111 Bldg 37, Rm 5B29 Fax: (301) 496-5839 BETHESDA, MD 20892-4255 USA WWW: http://www.nci.nih.gov/intra/lmch/MCNBIO.HTM ------------------------------------------------------------------------ ========= ========= ========= ======== ****** ****** From: Vikram Varma Also consider the Pentium Pros - in parallel, you can get a lot of bang for your buck!! >>>>> Vikram Varma National Research Council of Canada Phone: 613 993 5150 Institute for Biological Sciences FAX: 613 952 9092 Room 3071 100 Sussex Drive, e-mail: varma@nrcbs8.bio.nrc.ca Ottawa, Ontario K1A 0R6 www: http://nrcbsa.bio.nrc.ca/~varma <<<<< ========= ========= ========= ======== ****** ****** From: Alexander Hofmann Some Gaussian-benchmarks http://www.chem.joensuu.fi/people/juha_muilu/Misc/benchmarks.html regards alex ========= ========= ========= ======== ****** ****** From: "M.F.Guest" Dear Carles, In response to your mailing, I thought you might find the attached of value. This is a plain text version of an assessment of a wide variety of machines in computational chemistry, including the R10000 and a prototype version of the new HP machine. While it doesnt specifically include GAUSSIAN and AMBER, I hope that you will find it of use. Let me know if I can be of any further assistance. Best regards Martyn ****************************************************************** * Martyn F. Guest * * Head, Advanced Research Computing email: m.f.guest@dl.ac.uk * * CCLRC Daresbury Laboratory FAX : +44 (0)1925 603634 * * Warrington voice: +44 (0)1925 603247 * * Cheshire WA4 4AD * * England, UK * ****************************************************************** ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Performance of Various Computers in Computational Chemistry Martyn F. Guest September 1996 Abstract This report compares the performance of a number of different computer systems using a variety of software from the discipline of computational chemistry. The software includes matrix operations, a variety of chemistry kernels from quantum chemistry and molecular dynamics, and a set of twelve quantum chemistry calculations using the GAMESS-UK electronic structure program. The comparison involves approximately fifty computers, ranging from a Cray YMP-C98 to scientific workstations from IBM, Sun, Hewlett Packard, Digital and Silicon Graphics, and Pentium Pro-based PCs. 1. Introduction This report presents a performance evaluation through benchmarking of a number of different computer systems specifically in the area of computational chemistry. This work has been ongoing since 1988, when the intention was to include representative hardware typifying supercomputers, superminis, workstations and the emerging class of parallel, novel architecture machines. Throughout the 1980's the cost effective debate in scientific computing centred on the relative merits of conventional vector supercomputers [1] and so-called superminis, machines costing some 10% of supercomputers, and exhibiting some 10% of supercomputer performance [2]. Over the past 7 years the supermini category of computational resource has to a large extent disappeared from both the vocabulary and offerings of most hardware vendors, to be replaced by high-end workstation servers. We have retained those machines that originally belonged in the supermini bracket, the Convex 220, the FPS M64/60 [2] and Alliant FX2808, primarily to provide a historical perspective at the evolution of workstation capabilities, and how machines that typically fell in the $500K price range are now outperformed by machines costing some 10% of this figure. Supercomputers used in this report include the Cray X-MP, Y-MP, YMP/J90 and YMP/C98, and the Convex C3860. A large number of workstations have been benchmarked, including those from - IBM, with the Power and Power2 Risc system RS6000-based models, - Hewlett Packard with the HP/Apollo DN10020 and the PA-RISC based HP model 9000 series, including the more recent PA8000 CPU. Note that the latter was housed in a single-processor HP PA/9000-K460, with a 160 Mhz PA8000 (and not 180 MHz). - DEC, with the DEC Station 500, the AXP EV4-based 3000 series. and the EV5-based 600, 800 and 2100 alpha series, - Silicon Graphics, with the R3000-, R4000-, and R8000-based machines including the Challenge, Power Challenge, Indy, Indigo and Indigo2, Crimson, and 4D series, plus machines with the more recent R10000 and R5000 CPUs. - Stardent (1520, 3020 and VISTRA 800), and - Sun 4/370, SPARCstation-2, SPARC-5 and SPARC-10 and the more recent Hyper- and Ultra-SPARC processors (Ultra-1/140 and 170, and the Ultra-2/200). While workstations have, for the majority of scientific applications, demonstrated their cost-effectiveness against vector supercomputers, recent developments with PCs suggest that the position of the workstation as the desktop system of choice is now under threat. We thus include for the first time one of the most recent offerings from the PC marketplace, the 200 MHz Pentium Pro. Parallel, or ``novel architecture'' machines include the iPSC/860 from Intel, both transputer and i860-based Meiko Computing Surfaces, the KSR-2 from Kendall Square Research, the Cray T3D and IBM SP2. Machines featuring in this exercise, together with associated configurations, are given in the Appendix. We should stress from the outset that our access to much of the hardware evaluated herein has been at best short lived, and has often involved the temporary loan or donation of machines as part of one of the hardware evaluation exercises run at the Daresbury Laboratory. In many cases these machines were not optimally configured in terms of either memory, or high speed disk, and consideration of the results presented here should be viewed in that light. Following an introductory evaluation of hardware based on the Whetstone Benchmark, we present in Sections 2, 3, and 4 results using a variety of chemistry-oriented software. This 64-bit floating point precision FORTRAN-based code may be classified into three distinct categories, each designed to provide a pointer to the relative hardware capabilities in the discipline of computational chemistry; 1. The first category (the MATRIX Benchmark, section 2) reflects the dependence of many of the algorithms in the area of electronic structure calculations on matrix operations, and includes both matrix multiplication and matrix diagonalization; 2. The second category (the Computational Chemistry Kernels, section 3) includes four chemistry `kernels', each comprising less than a 1000 lines of FORTRAN code, and intended to be representative of the typical calculations undertaken in the area of computational chemistry. Described in more detail in section 3, these kernels include direct-SCF, molecular dynamics (MD), quantum monte carlo (QMC), and a Jacobi eigen solver (JACOBI); 3. Finally, we include complete quantum chemistry applications (section 4), using the GAMESS-UK electronic structure program [3]. Twelve typical applications are included, featuring both conventional Hartree Fock self-consistent field (SCF) and direct SCF, complete active Space SCF (CASSCF) and multiconfiguration SCF (MCSCF), configuration interaction calculations, both direct-CI and conventional table-driven MRD-CI, Moller Plesset perturbation theory (MP2), and both SCF and MP2 analytic 2nd derivatives. 2. The MATRIX Benchmark 2.1 Whetstone Benchmark A comparison of the single processor Whetstone performance on a variety of machines, including vector supercomputers, minisupers, superworkstations and workstations, together with that obtained on a single node of various novel architecture machines is given in Table 1. Data provided includes the Mflop performance on a variety of floating point vector loops (VL=1024), together with the total cpu time to execute the benchmark, and the MWips performance. The primary aim of this benchmark is to provide a performance measure of both floating point (FP) and integer arithmetic; thus while trends in the VL Mflop ratings are of interest, only a small part of the total CPU time is actually involved in these operations. The wide variety of standard functions exercised (abs, sqrt, exp, alog, sin, cos, atan etc.) consume a far larger fraction of the reported times; note the latter provide a close mapping onto the measured rate of instruction processing (MWips, million whetstones instructions per second). This benchmark was originally designed to monitor the performance of vector supercomputers, and an examination of Table 1 reveals that both the Cray Y-MP and YMP-C90 continue to outperform all other machines. As expected, the Cray YMP-J90 is less impressive, some four times slower than the C90, and slower than five of the leading workstation CPUs. The fastest CPU is seen to be the 195 MHz R10000 processor from SGI, some 1.5 times faster than the 333 MHz EV5 of the alpha 600/5. Both CPU time and MWips rate suggest that the latter processor is marginally faster than the recently released PA8000 processor of the HP PA/9000-K460, and 1.5 times the speed of the 200 MHz Ultra-2/200 from Sun. The performance of the K460 is far below that expected based on the published SPEC-fp95 ratings, and it is clear that the compiler, libraries etc on the machine under test (a single processor 160 Mhz prototype of the PA8000) were not optimal, with the results of this and subsequent benchmarks not reflecting the true potential of the PA8000. SGI's other new processor, the R5000 from mips, is also seen to perform well, and while about 1.8 times slower than the R10000, is faster than the Ultra-2 and alpha 266 Mhz EV5. In contrast the R8000-based machines from SGI appear to under-perform, 4 times slower than the R10000, three times slower than the AXP-600/5/333, and slower than both the HP PA/9000-735/125 and IBM Power 2 RS/6000-3CT. The R8000 is seen to outperform its predecessor, the R4400, by just a factor of 1.7, based on the CPU time for the complete benchmark. Sun's latest processor, the 200 MHz Ultra-2/200 is found to be more than twice the speed of the 125 Mhz HyperSPARC, and 8.5 times the 40 MHz SuperSPARC processor in the Sun SPARC 10/41. Considering the MPP single node performance of Table 1, the KSR-2 custom processor is seen to be comparable with mid-range workstation CPUs (IBM RS/6000-360 and DEC AXP/3000-500), while the quality of the FORTRAN compiler on the Cray T3D is at least in part responsible for the Whetstone timing of 121 seconds, 1.8 times slower than the DEC AXP/3000-500 (68.7 secs) which does, of course, house the same CPU. The IBM-SP2 TN2 processor is by far the dominant CPU, twice the speed of the KSR-2 and 3.5 times that of the Cray T3D. Finally, we note that the performance of the Pentium Pro is broadly in line with expectations. It outperforms the R8000-based SGI and Power2-based IBM workstations, while slower than the leading CPUs from SGI, Digital, HP and Sun, by factors of 3.8, 2.5, 2.3 and 1.7 respectively. It is important to realise that this level of performance is only achieved using "commercial" Fortran compilers (in this case from Intel). Using public domain f2c and a variety of c-compilers produced far inferior figures, some 3-4 times slower than those of Table 1. 2.2 Sparse Matrix Multiply Benchmark The matrix multiply operation (MMO) is central to the efficient operation of modern QC codes on vector processors [1], it being possible both to extract near peak performance for this kernel and to formulate many QC steps around this operation. A comparison of the single processor sparse MMO performance on a variety of machines, is given in Table 2. In this benchmark a series of MMOs (R = A X B) involving matrices of order 10, 20, 30, ... 150 were performed. Each MMO was conducted a number of times, this number being inversely proportional to the order of the matrices, so that the summed CPU times of Table 2. refer to 150 MMOs of order 10 matrices, 140 of order 20 matrices, and so on up to 10 MMOs for matrices of order 150. Figures are presented for both `full' (0% sparse) and 50%-sparse B matrices, with the performance figures referring to code written entirely in Fortran. The potential of the PA8000 processor is clearly seen in the figures of Table 2, with the HP/PA9000-K460 recording the same time as the Cray Y-MP/C98, and marginally faster than the R10000/195 processor. Both processors outperform the Cray Y-MP/8128, with the HP/PA9000-K460 twice as fast as the R8000-based SGI machines and Power2 RS/6000-3CT. The latter machines exhibit identical performance on this benchmark (with 0% sparsity timings of 1.8 seconds). Both CPUs are marginally faster than the EV5 600/5/333 and 84000/5/300, 1.3 times faster than the Ultra-2/200 and 1.4 times faster than the HP PA/9000-735/125. Both exhibit comparable timings to that on the Y-MP/8128 (1.5 seconds), achieve some 50% of the YMP-C98 rating, and outperform the Cray YMP-J90 by a factor of 1.4. The performance of the R5000 processor is perhaps disappointing, four times slower than the R10000. The R1000-based Power Onyx is seen to outperform the corresponding R8000 machine by a factor of 1.6, which in turn outperforms the R4400 Challenge L by a factor of 3.9, and the earlier 50 Mhz R4000 Challenge by a factor of 5.6. Much of the speed of the R8000 may be attributed to the KAP pre-processor, which enhances FORTRAN performance by a factor of 1.8. The performance of the Pentium Pro/200 is again seen to be impressive, recording exactly the same benchmark time as the DEC Alpha 600/5-266 and Sun Ultra-2/200. Of historical note is the timing of 448.6 seconds recorded on the T800 20MHz Transputer, some 500 times slower than the PA8000 CPU and the Cray YMP-C98. Considering the MPP nodes, the IBM-SP2 TN2 node outperforms the Cray AXP node of the T3D by a factor of 4.7, and the KSR-2 by a factor of 6.6. Note that the T3D node remains 1.5 times slower than the DEC AXP/3000-500. One additional feature of the MMO benchmark not apparent in Table 2 is the significantly enhanced performance found on all machines when comparing assembly language MMO to Fortran MMO. Historically this has often involved the user having to code key routines in assembly language, for few vendors initially provided optimized mathematical libraries; improvement factors of 3.2 (Cray X-MP), 4.2 (IBM 3090/VF), 3.1 (Convex C-220) and 3.4 (FPS-M64/60) have previously been reported with assembly language implementations of the sparse MMO routine, MXMB. Optimized BLAS libraries are now fairly commonplace on the majority of workstation platforms, the most notable exception, until recently, being the SPARC offerings from Sun (note that the Cray-optimised libraries are now available on both Hyper- and UltraSPARC machines). The impact of optimized library routines continues to be evident on current workstations, with the 0% sparsity timings of Table 2 improving by factors of 1.8, 1.9, 2.3, 2.5, 2.7 and 3.1 for the SGI R10000/195, IBM RS/6000-3CT, SGI R8000 Indigo2, HP PA/9000-735/125, DEC Alpha 600/5/333 and Alpha 8400/5-300 respectively when using the BLAS dgemm routine. A corresponding factor of 3.8 is found when using the Kuck Library on the i860, and perhaps somewhat surprisingly, a factor of 4.5 when using SCILIB on the Cray YMP-C98. The availability and degree of functionality of library software are, we believe, important issues when considering cost-effective performance. This effect is evident from the second benchmark which, given in Table 3, involves performing a series of similarity transforms (Q*HQ) using both a scalar and vector algorithm. The scalar code collapses the matrix transposition and multiplications to yield an algorithm with fewer FLOPS than the vector code, which adopts a brute force approach by explicitly performing the transposition and two matrix multiplications. In the latter case we utilize the BLAS library routine DGEMM (where available) for performing the requisite MMOs, in the former case the dot product BLAS routine, DDOT. Considering the scalar algorithm, the SGI R10000 and HP PA/9000-K460 exhibit the optimum performance, with the R10000 1.1 times the speed of the Sun Ultra-2/200 and 1.2 times that of the IBM RS/6000-3CT. The Power2 CPU is marginally faster than the DEC 600/5/333, and 1.2 times faster than the R8000-based SGI machines and the Sun Ultra-1/170. With a couple of notable exceptions. this ordering is similar to that found for the vector case, where the R10000 just outperforms the Sun Ultra-2/200 and the DEC 600/5/333, which are in turn superior to both the IBM RS/6000-590 and R8000-based SGI machines. The performance of the R10000 in the scalar algorithm is first class, faster than the Cray Y-MP/J90, Cray Y-MP/8128 and Cray YMP C98/4256 by factors of 4.3, 2.3 and 1.2 respectively. The Pentium Pro/200 again fares well, recording comparable scalar timings to the DEC Alpha 600/5-266, Sun Ultra-1/140, and DEC Alpha 2100/5-250, although 1.7 times slower than the R10000. The notably poor performance on the vector algorithm for the HP PA/9000-K460, SGI Indy 5000 and Pentium Pro/200 may be attributed to either use of poorly tuned maths libraries (as on the HP and SGI machine), or to reliance on straight Fortran code (as on the Pentium). A similar effect was seen on the RS/6000-3CT, where the relatively unimpressive timings from the vector algorithm were caused by the un-tuned library DGEMM routine available through -lblas; the corresponding ESSL routine (-lessl) improves performance by a factor of 1.52 on the IBM SP2. The Cray YMP-C98 at last justifies its supercomputer tag, outperforming the SGI R10000, R8000 and RS/6000-3CT by factors of 2.6, 3.2 and 3.6 respectively; the same cannot be said for the Cray Y-MP/J90, which remains a factor of 1.7 slower than the R10000. The latter outperforms the R5000 by factors of 3.4 (scalar) and 5.3 (vector). As noted above all of the more recent CPUs (with the exception of the PA/9000-K460 and Pentium Pro) exhibit superior performance on the vector algorithm, with average factors of 2.1 (DEC Alpha 600/5-333), 2.0 (SUN Ultra-1/170), 1.8 (DEC Alpha 8400/300 and HP PA/9000-735), 1.7 (SGI R10000, SUN Ultra-2/200 and SGI R8000), and 1.6 (IBM RS/6000, with the exception of the 590). Much higher factors are found with the vector CPUs; the figure of 4.2 on the Cray J90 leads to the Cray being competitive on the vector algorithm, but slower than the leading 24 workstations on the scalar code. Note again the inadequacies of the FORTRAN compiler on the Cray T3D; the unexceptional scalar algorithm timing of 79.3 secs. (to be compared with that of 45.1 secs. on the DEC AXP/3000-500), improves significantly with the vector algorithm, where use of the BLAS routines produces timings of 27.5, to be compared with 23.9 secs on the AXP/3000-500. This effect is also seen in comparison with the KSR-2 and IBM SP2 timings; the T3D is slower by a factor of 1.4 on the scalar algorithm, and faster by a factor of 1.3 in the vector case compared to the KSR-2, while the differential with the SP2 is reduced from 5.8 in the scalar case to 3.3 for the vector algorithm. 2.3 Diagonalization Benchmark Table 4 presents the results of a matrix diagonalization benchmark intended to supplement the previous analysis conducted by Dunning and co-workers [4]. We consider a similar benchmark, based on diagonalizing a series of real symmetric matrices, with rank 10, 20, 30, ... 100, using 64-bit floating point arithmetic. Again the CPU time was measured for the diagonalization of each size matrix, with the summed times used as the benchmark execution time. Results are presented for a range of compiler options available on the depicted hardware. While the previous analysis was restricted to the EISPACK RS routine, we consider below the performance of eight diagonalization routines available in various mathematical libraries and quantum chemistry codes: (i) EIGRS, an unoptimized FORTRAN version of the library routine RS (available in SCILIB on the Cray) from the IMSL library of routines [5]. (ii) F02ABF from the NAG library [6]. (iii) HQRII [7], as implemented in the semiempirical MOPAC program [8]. (iv) GIVENS, adapted from the QCPE program exchange (number 62.1). (v) SDIAG2, as implemented in the MUNICH system of programs. (vi) JACOBI, from the ATMOL system of programs [9]. (vii) JACO, the diagonalization routine from the direct-SCF program DISCO [10]. (viii) ERDUW, as taken from the Berkeley System of Quantum Chemistry codes. The first four routines are all based on the Householder QR method, whilst the last four use the Jacobi method. Note that the only optimization performed involved inserting calls to the BLAS for two-dimensional rotations (DROT) and vector interchange (DSWAP). The timings of Table 4 suggest that the SGI R10000/195 is again the fastest CPU, just ahead of the HP PA/9000-K460 and DEC Alpha 600/5-333, and 1.5 times faster than the Sun Ultra-2/200 and DEC Alpha 8400/5-300. The R8000-based machines, HP/9000-735/125 and IBM RS/6000-3CT are seen to exhibit comparable timings (8.0-8.1 secs.), a factor of 2.5 times slower than the R10000. This benchmark tends to be dominated by the slowest of the diagonalization routines in use, JACO, which typically accounts for > 40% of the total CPU time. Significantly the leading twenty workstations are seen to outperform the Cray YMP/C98, while the Cray Y-MP/J90 is bettered by the leading 44 workstation CPUs. The Pentium Pro is seen to be five times faster than the J90, and is only outperformed by the leading six workstation CPUs. The performance of the Cray T3D node is comparable to the IBM RS/6000-350, and again significantly slower than the IBM-SP2 TN2 node (21.7 secs. vs. 9.3 secs.) 2.4 Relative Performance on Matrix Operations To summarize the performance of the various workstations on the matrix multiply and diagonalization benchmarks detailed above, we show in Table 5 the performance of each relative to the SGI R10000/195. It is clear from these figures that the SGI R10000 and PA8000 processor (in the HP PA/9000-K460) lie ahead of the competition, with the R10000 1.3 times faster than the DEC Alpha 600/5-333 and 1.4 times faster than the Sun Ultra-2/200. While the PA8000 is marginally slower than the R10000, we belief that the arrival of tuned maths libraries on the former will reverse this order to provide a picture more consistent with the SPECfp95 ratings. We see that the relative ordering of processors within a given family are broadly in line with clock speeds. Considering the EV5-based CPUs, we find the DEC Alpha 600/5-333, 8400/5-300, 600/5-266 and 2100/5-250 to be slower than the R10000 by factors of 1.25, 1.49, 1.82 and 1.67 respectively. For the Sun Ultra, the Sun Ultra-2/200, Sun Ultra-1/170, and Sun Ultra-1/140 are slower than the R10000 by factors of 1.43, 1.69 and 2.05 respectively. We also note the following: - the 266 MHz EV5-based CPU outperforms the corresponding EV4 by a factor of 1.33; - the R10000 exhibits a speed up of 1.7 against its predecessor, the R8000 in the Power Onyx, and a speed up of 3.4 against the R5000 (due in the main to the poor library performance on the R5000); - the R8000 exhibits a speed up of 3.3 against its predecessor, the R4400 in both the Indigo2 and Challenge L, and, - the position of the Pentium Pro as the 14th fastest CPU of those considered will undoubtedly improve given the advent of optimised libraries (not available in this current exercise). 3. Computational Chemistry Kernels One of the crucial requirements in evaluating the increasingly broad range of hardware platforms, whether these be parallel machines (true MIMD message-passing machines, workstation clusters, shared-memory multiprocessors etc), or simply the lastest workstation, is the availability of portable benchmarking codes that are representative of the application area under consideration. In an attempt to provide such capabilities in computational chemistry, we have described previously four representative codes, each of which is less than 1000 lines of FORTRAN, and is sufficiently portable that migration to any hardware platform can typically be achieved in a matter of hours. In this report we limit our discussion to the performance of these codes on a variety of single CPUs. The benchmarking kernels comprise the following programs that are realistic models of actual chemical applications or algorithms; 1. Self Consistent Field (SCF); This Self Consistent Field (SCF) electronic structure kernel uses distributed primitive 1s gaussian functions as a basis (thus emulating use of s,p,... functions) and computes integrals to essentially full accuracy. It is a direct SCF code, with an atomic density used for a starting guess. There are two available problem sizes, corresponding to 60 basis functions Be4 and 240 basis functions (Be16). The timings of Table 6 refer to the former. 2. Molecular Dynamics (MD); This program bounces a few thousand argon atoms around in a box with periodic boundary conditions. Pairwise interactions (Leonard-Jones) are used with a simple integration of the Newtonian equations of motion. 3. Monte Carlo (MC); This code evaluates the energy of the simplest explicitly correlated electronic wavefunction for the He atom ground state using a variational monte-carlo method without importance sampling. 4. Jacobi iterative linear equation solver (JACOBI)]; Uses a naive jacobi iterative algorithm to solve a linear equation. All the time is spent in a large matrix vector product. Total CPU timings for the SCF, MD and MC benchmarks are presented in Table 6, together with the Mflop ratings from the JACOBI benchmark. These results present a somewhat confusing picture, with the processor ordering very much a function of the particular chemistry kernel under examination. With the exception of the JACOBI benchmark, the SGI R10000/195, DEC Alpha 600/5-333 and 8400/5-300, and Sun Ultra-2/200 processors are seen to be the superior CPUs, although the processor ordering in the SCF, MD and MC benchmarks varies significantly. Thus for the SCF kernel, the SGI R10000 and Alpha 600/5-333 are 1.5 times the speed of the HP PA/9000-K460, twice the speed of the Sun Ultra-2/200 and three times that of the POWER2 RS/6000. The HP/9000-735/125 exhibits good relative performance - it is 1.3-1.4 times faster than the R8000 and POWER2 RS/6000 (TN2 and 3CT). The Sun SS20/HS21 is also seen to perform well on this kernel, with the same execution time as the latter CPUs. The performance of the Pentium Pro/200 matches that of the SGI R8000 and and POWER2 RS/6000. The SGI R10000 is clearly the optimum processor in the MD benchmark, followed by the Sun Ultra-2/200 and Alpha 600/5-333. The POWER2 is seen to perform very poorly in the MD Benchmark where it is apparently almost 4.5 times as slow as the R10000, with the 3CT 3.8 times slower than the Sun Ultra-2/200. In fact the whole family of RS6000 processors remains consistently unimpressive on this benchmark. The relative processor ordering found in the MD and SCF kernels is seen to be markedly different to that suggested by the JACOBI benchmark. The Mflop ratings of Table 6 suggest that the Power2 3CT is the optimum CPU, with the 81 Mflop rating 2.1 times that achieved on the SGI R10000, 2.5 times that found on the R8000 (32.9 Mflop), and 2.6 times that recorded on the HP PA/9000-K460 (31.0 Mflop). The Sun Ultra performance on JABOBI is also impressive, with the Ultra-2/200, and Ultra-1/170 and Ultra-1/140 all surpassing the MFlop rate on the EV5 and R10000 processors. In the MC benchmark, the Alpha 600/5-333 and SGI R10000 are the fastest processors, twice the speed of the RS/6000 POWER2 and Ultra-2/200. Comparing the R10000/195 and R8000 processors, the R10000 is 3.2 times faster in the SCF kernel, 2.3 in the MC kernel, but only 1.2 times faster in JACOBI. The Indy R5000 demonstrates comparable performance to the R8000 - it is slower than the R10000 in the SCF, MD, MC, and JACOBI benchmarks by factors of 2.9, 2.1. 1,9 and 3.1 respectively. The performance of the Pentium Pro/200 is perhaps somewhat less impressive than that found in the matrix benchmarks. Its overall performance is similar to that shown by the DEC Alpha 250/4-266 and Indy R5000, approximately one half the speed of the R10000. 4. The Quantum Chemistry Benchmark The benchmark described below (and summarized in Table 7) is designed to highlight the typical range of calculations commonly performed by the ab initio quantum chemist. It includes 12 calculations carried out using the GAMESS-UK electronic structure code, and includes the following functionality; - Conventional SCF Calculations, on morphine and 2,4,6 tri-nitro-toluene (Calculations 1. and 2. respectively); - Valence-only ECP calculations, with a geometry optimization of Na7Mg+ in an ECP-DZ+D(Mg) basis of 70 GTOs (calculation 3). - A Direct-SCF calculation on cytosine (82 GTOs, 6-31G basis) Calculation 4); - Multi-configuration SCF calculations, with a CASSCF geometry optimization on H2CO (Calculation 5), and a larger CASSCF calculation, also on H2CO (Calculation 6); - Configuration interaction calculations, both Direct-CI on the H2CO/H2+CO transition state (Calculation 7), and conventional table driven-CI on TiCl4 (Calculation 8); - Moller Plesset calculations, with a MP2 geometry optimization of H3SiNCO (Calculation 9); - Analytic second derivatives, at both the SCF (pyridine) molecule in a 6-31G basis, Calculation 10) and MP2 level (C4) in a 6-31G* basis, Calculation 11); - A Direct-MP2 calculation on pyridine in a DZ + D(N) basis set (Calculation 12). 4.1 QC Benchmarks - Single Processor Results The data presented in Table 8 is collected under control of the UNIX command time where available, and includes CPU time (both user and system), total elapsed time and Efficiency, measured as CPU versus elapsed. While our original aim was to base comparisons strictly on elapsed times, such timings could not be consistently gathered over the range of machines considered. For example, the range of disk configurations varies enormously, from primitive SCSI disks to striped high-speed raid disks, and the loading on the machines varies, from effectively single-user loading on many of the workstations, to multi-user environments, such as on the Convex. Thus while reporting the elapsed times, we use such figures to identify, where appropriate, the requirement for enhanced disk configurations, rather than as any definite criticism of the machine in question. The total user CPU timings of Table 8 suggest that the DEC Alpha 600-5/333 and SGI R10000/195 are the optimum machines, with summed timings of 23.4 and 23.1 minutes for all 12 calculations. These are significantly less than those for the leading machines from Sun and IBM which exhibit summed timings of 31.5 and 40.1 for the Sun Ultra-2/200 and RS/6000-3CT respectively. A somewhat different picture emerges when considering the system CPU and Elapsed times. With the exception of the AXP and SGI R10000, all machines exhibit a system CPU time of the order of 10-15% of the user time; this percentage increases significantly, particularly on the AXP, to between 20-40% on the systems of Table 8. Considering the elapsed times and associated efficiences. the R8000 based machines from SGI appear to be the most balanced. Both the R8000 Power Onyx and Indigo2 exhibit efficiences of > 95%, to be compared with figures of 76%, 64% and 59% for the RS/6000-3CT, 9000-735/125 and Alpha 600/5-266. What is noticeable is the significant improvements in these efficiency ratios on the more recent Sun (Ultra-2/200) and Digital hardware (both the DEC Alpha 600/5/333 and DEC Alpha 2100/5/250) compared to the figures recorded in the past. Initial experience with the HP PA/9000-K460 suggested that the compiler was too unreliable to even attempt to perform the GAMESS-UK Benchmark, with numerous routines mis-compiling. The poor elapsed time on the Sun Ultra-1/140 was due in part to the limited memory on the machine (32 MByte). Overall factors of 10.6 (in total CPU) and 13.1 (in elapsed times) are found when comparing the ``slowest'' (Sun SPARCstation 10/30) and ``fastest'' (SGI R10000 Power Onyx) machines in Table 8. The corresponding CPU factors in both the Matrix and Chemistry Kernels are somewhat higher, 18.9 and 11.2 respectively. Considering machines from a given vendor, we find that the EV5-based Alpha 600/5/266 outperforms the corresponding EV4 system, the 250/4/266 by factors of 1.5 (CPU) and 1.4 (elapsed). The R10000 from SG is found to be approximately twice the speed of the R8000-based machines, and 3.2 times as fast as the Indy R5000. The R8000-based machines in turn are found to perform some 1.9 times faster than the corresponding Power Challenge L and R4400 Indigo2. Significantly higher ratios are found in some of the individual calculations of Table 7, with ratios of 2.5 - 2.8 found in the MCSCF, direct-CI, MP2 and 2nd derivative calculations. Two of the 12 benchmark calculations impact seriously on the final ratios, the ECP and MRDCI calculations exhibiting negligible speedups of 1.13 and 1.18 respectively. 5. Summary As a summary of this work, we present in Table 9 the relative performance of 34 of the leading workstations against the DEC Alpha 600/5/333 in terms of quoted SPEC (``Systems Performance Evaluation Cooperative'') benchmarks, and those from the present Matrix, Chemistry Kernels and GAMESS-UK benchmarks. Note that this analysis has been somewhat complicated by the inconsistent approach adopted by some vendors to providing a smooth transition between the older SPECfp92 and SPECint92 values, and the more recent SPECfp95 and SPECint95 benchmark. SGI in particular appear to provide only SPECfp95 values for the R10000 and R5000, and only SPECfp92 values for their older processors. In the following discussion we have used the SPEC-95 results when available (see Table 9) The SPEC benchmark suite contains non-tuned application-based code to measure processor speed for both integer (SPECint) and floating point (SPECfp) arithmetic. Based on the published SPECfp ratings, and normalising with respect to the DEC Alpha 600/5/333, we would expect the PA8000 processor of the HP PA/9000-K460 (124%) to be the fastest CPU, followed by the DEC Alpha 600/5/333 itself, the SGI R10000/195 (94%) and DEC Alpha 8400/5/300 (94%), the DEC Alpha 600/5/266 CPU (89%), the 200 MHz Sun Ultra-2/200 (84%), and the IBM Power2 RS/6000-3CT (77%) (where the %-values in parentheses indicate performance relative to the Alpha 600/5/333). Based on these relative SPECfp values given in the table, we expect a factor of 12 between the fastest and slowest processor, the Sun SPARC/10-30. A somewhat different processor ordering is revealed by the SPECint ratings, with the processors from SGI (notably the R8000) and IBM (the Power2) significantly slower than those from DEC, Sun and the HP (PA8000). It is perhaps worth noting that SGI have not as yet published the SPECint95 rating for either the R10000 or R5000. We note also that the Specint95 ratings suggest that Pentium Pro/200 is some 88% of the DEC Alpha 600/5/333, to be compared with the smaller rating of 51% based on SPECfp95. When considering the results, there are several factors we wish to consider based on the present evaluation exercise: 1. Do the SPECfp values provide a reliable metric for evaluating the capabilities of hardware in computational chemistry? If this so, we would expect to find a close mapping of the ratios for the various chemistry benchmarks onto the SPECfp ratios (note that the CPU values for the GAMESS-UK benchmark are used, since SPEC does not adequately incorporate I/O in its evaluation); 2. Does any particular CPU consistently ``underperform'' based on the SPECfp criteria? - this would manifest itself as the ratios from the chemistry benchmarks falling below the SPECfp ratios; 3. Do the ``simple'' Matrix and Chemistry Kernel benchmarks lead to the same conclusions as the GAMESS-UK benchmarks? In terms of relative speed, we find that all the chemistry benchmarks are broadly in line with the SPECfp predictions, the only notable exceptions being summarised below: - The poor performance of the HP PA/9000-K460 - while the matrix kernels are in line with the SPECfp ratio, the chemistry kernels would appear to be running at around half the expected speed. - The impressive performance of the SGI R10000 on all the benchmarks, with figures of 130%, 104% and 116% on the matrix, kernels and GAMESS-UK benchmarks, as against the value of 94% based on the SPECfp95 figures. Indeed, the R10000 would certainly appear to be the optimum CPU based on the benchmarks conducted in this report. The R5000 appears, however, to follow closely the SPECfp95 ratings. - There is some evidence from Table 9 that neither the DEC EV5-based Alpha 600/266 or the 8400/300 are performing as well as the SPEC ratings might suggest, with all benchmark ratios some 10% lower than expected based on SPECfp alone. In contrast the DEC Alpha 2100/5/250 is performing consistently above its SPEC rating. - The UltraSPARC systems from Sun appear to be performing exactly in line with the SPECfp95 ratings. - The R8000-based systems perform well on the matrix benchmarks, but are closer to the SPECfp ratings on the kernels and GAMESS-UK. - All IBM Power1 RS/6000 CPUs exhibit enhanced performance on the chemistry codes relative to the SPEC rankings e.g.. the SPECfp ratio of the RS/6000-370 to DEC 600/5 is 22%, to be compared with the Matrix, Kernels and GAMESS-UK ratios of 30%, 37% and 36% respectively. - A similar effect is shown with the HP PA/9000-735/125, where the SPECfp ratio of 35% increases to 54%, 40% and 52% for the chemistry benchmarks. - The potential of the Pentium Pro is evident, with the performance in the Matrix benchmarks exceeding the SPECfp95 figures. References [1] M.F. Guest and S. Wilson, Daresbury Laboratory Preprint, DL/SCI/P290T; Supercomputers in Chemistry, ed. P.Lykos and I.Shavitt, A.C.S. Symposium series 173 (1981) 1; V.R. Saunders and M.F. Guest, Comp.Phys.Comm., 26 (1982) 389: M.F. Guest, in ``Supercomputer Simulations in Chemistry'', Ed. M. Dupuis, Lecture Notes in Chemistry, 44, Springer Verlag (1986) 98. [2] M.F. Guest, R.J. Harrison, J.H. van Lenthe and L.C.H. van Corler, ``Computational Chemistry on the FPS-X64 Scientific Computers: Experience on single- and multi-processor systems'', Theoret. Chim. Acta 71 (1987) 117. [3] GAMESS-UK is a package of ab initio programs written by M.F. Guest, J.H. van Lenthe, J. Kendrick, K. Schoeffel and P. Sherwood, with contributions from R.D. Amos, R.J. Buenker, M. Dupuis, N.C. Handy, I.H. Hillier, P.J. Knowles, V. Bonacic-Koutecky, W. von Niessen, R.J. Harrison, A.P. Rendell, V.R. Saunders, and A.J. Stone. The package is derived from the original GAMESS code due to M. Dupuis, D. Spangler and J. Wendoloski, NRCC Software Catalog, Vol. 1, Program No. QG01 (GAMESS), 1980. [4] R. Shepard, R.A. Bair, R.A. Eades, A.F. Wagner, M.J. Davis, C.B. Harding and T.H. Dunning Jr., Int. J. Quant. Chem. , (1983) 17; R.A. Bair and T.H. Dunning Jr., J.Comp.Chem., 5 (1984) 44; R. Bair, ``FPS-164 Matrix Multiplication Subroutine Guide'', Argonne National Laboratory, (1984); T.H. Dunning Jr. and R.A. Bair, ``Advanced Theories and Computational Approaches to the Electronic Structure of Molecules'', NATO ASI Series, D. Reidel, 1984, p1. [5] IMSL Program Library, 1978. [6] NAG Fortran Library, Numerical Algorithms Group Ltd, 1984. [7] Y. Beppu, Computers and Chemistry, 6 (1982). [8] J.P. Stewart, ``MOPAC - A General Molecular Orbital Package'', QCPE 455, 1984. [9] V.R. Saunders and M.F. Guest, ``ATMOL3 Part 9'', RL-76-106, 1976; M.F. Guest and V.R. Saunders, Mol.Phys., 28 (1974) 819; D. Moncrieff and V.R. Saunders, ``ATMOL-Introduction Notes'', UMRCC, May, 1986; Cyber-205 Note Number 32, UMRCC, September, 1985. [10] J. Almlof et al, J.Comp.Chem., 3 (1982) 385. Performance of Various Computers in Computational Chemistry Table 1. Vector Whetstone Benchmark. Total CPU times (seconds), Mflop ratings (see text) and MWIP ratings ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Machine Mflop Ratings (VL=1024) Total CPU MWIPS N2 N3 N8 (seconds) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ iPSC/860 (RX) 4.6 4.4 5.3 282.7 15.0 Cray T3D (AXP) 9.8 8.4 7.3 120.5 33.5 KSR-2 32.8 31.3 29.7 68.6 59.6 IBM SP2 (TN2 node) 49.2 38.2 49.3 35.0 116.5 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Sun 4/370 2.0 1.8 1.0 642.8 6.3 SOLBOURNE S4000 1.4 1.3 0.9 629.3 6.4 Sun SPARCstation 2/GS 4.3 3.2 1.8 366.7 11.0 DEC S5000/120 4.5 4.0 2.7 351.3 11.5 IBM RS/6000-320 9.4 2.4 1.3 305.3 13.3 SGI 4D/220 5.6 4.4 2.9 289.5 14.0 Stardent 1520 6.3 5.9 6.0 283.2 14.5 DEC S5000/200 6.4 5.4 3.4 274.7 14.8 SGI R3000 Indigo 6.8 3.7 3.7 233.8 17.3 SGI 4D/320 7.6 5.9 3.6 227.0 18.0 Sun SPARC/5-85 3.3 3.1 4.3 205.5 19.7 Stardent VISTRA-800 4.7 4.4 5.3 196.5 19.0 SGI 4D/420 9.4 6.9 4.4 188.0 21.6 Sun SPARC/10-30 7.0 3.4 4.0 177.2 21.0 Sun SPARC/10-41 9.4 8.1 5.3 145.0 26.5 SGI IRIS Crimson 21.8 14.3 6.1 121.7 33.7 IBM RS/6000-540 15.1 7.7 5.7 120.3 33.8 HP PA/9000-720 11.6 11.1 9.3 119.3 34.0 IBM RS/6000-340 17.9 4.0 6.1 115.9 34.8 Sun SPARCserver 1000 12.5 10.9 6.5 111.6 33.8 SGI R4000 Indigo 21.8 13.6 6.4 105.8 38.1 IBM RS/6000-530H 16.4 10.4 6.8 102.0 39.9 RS/6000 PowerPC-250 15.1 8.4 5.4 95.0 38.7 IBM PowerPC-25T 15.1 8.4 6.4 93.2 41.1 HP PA/9000-730 14.0 14.2 11.5 93.4 43.4 SGI Challenge L/100 21.8 13.6 9.1 90.8 43.7 IBM RS/6000-550 21.8 10.8 7.9 86.8 46.6 IBM RS/6000-350 19.7 8.0 7.7 84.8 46.9 DEC AXP/3000-300 19.4 15.7 10.3 79.1 50.9 IBM RS/6000-360 24.6 9.0 9.2 70.7 56.1 DEC AXP/3000-500 20.8 16.9 10.7 68.7 58.7 DEC AXP/3000-600 26.2 19.8 12.7 64.4 62.8 HP PA/9000-750 15.1 27.5 24.3 64.1 63.6 SGI R4400 Indigo^2 32.7 19.9 13.1 62.3 63.8 SGI Challenge L/150 32.8 20.5 14.2 62.9 63.3 IBM RS/6000-370 32.8 12.0 11.5 56.5 70.2 HP PA/9000-715/100 32.8 29.9 15.8 54.5 73.3 Sun SPARCstation-20/HS21 30.0 25.5 18.2 49.8 81.6 HP PA/9000-J200 39.3 32.8 33.9 41.0 99.2 HP PA/9000-755 39.3 44.4 30.9 38.9 104.7 DEC AXP/3000-700 34.1 25.6 23.6 36.5 111.1 RS/6000 PowerPC-43P 21.9 9.8 24.2 36.4 92.2 SGI R8000 Indigo^2 27.0 26.2 109.2 36.4 112.4 SGI R8000 PowerOnyx 27.1 26.2 109.6 36.2 112.8 IBM RS/6000-590 32.8 31.3 44.2 34.8 117.3 IBM RS/6000-3CT 39.3 37.2 46.8 34.4 117.6 IBM RS/6000-3BT 39.2 37.2 47.2 34.2 118.9 Pentium Pro/200 41.8 35.2 21.7 32.3 123.7 HP PA/9000-735/125 39.3 57.3 38.9 30.8 132.0 DEC Alpha 250/4-266 36.6 34.8 72.5 26.9 150.5 Sun Ultra-1/140 19.9 19.3 170.9 26.3 155.1 Sun Ultra-2/200 29.8 27.0 239.6 18.7 218.2 DEC Alpha 2100/5-250 143.9 39.4 107.4 17.0 238.1 DEC Alpha 600/5-266 83.9 83.9 126.3 15.8 256.1 DEC Alpha 8400/5-300 94.4 97.9 133.5 14.2 286.7 HP PA/9000-K460 196.6 196.6 190.5 13.8 298.3 DEC Alpha 600/5-333 201.4 52.4 138.7 12.8 311.0 SGI PowerOnyx 10000/195 118.6 76.0 139.2 8.5 476.8 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Convex C-220 21.4 17.7 15.7 59.6 70.0 Convex C-3860 54.0 44.3 37.8 23.0 185.2 CRAY YMP/J90 115.9 117.9 145.9 16.6 260.2 CRAY Y-MP/8128 190.0 193.5 297.2 7.9 552.0 CRAY YMP-C98/4256 542.1 539.3 668.7 3.9 1114.0 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Table 2. Sparse MMO Benchmark: Total CPU times (seconds) for a series of sparse MMOs (R = A X B, see text) implemented in Fortran. ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Machine Sparsity in B-Matrix 0% 50% ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ iPSC/860 RX-node 21.2 11.0 KSR-2 11.3 5.9 Cray T3D AXP-node 8.5 4.5 IBM SP2 TN2-node 1.8 1.1 Solbourne S4000 74.4 38.4 Sun 4/370 57.4 30.6 DEC S5000/120 50.7 25.9 HP/Apollo DN10020 44.2 22.8 SGI 4D/220 39.4 20.1 DEC S5000/200 33.1 17.1 SGI R3000 Indigo 31.0 14.3 SGI 4D/320 27.9 14.4 Sun SPARCstation 2/GS 27.5 14.4 Stardent 1520 26.6 17.0 SGI 4D/420 23.7 12.1 Stardent VISTRA-800 20.4 10.6 Sun SPARCstation 10/30 16.1 7.9 Sun SPARCstation 5/85 14.9 7.8 Stardent 3020 14.7 9.1 IBM RS/6000-320 14.6 7.1 SGI R4000 Indigo 12.6 6.4 SPARCstation 10/41 11.8 6.1 SGI IRIS Crimson 11.0 5.6 SGI Challenge L/100 10.0 4.9 IBM RS/6000-530 9.3 4.9 Sun SPARCserver 1000 9.3 4.7 IBM PowerPC-25T 9.2 4.3 RS/6000 PowerPC-250 9.1 4.4 IBM RS/6000-340 8.9 4.1 HP PA/9000-720 8.5 4.8 IBM RS/6000-530H 7.8 4.1 IBM RS/6000-350 7.6 3.6 SGI R4400 Indigo^2 7.1 3.4 SGI Challenge L/150 7.1 3.4 HP PA/9000-730 6.7 3.5 IBM RS/6000-360 6.4 3.1 DEC AXP/3000-300 6.1 3.3 DEC AXP/3000-500 5.7 2.9 IBM RS/6000-550 5.6 3.1 HP PA/9000-750 5.1 2.7 IBM RS/6000-370 5.1 2.4 DEC AXP/3000-600 5.0 2.6 RS/6000 PowerPC-43P 4.3 2.0 HP PA/9000-715/80 3.7 2.0 DEC AXP/3000-700 3.7 1.8 Sun SPARCstation 20/HS21 3.5 1.8 Sun Ultra-1/140 3.4 1.7 DEC Alpha 250/4/266 3.2 1.6 HP PA/9000-755 3.1 1.7 HP PA/9000-715/100 3.0 1.6 Sun Ultra-1/170 2.8 1.4 DEC Alpha 2100/5/250 2.6 1.3 HP PA/9000-735/125 2.5 1.3 Sun Ultra-2/200 2.3 1.2 DEC Alpha 600/5-266 2.3 1.2 Pentium Pro/200 2.3 1.2 HP PA/9000-J200 2.1 1.1 DEC Alpha 8400/5-300 2.1 1.1 IBM RS/6000-3BT 2.1 1.1 IBM RS/6000-590 1.9 1.0 DEC Alpha 600/5-333 1.9 1.0 SGI R8000 Indigo^2 1.8 1.1 SGI R8000 Power Onyx 1.8 1.1 IBM RS/6000-3CT 1.8 1.0 SGI PowerOnyx 10000/195 1.1 0.6 HP PA/9000-K460 0.9 0.5 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Alliant FX2808 (1CE) 17.2 9.3 FPS-M64/60 17.1 8.9 Convex C-220 10.6 6.5 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ IBM 3090-600-E/VF 11.3 6.0 Convex C-3860 5.2 3.3 Cray X-MP/416 2.8 1.8 Cray YMP/J90 2.6 1.8 Cray Y-MP/8128 1.5 0.9 CRAY YMP C98/4256 0.9 0.6 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Table 3. Sparse MMO Benchmark: Total CPU times (seconds) for a series of Similarity Transformations (H=Q*HQ, see text) using both Scalar and Vector Algorithms. Machine Algorithm Scalar Vector ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ T800-20 5176.0 4439.0 iPSC/2 SX-node 3809.6 4456.1 Meiko MK086 node 240.1 262.2 iPSC/860 RX-node 118.8 60.1 KSR-2 55.3 34.8 Cray T3D AXP-node 79.3 27.5 IBM SP2 TN2-node 13.8 8.5 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SOLBOURNE S4000 711.9 750.2 Dec S5000/120 710.2 724.6 Sun 4/370 615.9 609.6 Dec S5000/200 368.3 445.1 SGI 4D/220 344.8 440.3 Sun SPARCstation 2/GS 333.3 394.0 SGI R3000 Indigo 285.0 356.4 SGI 4D/320 245.5 329.5 HP/Apollo DN10020 273.8 245.9 Stardent 1520 236.9 252.8 SGI 4D/420 200.1 273.8 Stardent VISTRA-800 177.0 209.4 Stardent 3020 160.4 144.2 Sun SPARCstation 10/30 141.5 162.3 Sun SPARCstation 10/41 111.3 119.3 Sun SPARCstation 5/85 105.9 151.6 Sun SPARCserver 1000 88.8 92.6 SGI Indigo R4000 98.2 78.7 SGI IRIS Crimson 94.2 78.7 IBM RS/6000-320 139.0 73.3 IBM PowerPC-25T 88.2 68.9 RS/6000 PowerPC-250 92.5 68.7 HP PA/9000-720 124.7 66.5 SGI Challenge L/100 74.9 58.2 HP PA/9000-730 89.9 48.4 IBM RS/6000-530 96.3 46.9 IBM RS/6000-340 70.4 43.4 HP PA/9000-750 58.6 41.5 SGI Indigo^2 R4400 52.3 39.8 SGI Challenge L/150 56.5 39.0 IBM RS/6000-540 66.9 38.4 IBM PowerPC-43P 44.3 36.4 Sun SPARCstation 20/HS21 42.2 35.1 IBM RS/6000-350 55.8 34.8 HP PA/9000-715/80 52.7 34.4 DEC AXP/3000-300 61.0 34.0 IBM RS/6000-530H 58.8 34.0 SGI Indy R5000 34.7 32.1 HP PA/9000-715/100 47.0 29.5 IBM RS/6000-360 48.0 29.3 IBM RS/6000-550 48.3 27.7 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ DEC AXP/3000-500 45.1 23.9 HP PA/9000-735 34.8 20.0 IBM RS/6000-370 37.6 23.3 DEC AXP/3000-600 38.5 20.2 HP PA/9000-755 35.6 20.1 Pentium Pro/200 17.1 23.2 HP PA/9000-J200 33.5 16.2 IBM RS/6000-3BT 30.8 16.2 HP PA/9000-735/125 29.2 16.2 DEC AXP/3000-700 28.3 16.2 DEC Alpha 250/4-266 24.2 13.1 HP PA/9000-K460 10.9 12.0 DEC Alpha 600/5-266 17.7 10.2 IBM RS/6000-3CT 12.6 9.7 Sun Ultra-1/140 17.1 9.5 SGI R8000 Indigo^2 15.2 8.7 SGI R8000 Power Onyx 15.1 8.7 DEC Alpha 2100/5-250 17.7 8.2 Sun Ultra-1/170 15.5 7.9 DEC Alpha 8400/5-300 13.8 7.9 Sun Ultra-2/200 11.5 6.8 DEC Alpha 600/5-333 13.2 6.2 SGI PowerOnyx 10000/195 10.2 6.1 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Alliant FX2800 (1CE) 243.1 86.3 FPS-M64/60 141.2 50.8 CONVEX C-220 128.6 49.0 CONVEX C-3860 55.1 20.1 Cray YMP/J90 44.1 10.6 Cray Y-MP/8128 23.2 5.7 Cray YMP C98/4256 12.6 2.6 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Table 4. Matrix Diagonalization Benchmark. Total CPU times (seconds) for a series of Matrix Diagonalizations (see text) using eight Different Routines. ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Machine CPU Time Compiler (seconds) Options ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ T800-20 1100.5 iPSC/2 (SX) 1059.0 -OLM MK086 i860 66.8 -OLM iPSC/860 (RX) 62.3 -O3 KSR-2 27.3 -O2 Cray T3D (AXP) 21.7 -O IBM SP2 (TN2) 9.3 -O3 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Stardent 1520 255.0 -O2 Sun 4/370 219.9 -O SOLBOURNE S4000 169.0 -O3 DEC S5000/120 145.8 -O2 Sun SPARCstation 2/GS 103.3 -O SGI 4D/220 97.4 -O2 Apollo DN10020 96.2 -O DEC S5000/200 90.6 -O2 SGI R3000 Indigo 78.8 -O2 Stardent 3020 68.1 -O2 SGI 4D/320 67.2 -O2 Stardent VISTRA 59.2 -O3 SGI 4D/420 58.1 -O2 IBM RS/6000-320 46.4 -O Sun SPARCstation 10/30 42.2 -O -dalign Sun SPARCstation 10/41 35.9 -O -dalign IBM RS/6000-530 35.6 -O Sun SPARCstation 5/85 32.4 -O -dalign HP PA/9000-720 31.9 -O IBM RS/6000-540 30.8 -O SGI IRIS Crimson 27.6 -sopt IBM RS/6000-340 27.6 -O IBM RS/6000-530H 26.0 -O SGI R4000 Indigo 26.0 -O -mips2 RS6000 PowerPC-250 25.1 -O Sun SPARCserver 1000 24.7 -O -dalign HP PA/9000-730 24.3 -O IBM PowerPC-25T 24.0 -O3 IBM RS/6000-550 22.2 -O IBM RS/6000-350 21.3 -O HP PA/9000-750 20.8 +O3 SGI Challenge L/100 20.4 -O -mips2 IBM RS/6000-360 17.7 -O HP PA/9000-715/80 15.9 +O3 SGI Challenge L/150 15.6 -O -mips2 DEC AXP/3000-300 15.5 -O SGI R4400 Indigo^2 15.2 -O -mips2 DEC AXP/3000-500 14.9 -O IBM RS/6000-370 14.2 -O3 HP PA/9000-715-100 12.8 +O3 Sun SS20/HS21 12.4 -O -dalign Sun SPARCstation 20/HS21 12.4 -O -dalign DEC AXP/3000-600 12.1 -O IBM PowerPC-43P 11.2 -O3 qarch=ppc HP PA/9000-735 10.0 +O3 HP PA/9000-755 10.2 +O3 HP PA/9000-J200 9.6 +O4 IBM RS/6000-3BT 9.4 -O3 qarch=pwr2 IBM RS/6000-590 9.0 -O3 qarch=pwr2 DEC AXP/3000-700 8.7 -O IBM RS/6000-3CT 8.1 -O3 qarch=pwr2 HP PA/9000-735/125 8.1 +O3 SGI R8000 Indigo^2 8.0 -O3 -mips4 SGI R8000 Power Onyx 8.0 -O3 -mips4 SGI Indy R5000 7.7 -O3 -mips4 DEC Alpha 250/4-266 7.3 -fast Sun Ultra-1/140 6.2 -fast -O4 DEC Alpha 600/5-266 5.6 -fast Sun Ultra-1/170 5.4 -fast -O4 Pentium Pro/200 5.3 -G6 -O2 DEC Alpha 2100/5-250 5.2 -fast DEC Alpha 8400/5-300 4.6 -fast Sun Ultra-2/200 4.5 -fast -O4 DEC Alpha 600/5-333 3.9 -fast HP PA/9000-K460 3.5 +Oaggressive SGI PowerOnyx 10000/195 3.1 -O3 -mips4 etc ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Convex C-220 86.5 -O2 Alliant FX2808 99.5 -Og FPS-M64/60 80.7 OPT3 Convex C-3860 36.0 -O2 Cray X-MP4/16 21.3 Cray YMP/J90 26.7 Cray Y-MP4/64 16.0 Cray YMP C98/4256 9.9 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Table 5. The Matrix Benchmark: Performance relative to the SGI Power Onyx R10000/195 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Machine MMO MMO Diagonal Total (FORTRAN) (Q*HQ) -ization ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SGI R10000/195 100% 100% 100% 100% HP PA/9000-K460 123% 57% 90% 90% DEC Alpha 600/5-333 61% 99% 80% 80% Sun Ultra-2/200 50% 90% 70% 70% DEC Alpha 8400/5 300 55% 78% 68% 67% DEC Alpha 2100/5 250 44% 75% 60% 60% Sun Ultra-1/170 41% 78% 58% 59% SGI R8000 Power Onyx 63% 71% 39% 58% SGI R8000 Indigo^2 63% 71% 39% 58% IBM SP2 (TN2 node) 63% 72% 35% 57% DEC Alpha 600/5-266 50% 60% 56% 55% IBM RS/6000-3CT 63% 64% 38% 55% Sun Ultra-1/140 33% 64% 50% 49% Pentium Pro/200 50% 36% 59% 48% HP/9000-J200 55% 38% 32% 42% IBM RS/6000-3BT 54% 38% 33% 42% DEC Alpha 250/4-266 36% 47% 43% 42% HP PA/9000-735/125 46% 38% 39% 41% Cray YMP/J90 44% 58% 12% 38% DEC AXP/3000-700 31% 38% 36% 35% HP PA/9000-755 37% 31% 31% 33% SGI Indy R5000 25% 22% 41% 29% HP PA/9000-715/100 38% 21% 34% 28% DEC AXP/3000-600 23% 30% 26% 26% Sun SparcStation-20/HS21 33% 17% 25% 25% IBM PowerPC-43P 27% 17% 28% 24% IBM RS/6000-370 22% 26% 22% 24% HP PA/9000-715/80 31% 18% 20% 23% DEC AXP/3000-500 20% 26% 21% 22% IBM RS/6000-360 20% 21% 18% 20% DEC AXP/3000-300 19% 18% 20% 19% IBM RS/6000-550 20% 21% 14% 19% HP PA/9000-750 22% 15% 15% 18% SGI R4400 Indigo^2 16% 15% 21% 17% SGI Challenge L/150 16% 15% 20% 17% Cray T3D AXP 13% 22% 14% 16% IBM RS/6000-350 15% 18% 15% 16% IBM RS/6000-340 13% 14% 11% 13% SGI Challenge L/100 11% 11% 15% 12% IBM PowerPC-25T 12% 9% 13% 12% Sun SPARCserver-1000 12% 7% 13% 11% HP PA/9000-720 13% 9% 10% 11% SGI R4000 Indigo 9% 8% 12% 10% Sun SparcStation-10/41 10% 6% 9% 8% Sun SparcStation-5/85 8% 6% 10% 8% IBM RS/6000-320 8% 8% 7% 8% Sun SparcStation-10/30 7% 4% 7% 6% Stardent VISTRA 6% 3% 5% 5% SGI 4D/420 5% 3% 5% 4% SGI 4D/320 4% 3% 5% 4% SGI R3000 Indigo 4% 2% 4% 3% Sun SPARCstation-2 4% 2% 3% 3% DEC S5000/200 3% 2% 3% 3% Stardent 1520 4% 3% 1% 3% Apollo DN10020 3% 2% 3% 3% SGI 4D/220 3% 2% 3% 3% DEC S5000/120 2% 1% 2% 2% Solbourne S4000 2% 1% 2% 1% ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Table 6. Computational Chemistry Kernels ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Machine Total CPU time (secs) Mflop ===================== SCF MD MC Jacobi ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Sun SPARCstation 10/30 758 2214 299 6.9 Sun SPARCstation 10/41 665 1788 266 6.6 Sun SPARCstation 5/85 1036 1082 195 6.7 Sun SPARCserver 1000 441 783 148 6.7 RS6000 Power-PC 250 603 1322 149 15.6 IBM RS/6000-530H 649 1594 176 26.7 IBM RS/6000-340 692 1608 187 21.2 IBM Power-PC 25T 409 1322 145 15.6 SGI Challenge L/100 400 794 130 9.5 SGI R4000 Indigo 375 809 112 9.5 DEC AXP/3000-300 427 716 98 12.0 IBM RS/6000-350 523 1288 141 27.4 HP PA/9000-750 237 554 163 11.5 %IBM RS/6000-550 563 1266 149 39.9 IBM RS/6000-360 433 1071 117 35.1 HP PA/9000-715/80 220 427 133 17.1 SGI Challenge L/150 233 517 78 13.3 SGI R4400 Indigo^2 234 523 78 13.7 DEC AXP/3000-600 314 541 79 21.6 HP 9000/715-100 177 354 107 17.3 IBM Power-PC 43P 135 470 56 14.8 IBM RS/6000-370 344 854 93 44.2 HP PA/9000-J200 121 292 92 12.4 Sun SPARCstation 20/HS21 132 319 84 16.3 HP PA/9000-755 131 284 102 18.6 DEC AXP/3000-700 146 411 54 21.7 HP PA/9000-735/125 103 236 91 15.0 SGI Indy R5000 124 219 42 12.5 SGI R8000 Indigo^2 139 218 49 23.7 Pentium Pro/200 142 321 38 28.4 SGI Power Onyx R8000 138 218 49 32.9 DEC Alpha 250/4/266 79 272 37 20.9 IBM/RS6000-3BT 140 389 43 44.8 Sun Ultra-1/140 110 186 61 45.2 IBM RS/6000-590 146 453 43 86.0 Sun Ultra-1/170 98 146 58 47.3 DEC Alpha 2100/5/250 59 187 28 27.3 IBM SP2 TN2-node 138 383 43 68.6 HP PA/9000-K460 68 138 31 31.0 DEC Alpha 600/5/266 57 210 31 40.9 IBM RS/6000-3CT 138 462 42 81.1 Sun Ultra-2/200 82 121 49 56.5 DEC Alpha 8400/5/300 50 183 27 43.9 DEC Alpha 600/5/333 46 137 21 44.9 SGI PowerOnyx 10000 43 106 22 39.1 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ CONVEX C-220 1015 1017 329 33.1 CONVEX C-3860 453 342 141 69.9 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Table 7. The GAMESS-UK Single Processor Benchmark Number Module Basis (GTOs) Details Molecular Species ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ 1. SCF STO-3G (124) Morphine 2. SCF 6-31G (154) C6H3(NO2)3 3. ECP Geometry ECPDZ (70) Na7Mg+ Optimization 4. Direct-SCF 6-31G (82) Cytosine 5. CASSCF TZVP (52) 480 csf H2CO Geometry Opt. 6. MCSCF (5s3p2d/3s1p/f(O) 5608 H2CO (74) 7. Direct-CI (5s3p2d/3s1p) 3M/167194 H2CO/H2+CO TS (64) 8. Table-CI (26M/6R) ECP (59) 2301815/4097 TiCl4 9. MP2 Geometry 6-31G* (70) H3SiNCO Optimization 10. SCF Second 6-31G (64) C5H5N Derivatives 11. MP2 Second 6-31G* (60) C4 Derivatives 12. Direct-MP2 DZ+D(N) (76) C5H5N ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Table 8. The GAMESS-UK Benchmark: Total CPU time (user and system) Elapsed time (minutes) and Efficiency (%) for Calculations 1 - 12 (see text) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Machine CPU Time Elapsed Efficiency User System Time (%) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ DEC Alpha 600/5/333 23.4 7.6 34.4 91% SGI PowerOnyx 10000 23.1 3.6 36.7 73% Sun Ultra-2/200 31.5 3.0 38.1 91% DEC Alpha 2100/5/250 30.2 8.2 43.6 88% SGI R8000 Power Onyx 48.1 5.6 55.2 97% Sun Ultra-1/170 40.5 4.9 56.3 81% IBM RS/6000-3CT 40.1 4.4 58.3 76% SGI Indigo^2 R8000 50.8 7.2 60.6 96% IBM RS/6000-590 46.6 4.7 74.8 68% DEC Alpha 600/5/266 30.6 6.4 62.2 59% DEC Alpha 250/4/266 46.0 9.7 85.7 65% DEC Alpha 8400/5/300 26.9 10.4 92.8* 40% HP PA/9000-735/125 51.6 8.4 93.3 64% HP PA/9000-755 64.9 8.8 98.2 75% SGI Indy R5000 72.9 11.3 101.0 83% DEC AXP/3000-700 53.4 11.5 105.4 62% DEC AXP/3000-600 72.1 14.1 107.8 80% IBM RS/6000-370 78.7 8.4 108.8 80% SGI R4400 Challenge L/150 93.3 10.3 110.6 94% SGI R4400 Indigo^2 94.3 10.0 120.6 86% HP 9000/715-100 81.4 14.3 124.7 77% Sun Ultra-1/140 45.3 5.7 139.8* 36% HP PA/9000-715/80 93.7 15.9 140.1 78% DEC AXP/3000/500 93.0 40.1 148.6 90% HP PA/9000-750 111.1 17.4 140.2 92% IBM RS/6000-550 117.6 11.2 146.4 88% SGI Challenge L/100 140.8 17.1 178.0 89% DEC AXP/3000-300 129.8 39.6 184.0 92% Sun SS-20/HS21 82.5 16.2 202.7 49% SGI R4000 Indigo 153.2 17.7 206.0 83% Sun SPARCserver 1000 175.1 50.8 445.6 51% Sun SPARCstation 10/41 201.4 21.0 260.4 85% Sun SPARCstation 5/85 240.5 25.8 299.0 89% Sun SPARCstation 10/30 251.4 31.7 306.3 92% ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ CONVEX C-3860 124.3 3.5 210.9 61% Cray Y-MP/8128 56.8 6.0 188.4 33% Cray YMP-C98/4256 37.9 2.0 41.2 97% ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ * see footnotes to Table 9 Table 9. The Chemistry Benchmark: Performance relative to the DEC Alpha 600/5/333 (see text) Machine SPECfp SPECint Matrix CC GAMESS-UK Kernels CPU Wall ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ DEC Alpha 600/5/333 100 100 100 100 100 100 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ HP PA/9000-K460 124 113 124 76 SGI R10000/195 94 130 104 116 93 DEC Alpha 8400/5/300 94 81 85 85 83 37 * DEC Alpha 600/5/266 89 86 71 76 84 55 Sun Ultra-2/200 84 83 87 86 90 90 IBM RS/6000-3CT 77 37 72 73 70 59 Sun Ultra-1/170 69 60 73 70 68 61 DEC Alpha 2100/5/250 64 65 74 71 81 79 Sun Ultra-1/140 60 50 61 63 61 25 + SGI Power Onyx $ 57 26 75 53 58 62 Pentium Pro/200 51 88 64 48 SGI Indigo^2 R8000 $ 49 27 75 48 54 57 DEC Alpha 250/4/266 48 56 53 53 56 40 DEC 3000/700 AXP $ 43 40 45 38 48 32 SGI Indy R5000 36 39 44 37 34 HP 9000/735-125 35 43 54 40 52 37 HP 9000/755 $ 31 26 43 36 42 35 DEC 3000/600 AXP $ 30 28 33 29 36 17 Sun SS-20/HS21 $ 28 32 34 35 31 17 DEC 3000/500 AXP 28 23 28 19 23 23 HP 9000/715-100 26 31 38 31 32 27 HP 9000/715-80 $ 23 23 31 27 28 24 IBM RS/6000-370 $ 22 17 30 37 36 31 DEC 3000/300 AXP $ 17 16 25 20 18 19 SGI Challenge L/150 $ 16 22 22 26 30 31 SGI Indigo^2 R4400 $ 16 22 23 26 30 28 SPARC SS-1000 $ 15 14 14 14 8 HP 9000/750 $ 14 12 24 21 24 24 IBM RS/6000-550 $ 13 9 24 31 24 23 SGI Challenge L/100 $ 12 15 16 17 20 19 SGI Indigo R4000 $ 11 14 13 17 18 17 Sun SS-10/41 10 12 11 9 14 13 Sun SS-5/85 $ 10 16 10 11 12 11 Sun SS-10/30 $ 10 11 8 9 11 11 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ $ - SPECfp and SPECint rations based on SPEC92 values. * - multi-user environment on DEC Alpha 8400/5/300. + - small memory configuration (32 MByte) on Sun Ultra-1/140. Table 10. APPENDIX I: Machine Configurations under Evaluation ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Machine Configuration Location ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Workstations ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Solbourne S4000 DL (loan) Sun 4/370 DL Sun SPARCstation 2/GS SPARC/40 Mhz DL (loan) Sun SPARCstation 5/85 MicroSPARC II/85 MHz DL (loan) Sun SPARCstation 10/30 SuperSPARC/36 MHz DL (loan) Sun SPARCstation 10/41 SuperSPARC/40 MHz PNL Sun SPARCserver 1000 SuperSPARC/50 MHz DL (loan) Sun SPARCstation 20/HS21 HyperSPARC/125 MHz DL(loan) Sun Ultra-1 Model 140 UltraSPARC-1/143 MHz DL (loan) Sun Ultra-1 Model 170 UltraSPARC-1/167 MHz DL Sun Ultra-2 Model 200 UltraSPARC-2/200 MHz DL (loan) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ HP/Apollo DN10020 PRISM DL HP PA/9000-720 PA7000/50 MHz DL HP PA/9000-730 PA7000/66 MHz MCC HP PA/9000-750 PA7000/66 MHz DL HP PA/9000-715/100 PA7100LC/100 MHz DL (loan) HP PA/9000-715/80 PA7100LC/80 MHz DL (loan) HP PA/9000-755 PA7100/99 MHz DL HP PA/9000-735/125 PA7150/125 MHz PNL HP PA/9000-J200 PA7200/100 MHz DL (loan) HP PA/9000-K460 PA8000/160 MHz DL (loan) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ DEC S5000/120 R3000A/R3010A 20 Mhz DL (loan) DEC S5000/200 R3000A/R3010A 25 MHz DL (loan) DEC AXP/3000-300 AXP A21064/150 MHz PNL DEC AXP/3000-500 AXP A21064/150 MHz DL (loan) DEC AXP/3000-600 AXP A21064/175 MHz PNL DEC AXP/3000-700 AXP A21064A/225 MHz DL (loan) DEC Alpha 250/4/266 AXP A21064A/266 MHz DL (loan) DEC Alpha 600/5/266 AXP A21164/266 MHz DL (loan) DEC Alpha 2100/5/250 AXP A21164/250 MHz DL (loan) DEC Alpha 8400/5/300 AXP A21164/300 MHz RAL DEC Alpha 600/5/333 AXP A21164/333 MHz DL (loan) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SGI 4D/220 GTX DL SGI 4D/320 R3000A/R3010A 33 MHz DL (loan) SGI 4D/420 DL (loan) SGI IRIS Crimson R4000/R4010 100 Mhz DL (loan) SGI R3000 Indigo R3000A/R3010A 33 MHz DL (loan) SGI R4000 Indigo R4000/R4010 100 MHz DL (loan) SGI Challenge L/100 R4400/R4010 100 MHz Utrecht SGI R4400 Indigo^2 R4400/R4010 150 MHz DL (loan) SGI Challenge L/150 R4400/R4010 150 MHz Southampton SGI R8000 Indigo^2 R8000/R8010 75 MHz DL (loan) SGI R8000 Power Onyx R8000/R8010 75 MHz DL (loan) SGI Indy R5000 R5000/R5000 180 Mhz DL (loan) SGI PowerOnyx 10000 R10000/R10010 195 MHz DL (loan) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Stardent 1520 DL Stardent 3020 DL (loan) Stardent VISTRA-800 DL (loan) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ IBM Power1 RS/6000-320 DL (loan) IBM Power1 RS/6000-530 DL (loan) IBM Power1 RS/6000-530H RS6000/33 MHz DL IBM Power1 RS/6000-540 Perugia IBM PowerPC-25T MPC601 66 MHz DL IBM PowerPC-43P MPC604 100 MHz DL IBM Power1 RS/6000-340 RS6000/33 MHz DL (loan) IBM Power1 RS/6000-350 RS6000/41.6 MHz DL (loan) IBM Power1 RS/6000-550 RS6000/41.6 MHz Perugia IBM Power1 RS/6000-360 RS6000/50 MHz DL (loan) IBM Power1 RS/6000-370 RS6000/62.5 MHz DL IBM Power2 RS/6000-590 RS6000/66 MHz IBM IBM Power2 RS/6000-3BT RS6000/67 MHz DL (loan) IBM Power2 RS/6000-3CT RS6000/72 MHz DL (loan) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ PCs ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Netpower PC Pentium Pro/200Mhz DL (loan) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SuperMinis ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Alliant FX2808 DL FPS-M64/60 DL Convex C-220 DL ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ SuperComputers ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Convex C-3860 ULCC IBM 3090-600-E VF RAL Cray YMP J90/10 EPCC Cray Y-MP/8128 SARA Cray YMP C98/4256 SARA ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Novel architecture Node ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Meiko Computing Surface T800-20 DL iPSC/2 SX-node DL iPSC/2 VX-node DL iPSC/860 RX-i860 node (40 MHz) DL KSR-2 KSR-2 node (80 MHz) PNL Cray T3D AXP node (150 MHz) Edinburgh IBM SP2 TN2 node (67 MHz) DL ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ========= ========= ========= ======== ****** ****** _______________________________________________________________________ Carles Colominas Dept. of Org. Chem. E-mail ccolo@mompou.iqs.url.es Institut Quimic de Sarria. TEL: (34-3)-203.89.00 Universitat Ramon Llull. FAX: (34-3)-205.62.66 Via Augusta 390. 08017-Barcelona. CATALONIA. _______________________________________________________________________ From guojx@xx1.icas.ac.cn Tue Oct 22 01:40 EDT 1996 Received: from bedrock.ccl.net for guojx@xx1.icas.ac.cn by www.ccl.net (8.8.0/950822.1) id BAA03753; Tue, 22 Oct 1996 01:40:52 -0400 (EDT) Received: from xx1.icas.ac.cn for guojx@xx1.icas.ac.cn by bedrock.ccl.net (8.8.0/950822.1) id BAA21838; Tue, 22 Oct 1996 01:40:22 -0400 (EDT) Received: (from guojx@localhost) by xx1.icas.ac.cn (8.6.12/8.6.9) id NAA00232; Tue, 22 Oct 1996 13:37:52 +0800 Date: Tue, 22 Oct 1996 13:37:52 +0800 (CST) From: Guo Jian-Xin To: ccl@ccl.net Subject: M:Force constant in MOPAC6? In-Reply-To: <19961021200530.AAB9206@LOCALNAME> Message-ID: Dear Netters: I found there are diagonal elements in the force constant matrix in the output of MOPAC 6.0, for example, it gives: force constant: O C H ........ O 3.0 C 2.5 2.0 H 3.7 1.8 3.3 . . . . . I wonder what the meaning is for the diagonal element? (In Gaussian9X, I can not see the similar result, the force constant were given for each mode) Another question is the force constant matrix is connected with the normal modes. whether there exist the similar "force constant matrix" connected with the internal coordinates? I know the normatl modes can be transformed from the internal coordinates, are there any methods to get the transformed matrix in MOPAC6 or any other direct method to calculate the force constant? Thanks in advances. I will summary the replies if interested. Guo From morokuma@euch4e.chem.emory.edu Tue Oct 22 12:16:35 1996 Received: from euch4e.chem.emory.edu for morokuma@euch4e.chem.emory.edu by www.ccl.net (8.8.0/950822.1) id MAA07324; Tue, 22 Oct 1996 12:08:24 -0400 (EDT) From: Received: by euch4e.chem.emory.edu (AIX 3.2/UCB 5.64/4.03) id AA15038; Tue, 22 Oct 1996 12:08:25 -0400 Message-Id: <9610221608.AA15038@euch4e.chem.emory.edu> Subject: icqc To: chemistry@www.ccl.net Date: Tue, 22 Oct 1996 12:08:25 -0400 (EDT) 9th International Congress of Quantum Chemistry Emory Conference Center Hotel Emory University Atlanta, Georgia June 9-14, 1997 SECOND CIRCULAR is now available at http://www.emerson.emory.edu/conferences/icqc97.html From scistra@frodo2.cs.sandia.gov Tue Oct 22 19:55 EDT 1996 Received: from cs.sandia.gov for scistra@frodo2.cs.sandia.gov by www.ccl.net (8.8.0/950822.1) id TAA10772; Tue, 22 Oct 1996 19:54:43 -0400 (EDT) Received: from frodo2.cs.sandia.gov by cs.sandia.gov with smtp (Smail3.1.28.1 #5) id m0vFqdm-000XPRC; Tue, 22 Oct 96 17:53 MDT Received: by frodo2.cs.sandia.gov (SMI-8.6/SMI-SVR4) id RAA00743; Tue, 22 Oct 1996 17:52:32 -0600 Date: Tue, 22 Oct 1996 17:52:32 -0600 From: scistra@cs.sandia.gov (Sorin C. Istrail) Message-Id: <199610222352.RAA00743@frodo2.cs.sandia.gov> To: chemistry-request@www.ccl.net Subject: RECOMB 97: CALL FOR POSTERS; LIST OF ACCEPTED PAPERS RECOMB 97 NEWS ************** October 22, 1996 1. REMINDER: CALL FOR POSTERS (deadline Oct 25, 96) 2. List of accepted papers to RECOMB 97 ------------------------------------------------ FIRST ANNUAL INTERNATIONAL CONFERENCE ON COMPUTATIONAL MOLECULAR BIOLOGY (RECOMB 97) January 20-23, 1997 Eldorado Hotel Santa Fe, New Mexico Sponsored by ACM SIGACT with support from SLOAN Foundation US Department of Energy recomb97@hto.usc.edu http://www.cs.sandia.gov/recomb97 ------------------------------------------- 1. This is a reminder that the deadline for receiving a poster abstract for RECOMB 97 is OCTOBER 25, 1996. This call is for a one page abstract. The actual space for the poseter presentation will be a regular poster space accomodating about 15 pages. Call for RECOMB 97 Posters ************************** Please send a one-page abstract of your Poster including title, authors, affiliation and abstract-text *preferably* via email to recomb97@hto.usc.edu or hard copy to: Professor Michael Waterman RECOMB 97 Program Chair University of Southern California Department of Mathematics, DRB 155 Los Angeles, CA 90089-1113 Deadline for poster abstract submission: October 25, 1996 Notification of acceptance/rejection: November 15, 1996 --------------------------------------------- 2. The List of Accepted Papers for RECOMB 97: ****************************************** Name: Zheng Zhang, William R. Pearson, Webb Miller Title: Aligning a DNA Sequence with a Protein Sequence Name: Gene Myers, Sanford Selznick, Zheng Zhang, Webb Miller Title: Progressive Multiple Alignment wtih Constraints Name: Ken Dill, Andrew T. Phillips, J. Ben Rosen Title: Protein Structure Prediction and Potential Energy Landscape Analysis using Continuous Global Minimization Name: Alberto Caprara Title: Sorting by Reversals is Difficult Name: J. Richard Bradley, Steven Skiena Title: Fabricating Arrays of Strings Name: Simon Heath Title: The application of Markov Monte Carlo methods to radiation hybrid mapping Name: Tatsuya Akutsu, Satoru Miyano Title: On the Approximation of Protein Threading Name: Eric L. Anson, Gene Myers Title: ReAligner: A Program for Refining DNA Sequence Multi-Alignments Name: George A. Komatsoulis, Michael Waterman Title: Chimeric alignment by dynamic programing: Algorithm and biological uses Name: Gary A. Churchill Title: Monte Carlo Sequence Alignment Name: Benno Schwikoski, Martin Vingron Title: The Deferred Path Heuristic for the Generalized Tree Alignment Problem Name: Tao Jiang, Richard M. Karp Title: Mapping Clones with a Given Ordering or Interleaving Name: Jamie Cohen, Martin Farach Title: Numerical Taxonomy on Data: Experimental Results Name: Dan Fasulo, Tao Jiang, Richard M. Karp, R. Settergren, E. C. Thayer Title: An Algorithmic Approach to Multiple Complete Digest Mapping Name: Sing-Hoi Sze, Pavel Pevzner Title: Towards 100% Accurate Gene Recognition: Suboptimal and Error-Tolerant Spliced Alignment Name: Ralf Zimmer, Tom Lengauer Title: Fast and Numerically Stable Parametric Alignment of Biosequences Name: Tao Jiang, Lusheng Wang, Dan Gusfield Title: A More Efficient Approximation Scheme for Tree Alignment Name: Serafim Batzogloa, Scott E. Decatur Title: Constant Approximation Algorithm on the Triangular Lattice and Generalized Hydrophobicity for Protein Folding in the Hydrophobic-Polar Model Name: S. Muthukrishnan, Laxmi Parida Title: A highly effective simple combinatorial approach for constructing physical maps by optical mapping Name: Richa Agarwala, V. Dancik, S. Hannenhalli, M. Farach, S. Muthukrishnan, S. Skiena Title: Local Rules for Protein Folding on a Triangular Lattice Name: K. Reinert, Hans-Peter Lenhof, P. Mutzel, K. Mehlhorn, J. D. Kececioglu Title: A Branch-and-Cut Algorithm for Multiple Sequence Alignment Name: Hans-Peter Lenhof Title: New Contact Measures for the Protein Docking Problem Name: Haim Kaplan, Ron Shamir, Robert Tarjan Title: Faster and Simpler Algorithm for Sorting Signed Permutations by Reversals Name: Ying Xu, Edward Uberbacher Title: Reference-based Gene Model Prediction on DNA Contigs Name: B. DasGupta, T. Jiang, S. Kannan, M. Li, Z. Sweekyk Title: On the Complexity and Approximation of Syntenic Distance Name: Mutida Jain, Gene Myers Title: Algorithm for Computing and Integrating Physical Maps Using Unique Probes Name: Gary Benson Title: Sequence Alignment with Tandem Duplication Name: Hiroshi Mamitsuka Title: Supervised Learning of Hidden Markov Models for Sequence Discrimination Name: William Hart Title: On the Computational Complexity of Sequence Design Problems Name: William Hart, Sorin Istrail Title: Lattice and Off-Lattice Side Chain Models of Protein Folding: Linear Time Structure Prediction Better than 86\% of Optimal Name: David Greenberg, Cynthia Phillips, David Wilson Title: Beyond Islands: Ambiguity in Random Clone-Probe Matrices Name: David Sankoff, V. Ferretti, Joe Nadeau Title: Conserved segment identification Name: John Kececioglu, T. Christof, M. J\"unger, P. Mutzel, G. Reinelt Title: A branch-and-cut approach to physical mapping with end-probes Name: Donna Slonim, L. Kruglyak, L. Stein, Eric Lander Title: Building Human Genome Maps with Radiation Hybrids Name: Bonnie Berger, Mona Singh Title: An Iterative Method for Improved Protein Structural Motif Recognition Name: Fengzhu Sun, Gary Benson, Mike Waterman Title: Pooling Strategies for Establishing Physical Genome Maps Using FISH Name: M. Ogihara, A. Ray Title: Simulating Boolean circuits on a DNA computer Name: M. G. Reese, F. H. Eeckman, D. Kulp, D. Haussler Title: Improved Splice Site Detection in Genie Name: Amir Ben-Dor, Benny Chor Title: On Constructing Hybrid Maps Name: Shili Lin, Terence P. Speed Title: An Algorithm for Haplotype Analysis Name: Tetsuo Shibuya, Hiroshi Imai Title: New Flexible Approaches for Multiple Sequence Alignment Name: Erich Bornberg-Bauer Title: Chain Growth Algorithms for HP-Type Lattice Proteins Name: W Cai, Anne Condon, RM Corn, E Glasser, Z. Fei, T. Frutos, Z. Guo, MG Lagally, Q Lui, LM Smith, A Theil Title: The Power of Surfaced-based DNA Computation ----------------------------------------- See you in Santa Fe, Mike Waterman, Pavel Pevzner and Sorin Istrail From bru@fcu.um.es Tue Oct 22 11:28:00 1996 Received: from unimur.um.es for bru@fcu.um.es by www.ccl.net (8.8.0/950822.1) id KAA06190; Tue, 22 Oct 1996 10:41:53 -0400 (EDT) Received: from fcu.um.es (gaia.fcu.um.es) by unimur.um.es (4.1/SMI-4.1) id AA05656; Tue, 22 Oct 96 16:44:55 +0200 Received: from roquebru.bio.um.es by fcu.um.es (5.x/SMI-SVR4) id AA09994; Tue, 22 Oct 1996 16:44:26 +0100 Message-Id: <9610221544.AA09994@fcu.um.es> X-Sender: bru@gaia.fcu.um.es Date: Tue, 22 Oct 1996 16:43:12 +0100 To: chemistry@www.ccl.net From: bru@fcu.um.es (Roque Bru Martinez) Subject: CCL:formulations freeware or software Dear netters: I am looking for freeware or software to desing formulations to attain emulsions with specific desired properties, in particular droplet size, viscosity, stability, and so on. May someone give me some clue? Thanx ---------------------------------------------------------------------------- Dr. Roque Bru-Martinez Phone: (+34 68) 30.71.00 ext 2945 Dpto. Bioquimica y Biol Mol. (A) Fax.....: (+34 68) 36.41.47 and 36.39.63 Fac. Veterinaria e-mail: bru@fcu.um.es Unidad Docente de Biologia UNIVERSIDAD DE MURCIA Sent using Eudora 1.4 Apto. 4021 E-30071 Murcia Spain ---------------------------------------------------------------------------- From toukie@zui.unizh.ch Tue Oct 22 09:16:37 1996 Received: from zzmkgtw.zzmk.unizh.ch for toukie@zui.unizh.ch by www.ccl.net (8.8.0/950822.1) id JAA05614; Tue, 22 Oct 1996 09:04:55 -0400 (EDT) Received: by zzmkgtw.zzmk.unizh.ch; (5.65v3.2/1.3/10May95) id AA13072; Tue, 22 Oct 1996 14:09:16 +0100 Message-Id: <1.5.4.32.19961022130546.0066ecd0@zui.unizh.ch> X-Sender: toukie@zui.unizh.ch (Unverified) Date: Tue, 22 Oct 1996 14:05:46 +0100 To: chemistry@www.ccl.net From: "Hr. Dr. S. Shapiro" Subject: Seeking CCDB data Dear Colleagues; I wish to search the Cambridge Crystallographic Database for struc- tures that might have been deposited there which meet all of the following criteria: (i) they are phenolic; and (ii) they have an intramolecular hydrogen bonds between the phenolic -OH moiety and some other group (e.g., an oxygen atom or a C=O moiety ortho to the phenolic -OH moiety); and (iii) their structures have been determined by neutron diffraction (I need experimental values for the positions of the hydrogen atoms as well as for the heavy atoms). I applied to the Pittsburgh Supercomputer Centre to access their CCDB mirror, but I was turned down because I am not affilated with an Ameri- can institution. Therefore, if anyone out there in CCL-Land would be will- ing to undertake a search for me in some mirror of the CCDB for compounds meeting the above criteria, I would greatly appreciate hearing from you. Yours most respectfully, (Dr.) S. Shapiro Inst. f. orale Mikrobiol. u. allg. Immunol. Zent. f. Zahn-, Mund- u. Kieferheilkd. der Univ. ZH Plattenstr. 11 Postfach CH-8028 Zuerich 7 Switzerland Internet: toukie@zui.unizh.ch FAX-nr: ( ... + 1) 261'56'83 From jkl@ccl.net Tue Oct 22 22:18 EDT 1996 From: Jan Labanowski Date: Tue, 22 Oct 1996 22:18:54 -0400 Message-Id: <199610230218.WAA08261@krakow.ccl.net> To: chemistry@www.ccl.net Subject: (Repost) IMPORTANT -- Future of CCL Dear Members of CCL, As promissed, I am back from Aberdeen, and I am posting this long message again, in case you missed it the first time. Big Thank You for all who responded. I learned a lot from your answers, and you gave me a lot of valuable, first hand information, as well as, great suggestions. I will answer your messages soon, but also this time, I ask you for understanding (my maibox is quite full at the moment {:-)}). I will also try to summarize your responses briefly. I already have some new thoughts thanks to your comments. But please, give me more... Thanks again. -------------------- original message reposted -------------- Please read this, since it is important to the CCL. This is, by necessity, a lenghty note, but please read on... As you know, I applied twice for the support of CCL to National the Science Foundation. First time, I did not get funding, but I learned from reviewers comments. Next time I got it... The CCL was granted NSF support, under the condition that CCL becomes self funded after 3 year period. And I need to show progress soon. The Web site has to be more organized, so it is easier to get to what you want. (...) The list grows, the number of topics grow, and I have less and less time, which I CAN JUSTIFY to spend on administering, to say nothing about improving the list. (...) While I recognize the potential, the list eats OSC resources (the Web, gopher, and ftp archives send gigabytes of stuff to the world every week), it eats my personal operational budget, and the Center cannot really justify these costs indefinitely. So please do not get me wrong... The situation is forced upon CCL. While it is a challenge for me (AND YOU), it is also an opportunity. The CCL may evolve into a much better resource. The NSF grant provides for some hardware, miscelaneous, and a single position for 3 years to support and develop the list into an enterprise which can support itself from income. If you are interested in working WITH me on this, please read the job opening announcement in the positions.offered file in CCL archives (http://www.ccl.net/chemistry.html --> CCL archives --> jobs) or go there directly via anon. ftp: ftp://www.ccl.net/pub/chemistry/jobs/positions.offered and check under: 96.09.10. I already have a few candidates, but I did not make decision yet, so if you are interested, please apply, but do it soon. (...) I will try to tell you as much as I can about my vision for the future of CCL, though obviously I cannot tell you everything. This creates a problem of confidence, and I am sorry about it. However, I hope that I proved to you for all these years that I am devoted to CCL, and that all this work was "labor of love". I hope that you can accept that it is not just a a business proposition for me, but more like having a child live long and prosper. So, how to become self funding? it boils down to essentially 2 models after you consider all cons and pros... Believe me, I did a lot of thinking, asking, and discussing... 1) non-profit, membership based, educational organization, [501(c)(3)]. (...) 2) nonallied, independent, for-profit enterprise, which provides FREE discussion forum as a price for its visibility and image. (...) The recipe for "success" which I was given quite often (but not always!!!) was: "Charge the membership fees". But I do have reservations. (...) Dues are a doubly edged sword. On one hand you get only people who want it and pay for it - a few good people. On the other hand, by charging dues, CCL would lose people for whom it would be too difficult (i.e., people who hate to pay for the free Internet; subscribers from abroad, especially from countries without free currency exchange; and students, for whom a 100 bucks is a 100 bucks, and 200 bucks is a million.). Moreover, membership fees may shrink the advertising audience. And besides, can one advertise to paid customers? On the other hand, with fees or no fees, I consider advertizing only through the CCL Web site and occassionally put some plug about visiting the Web site and praise our supporters. On the other hand, I realize that I cannot overdo this stuff, since some of you are very sensitive to this issue. (...) The other option is to go for-profit. This is a brave proposition, and by no means easy. It requires vision, knowledge, and you need to put your own money into it. But it has one advantage, that you can: "engage in any lawful act or activity for which a corporation may be formed in Ohio, pursuant to O.R.C. 1701.04(A)(3)." I do not have yet a formal business plan, and we have at least a year to decide how to go around it. The FREE list will be here until NSF grant is terminated/concluded, unless something unpredictable happens, (...) Whichever way it turns out, do not forget that all of you who subscribe to CCL are in effect in the CCL Board of Trustees. You go, and I go under. (...) Therefore I want to preserve the list as it exists NOW for FREE. It will have the current wide scope, and an interactive feel. I will most likely connect CCL to Usenet, as a moderated group, though moderating will be done by software to the extent software can do it with a very limited human intervention. (...) I assume that the list and its discussions are the core of all this, and it should not be messed up. I want to have free archives and a free Web side. But of course not all can be free, since CCL will have to earn money to pay: 1) a salary for at least one full time person, 2) a high bandwidth Internet connection 3) pay for hardware, software, and maintenance/licensing. So I have to create income sources which will depend on the FREE list, some of which will be the added value to the PLAIN list, and some which will be made attractive by the wide exposure given by the list. (...) I will try to list some ideas (not all, though) how the list can support itself from related service: 1) the CCL could be involved in non-intrusing advertising (via Web), 2) filtering messages on specific threads/topics for people who want to keep their e-mail volume low, 3) searching for particular information (in CCL archives or anywhere on the Internet), 4) consultant's brokerage, 5) selling derivatives of CCL discussions (i.e, highly organized archives, with CD-ROM editions), 6) organize virtual conferences (possibly for a fee) which will result in publishable CD-ROMS. 7) start a rapid Comp.Chem. Comm. News flash, 8) provide a home to some computational chemistry electronic journal(s) (or develop one), 9) have a job market/employment service (i.e., positions.offered may be a paid service in the future) 10) sell things over Internet (virtual store) using secure credit-card/digital-cash transactions and get commission for goods sold, 11) Web presence, Web site design, etc., 12) provide anonymous participation for users who do not want to be associated with their employers when posting, 13) provide site for Requests For Proposals for companies which want to find contractors, or organize consortia. 14) create searchable databases of comp.chem. results, data, and sources, 15) access to other services (e.g., selling computer time at computer centers) as commission, 16) selling software for small developers who cannot afford the marketing infrastructure, 17) educational services (e.g., on chemistry related HTML design), and providing infastructire for Web based instruction in chemistry related disciplines, which was prepared by 3rd parties, 18) selling our own software developed for running this CCL services, 19) providing Web space information and membership services for societes and associations in related areas 20) providing US representation for chemistry related services of foreign small businesses, and vice versa. 21) Providing some ISP functions (e.g., private e-mail accounts not associated with person's employer, providing e-mail interface to Usenet groups). This is by far not a complete listing of possibilities, and obviously, there maybe not enough market needs for some possibilities listed above. Do I want to do it all by myself? I wish there was 240 hours a day. But I hope that some of companies/startup may want to use CCL infrastructure to provide their services, and I can take some markup. So if you have some good ideas, I will be glad if you can e-mail me. Now, I will have to protect CCL assets. Thanks to the new US copyright law and some court decisions, I have some rights to the assets of CCL archive, since it represents the collection. I also have rights to the derivatives of the archive. I will put there soon some copyright notice to deter, (...) Now, each of you has a choice: do nothing, or support me and CCL which I am trying TO SAVE (Yes, SAVE!!!) I also have choices. When many of you choose to help me, we will have CCL for the long time to come, and it will be better. And remember, right now, there is no for-profit corporation associated with the list which is run by myself. The list is supported by NSF, and runs off the Ohio Supercomputer Center. But it WILL HAVE TO CHANGE IN THE FUTURE. Why? Because, I am being so told... Now, how can you help me? In many ways... For example: 1) Give me good stuff, good content, good discussions, and good, thought provoking questions for discussions. When you publish a paper, you give your best shot, since it is your divine call, and your name is on it. The CCL is a chat forum, but people listen, and they have feelings. 2) Contribute free stuff to CCL archives. You have lots of nifty software which you wrote, a lot of educational materials, good data and results, handouts, mpegs, jpegs, and gifs, and you reviewed a lot of software, and did write-ups for internal use, etc. Copyright it to yourself or whoever, and give me a license to use it for public distribution via CCL archives. You will get recognition, and I will get good stuff which will make CCL a valuable resource. But put some doc with it please, it will add a lot of value to your contribution. 3) Give me ideas. Do not be offended or disappointed, however, if I do not apply them, since I may not see their importance, or I have some plan, which would be in conflict, or, simply, I do not have manpower. I will always try to tell you why, if I can. 4) Give me money... Contribute to the "OSC Development Fund (CCL)". I will give you details soon, but in short, if you, or your organization gives me something, you will be thanked on the Web, proportionally to the amount. I will soon decide levels for Ambasadors, Patrons, Friends, Supporters, etc. and the amount of exposure associated. (...) 5) I am not a business yet... But all of you have to understand is that if I take a business path, and you do not like it, all you have to do is unsubscribe. And I am out of business. Moreover, with my other activities and involvment in the Center, I have a chance to bring some additional assets to the list archives and add these stuff to the CCL COLLECTION (sic!). However, give me your ideas on possible business opportunities for CCL. I will keep your propositions and comments in full confidence. 6) I will bug you with the info on CCL directions, changes in format, will ask you to participate in testing some ideas or software, and I will solicit your advice, your inputs, and your opinions. PLEASE, DO NOT DISCUSS CCL ON CCL!!! It may create flame wars, and will also increase the noise level since CCL is for Comp Chem. It is more than enough that I have to do it. Please send me your responses directly, and even if I do not write back immediately, I will read them, and be grateful. So, please comment! Send me your nice comments, or harsh criticism since I need it. I understand that some of you may feel disappointed. In a sense, some innocence of the list has been lost. But, as you can see, I tried to convince you that these are the means, and not ends for me. And if you think that this is another "get rich fast on the Internet", look closer at the record. The list is now at the end of its 6th year, and I am yet to see my first penny made on the list. I try to keep the good thing. But I cannot do it without your quidance, support, and trust. On the other hand, I have to take charge, since we cannot vote on everything, (...) We have to work together, but I understand that not all of you would want to support this venture. But the simple truth is that CCL has to pay its bills, or dies in pain. If there are other options, tell me about it, or you may try them yourself. Yours, Jan Labanowski jkl@ccl.net From jkl@ccl.net Tue Oct 22 22:18 EDT 1996 From: Jan Labanowski To: chemistry@www.ccl.net Subject: Pointer to full text of CCL future vision Dear Members of CCL, One more note... The full text version of the ideas on the future of CCL can be retrieved as: The full text of this message can be found at: http://www.ccl.net/ccl/future.html or ftp://www.ccl.net/pub/chemistry/future/vision.txt or retrieved by e-mail by sending a message select chemistry cd future get vision.txt quit to MAILSERV@www.ccl.net Jan Labanowski jkl@ccl.net From erdem@pharmacy.ankara.edu.tr Wed Oct 23 02:16:35 1996 Received: from io.pharmacy.ankara.edu.tr for erdem@pharmacy.ankara.edu.tr by www.ccl.net (8.8.0/950822.1) id BAA13701; Wed, 23 Oct 1996 01:39:03 -0400 (EDT) Received: from IO.194.27.25.3 (erdem.pharmacy.ankara.edu.tr [194.27.25.26]) by io.pharmacy.ankara.edu.tr (8.6.12/8.6.9) with SMTP id IAA28109 for ; Wed, 23 Oct 1996 08:01:15 +0200 Message-Id: <1.5.4.32.19961023064007.0068b128@pharmacy.ankara.edu.tr> X-Sender: erdem@pharmacy.ankara.edu.tr X-Mailer: Windows Eudora Light Version 1.5.4 (32) Mime-Version: 1.0 Content-Type: text/plain; charset="us-ascii" Date: Wed, 23 Oct 1996 08:40:07 +0200 To: chemistry@www.ccl.net From: Erdem Buyukbingol Subject: Symposium in Anatolia 5th International Symposium on Pharmaceutical Sciences Ankara University, Faculty of Pharmacy, Ankara Turkey, June 24 - 27, 1997 FIRST ANNOUNCEMENT Dear Colleague October 23, 1996 The "Fifth International Symposium on Pharmaceutical Sciences" organized by the Faculty of Pharmacy, Ankara University, will be held in Ankara during June 24 - 27, 1997. Apart from invited lectures, participants from Universities, Research Centers and Industry will have the opportunity of contributing oral, poster and electronic poster presentations on the topics of basic and applied pharmaceutical sciences. You can easily access to uor Faculty's web page and fill the application form in order to include yourself as a participant. The URL address is, http://www.pharmacy.ankara.edu.tr The e-mail is, ankpharm@pharmacy.ankara.edu.tr This time we are also arranging an Electronic Poster session for your convenience to take part your favorite studies in the symposium if you are unable to visit our country. All abstracts for the electronic posters will undergo regular refereeing before being mounted for the electronic Conference. Abstract titles, authors and URL addresses of the electronic posters will be included in the Symposium Book of Abstracts. The Organizing Committee would be grateful if you could participate the Symposium and inform your colleagues about it. We hope that you will join us and take the oppotunity to participate in exciting scientific program, as well as to travel throughout this unique land so-called ancient ANATOLIA. We look forward to welcoming you to a stimulating meeting and wish you an enjoyable stay in Turkey. Sincerely yours, Organizing Committee From phoward@mailbox.syr.edu Wed Oct 23 11:16:42 1996 Received: from mailer.syr.edu for phoward@mailbox.syr.edu by www.ccl.net (8.8.0/950822.1) id KAA16375; Wed, 23 Oct 1996 10:56:59 -0400 (EDT) Received: from forbin.syr.edu by mailer.syr.edu (LSMTP for Windows NT v1.0a) with SMTP id B37B1860 ; Wed, 23 Oct 1996 10:55:27 -0400 Received: from localhost (phoward@localhost) by forbin.syr.edu (8.7.6/8.7.3) with SMTP id KAA21907; Wed, 23 Oct 1996 10:56:14 -0400 (EDT) X-Authentication-Warning: forbin.syr.edu: phoward owned process doing -bs Date: Wed, 23 Oct 1996 10:56:13 -0400 (EDT) From: "Philip H. Howard" X-Sender: phoward@forbin.syr.edu To: jianghua wang cc: chemistry@www.ccl.net Subject: Re: CCL:PKa In-Reply-To: <199610220041.UAA00681@www.ccl.net> Message-ID: MIME-Version: 1.0 Content-Type: TEXT/PLAIN; charset=US-ASCII On Mon, 21 Oct 1996, jianghua wang wrote: > Heli, everyone: > > I am lookIs there any porogram which acan calculated PkaKa for > small pmoleculle? Any suggestion should beThe dsuggestion will be appreciated. > > Joshua Wang > > CCNY > Phys. Dept. > New York, NY 10031 > > You might want to try pKalc. We have found it gives reasonable results. http://www.acs.org/pubgen/software/pkalc.htm Also, EPA and the U. of Georgia has developed a program called SPARC that will estimate pKa. See Hilal, S.H., L.A. Carreira and S.W. Karickhoff. 1994. Estimation of chemical reactivity parameters and physical properties of organic molecules using SPARC. In Quantitative Treatments of Solute/Solvent Interactions: Theoretical and Computational Chemistry Vol 1 291-353. Philip H. Howard Phone: 315-426-3350 Environmental Sciences Center Fax: 315-426-3429 Syracuse Research Corporation Email: howardp@syrres.com Merrill Lane http://esc.syrres.com Syracuse, NY 13210 From jhwang@bphp.sci.ccny.cuny.edu Wed Oct 23 14:16:44 1996 Received: from bphp.sci.ccny.cuny.edu for jhwang@bphp.sci.ccny.cuny.edu by www.ccl.net (8.8.0/950822.1) id NAA17250; Wed, 23 Oct 1996 13:24:28 -0400 (EDT) Message-Id: <199610231724.NAA17250@www.ccl.net> Received: by bphp.sci.ccny.cuny.edu (1.38.193.4/16.2) id AA04730; Wed, 23 Oct 1996 13:23:02 -0400 Date: Wed, 23 Oct 1996 13:23:02 -0400 From: jianghua wang To: chemistry@www.ccl.net Subject: PKa Hello everyone: A few days ago, I posted aid looking for program calculating PKa. I received many messages from our dear CCL fellows. Thank everyone who gave me help. Joshua Wang Physics Dept. CCNY New York, NY 10031 From jhwang@bphp.sci.ccny.cuny.edu Wed Oct 23 14:31:35 1996 Received: from bphp.sci.ccny.cuny.edu for jhwang@bphp.sci.ccny.cuny.edu by www.ccl.net (8.8.0/950822.1) id NAA17250; Wed, 23 Oct 1996 13:24:28 -0400 (EDT) Message-Id: <199610231724.NAA17250@www.ccl.net> Received: by bphp.sci.ccny.cuny.edu (1.38.193.4/16.2) id AA04730; Wed, 23 Oct 1996 13:23:02 -0400 Date: Wed, 23 Oct 1996 13:23:02 -0400 From: jianghua wang To: chemistry@www.ccl.net Subject: PKa Hello everyone: A few days ago, I posted aid looking for program calculating PKa. I received many messages from our dear CCL fellows. Thank everyone who gave me help. Joshua Wang Physics Dept. CCNY New York, NY 10031 From chipot@camelot.arc.nasa.gov Wed Oct 23 15:31:47 1996 Received: from camelot.arc.nasa.gov for chipot@camelot.arc.nasa.gov by www.ccl.net (8.8.0/950822.1) id PAA17902; Wed, 23 Oct 1996 15:02:13 -0400 (EDT) Message-Id: <199610231902.PAA17902@www.ccl.net> Received: by camelot.arc.nasa.gov (1.39.111.2/16.2) id AA143767105; Wed, 23 Oct 1996 11:58:25 -0700 From: Chris Chipot Subject: Error analysis To: CHEMISTRY@www.ccl.net Date: Wed, 23 Oct 1996 11:58:24 PDT X-Mailer: Elm [revision: 111.1] Hi, there: Given a two-dimensional probability distribution - P(x,y) - and given a free energy difference between two states `i' and `j' - corresponding to regions of the (x,y) space - defined by: integral over region j P(x,y) dx dy delta A(i->j) = -kT log ------------------------------------ integral over region i P(x,y) dx dy would anyone have a clue on how to evaluate the error on delta A(i->j), assuming that the error on the probability at each point of the (x,y) map is known, and that the two regions `i' and `j' are not overlapping? It is not clear, however, whether or not the data points are uncorrela- ted - in fact, I suspect they are... Thanks in advance for any helpful suggestion. Chris _______________________________________________________________________ Chris Chipot Planetary Biology Branch Phone: (415) 604-5496 Mail Stop 239-4 Fax: (415) 604-1088 NASA - Ames Research Center Moffett Field, CA 94035-1000 E-mail: chipot@max.arc.nasa.gov _______________________________________________________________________ From jhwang@bphp.sci.ccny.cuny.edu Wed Oct 23 22:31:41 1996 Received: from bphp.sci.ccny.cuny.edu for jhwang@bphp.sci.ccny.cuny.edu by www.ccl.net (8.8.0/950822.1) id WAA20423; Wed, 23 Oct 1996 22:30:59 -0400 (EDT) Message-Id: <199610240230.WAA20423@www.ccl.net> Received: by bphp.sci.ccny.cuny.edu (1.38.193.4/16.2) id AA06317; Wed, 23 Oct 1996 22:29:37 -0400 Date: Wed, 23 Oct 1996 22:29:37 -0400 From: jianghua wang To: chemistry@www.ccl.net Subject: PKa Hi, everyone: Since some fellows have same question as I have. Here I post the messages I received. It seems that there are three programs are mentioned: pkcal, spartan, sparc Joshua Wang P.S. ----------------------------------------------------- >From jparikh@ari.net Wed Oct 23 14:40 EDT 1996 The program PKalc developed by CompuDrug in Hungray is your best bet. We are THE distributor for that particular program. ACS is not really the source for that. Marketing Manager AHSystems Group 5401 Lakeford Lane, Suite L-1 Bowie, MD 20720 Phone 301.352.0896 Fax 301.352.0199 Web Site www2.ari.net/ahsystems ------------------------------------- >From: ksingh@UMDNJ.EDU DelPhi (standardalone and within Insight) can be used to calculate PKa. Kamal Singh ------------------------------ >From: vangreve@univ-orleans.fr Take a look at http://www.ccl.net/ccl/pallas.html Eric ---------------------- >From: ccolo@mompou.1qs.url.es Perhaps a program called SPARC could be of interest.... SPARC was developed by L.A. Carreira and S.W. Karichoff. Ref. Quant. Struct. Act. Rel. (QSAR) 14, 348 (1995). CC ------------------------------- >From: johnL@proteus.co.uk There is a PKa calculate package which is part of the PALLAS software marketed by compuDrug..... You may contact CompuDrug. mktg@cdr-cgx.hu www.datanet.hu/compudrug John W. Liebeschuetz ------------------------------ >From: elewars@alchemy.chem.utoronto.ca One way to estimate Pk is given in "computational Organic Chemistry" by Hehere, Burke, Shusterman and Pietro...... Errol Lewars ------------------------------ >From: johnduch@mallchem.global.ibmmail.com The CAChe program will allow you to predit PKas if you know the Pka of similar molecules. Using project leader, you can do least squares analysis of the molecules that have known Pka.......................... John Duchek ----------------------- >From: JeffAyres@postoffice.world.att.net ..... The Spartan program( available from wavefunction, Ivring CA) will calculate frequencies and display the thermodynamic quantities necessary to calculate the change in free energy... Jeffrey J Ayres -----------------------