NAS Parallel Benchmark Version 1.0 Results 11-96 · 2016. 2. 26. · processors operating in...

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NAS Parallel Benchmark (Version 1.0) Results 11-96Subhash Saini1 and David H. Bailey2

Report NAS-96-18, November 1996

Numerical Aerospace Simulation ProgramNASA Ames Research Center

Mail Stop T 27A-1Moffett Field, CA 94035-1000, USA

email: [email protected]

Abstract

The NAS Parallel Benchmarks have been developed at NASA Ames Research Center to studythe performance of parallel supercomputers. The eight benchmark problems are specified in a‘‘pencil and paper’’ f ashion. In other words, the complete details of the problem to be solved aregiven in a technical document, and except for a few restrictions, benchmarkers are free to selectthe language constructs and implementation techniques best suited for a particular system. Theseresults represent the best results that have been reported to us by the vendors for the specificsystems listed. In this report3, we present new NPB (Version 1.0) performance results for thefollowing systems:

- DEC Alpha Server 8400 5/440,- Fujitsu VPP Series (VX, VPP300, and VPP700),- HP/Convex Exemplar SPP2000,- IBM RS/6000 SP P2SC node (120 MHz)- NEC SX-4/32,- SGI/CRAY T3E,- SGI Origin200- SGI Origin2000

We also report High Performance Fortran (HPF) based NPB results for IBM SP2 Wide Nodes,HP/Convex Exemplar SPP2000, and SGI/CRAY T3D. These results have been submitted byApplied Parallel Research (APR) and Portland Group Inc. (PGI). We also present sustainedperformance per dollar for Class B LU, SP and BT benchmarks.

1. Subhash Saini is an employe of MRJ Inc. This work is supported by NASA Ames Research Center throughcontract NAS 2-14303.

2. David H. Bailey is an employee of NASA Ames Research Center.3. URL: http://www.nas.nasa.gov/NAS/NPB/

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1: Intr oduction

The Numerical Aerodynamic Simulation (NAS) Program, located at NASA Ames ResearchCenter, is a pathfinder in high-performance computing for NASA and is dedicated to advancingthe science of computational aerodynamics. One key goal of the NAS organization is todemonstrate by the year 2000 an operational computing system capable of simulating an entireaerospace vehicle system in one to several hours. It is currently projected that the solution of thisGrand Challenge problem will require a system that can perform scientific computations at asustained rate of approximately 1000 times faster than 1990 generation supercomputers. Such acomputer system will most likely employ hundreds or even thousands of powerful RISCprocessors operating in parallel.

In order to objectively measure the performance of various highly parallel computer systemsand to compare them with conventional supercomputers, NAS has developed the NAS ParallelBenchmarks (NPB 1.0) [1, 2]. Note that the NPB 1.0 are distinct from the NAS High SpeedProcessor (HSP) benchmarks and procurements. The HSP benchmarks are used for evaluatingproduction supercomputers for procurements in the NAS organization, whereas the NPB 1.0 areused for studying highly parallel processor (HPP) systems in general.

2: NAS Parallel Benchmarks

The NPB 1.0 consist of a set of eight benchmark problems, each of which focuses on someimportant aspect of highly parallel supercomputing for aerophysics applications. Some extensionof Fortran or C is required for implementations, and reasonable limits are placed on the use ofassembly code and the like. Otherwise, programmers are free to utilize language constructs thatmaximize performance on the particular system being studied. The choice of data structures,processor allocation, and memory usage are generally left open to the discretion of theimplementer.

The eight problems consist of five kernels and three simulated computational fluid dynamics(CFD) applications. The five kernels comprise relatively compact problems, each emphasizing aparticular type of numerical computation. Compared with the simulated CFD applications, theycan be implemented fairly readily and provide insight as to the general levels of performance thatcan be expected on these specific types of numerical computations.

The simulated CFD applications, on the other hand, usually require more effort to implement,but they are more representative of the types of actual data movement and computation required instate-of-the-art CFD application codes. For example, in an isolated kernel, a certain data structuremay be very efficient on a certain system; and yet, this data structure may be inappropriate ifincorporated into a larger application. By comparison, the simulated CFD applications requiredata structures and implementation techniques that are more typical of real CFD applications.

(Space does not permit a complete description of these benchmark problems. A more detaileddescription of these benchmarks, together with the rules and restrictions associated with them, isgiven in reference 2.)

There are now three standard sizes for the NAS Parallel Benchmarks: Class A, Class B andClass C size problems. The nominal benchmark sizes for Class A, Class B and Class C problems

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are shown in Table 1. These tables also give the standard floating-point operation (flop) counts forClass A and Class B. We recommend that those wishing to compute performance rates in millionsof floating point operations per second (Mflop/s) use these standard flop counts. Table 1 containsMflop/s rates calculated in this manner for the current fastest implementation on one processor ofCRAY Y-MP for Class A and on one processor of CRAY C90 for Class B. Note, however, that inthis report, performance rates arenot cited in Mflop/s; instead we present, the wall clock times(and, the equivalent performance ratios). We suggest that these, not Mflop/s, be examined whencomparing different systems and implementations.

With the exception of the IS benchmark, these standard flop counts were determined by usingthe hardware performance monitor on the CRAY Y-MP or CRAY C90, and we believe that theyare close to the minimal counts required for these problems. In the case of the IS benchmark,which does not involve floating-point operations, we selected a value approximately equal to thenumber of integer operations required, in order to permit the computation of performance ratesanalogous to Mflop/s rates. We reserve the right to change these standard flop counts in the future,if necessary.

The NAS organization reserves the right to verify any NPB results that are submitted to us. Wemay, for example, attempt to run the submitter’s code on another system of the same configurationas that used by the submitter. In those instances where we are unable to reproduce the vendor’ssupplied results (allowing a 5% tolerance), our policy is to alert the submitter of the discrepancyand allow submitter to resolve the discrepancy in the next release of this report. If the discrepancyis not resolved to our satisfaction, then our own observed results and not the submitter’s resultswill be reported.

3: NAS Parallel Benchmark Results

In the following section, each of the eight benchmarks will be briefly described, and then thebest performance results we have received to date for each computer system will be given inTables 2 through 10 and Tables 14-18. These tables include run times and performance ratios. Theperformance ratios compare individual timings with the current best time for that benchmarkachieved on one processor of CRAY Y-MP for Class A and on one processor of CRAY C90 forClass B. The run times in each case are elapsed time measured in accordance with thespecifications of NPB rules. This report includes a number of new results including previouslyunpublished - DEC Alpha Server 8400 5/440, Fujitsu VPP Series (VX, VPP300, VPP700),HP/Convex Exemplar SPP2000, IBM RS/6000 SP P2SC node (120 MHz), NEC SX-4/32,SGI/CRAY T3E, SGI Origin200 and SGI Origin2000

3.1: Kernels

The results for five kernels (EP, MG, CG, FT, and IS) are given below in the following section:

3.1.1: The Embarrassingly Parallel (EP) Benchmark

The first of the five kernel benchmarks is anembarrassingly parallel problem. In thisbenchmark, two-dimensional statistics are accumulated from a large number of Gaussian pseudo-random numbers, which are generated according to a particular scheme that is well-suited forparallel computation. This problem is typical of many Monte Carlo applications. Since it requiresalmost no communication, in some sense this benchmark provides an estimate of the upperachievable limits for floating-point performance on a particular system. Results for EP benchmark

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are given in Table 2.

3.1.2: Multigrid (MG) Benchmark

The second kernel benchmark is a simplified multigrid kernel, which solves a 3-D PoissonPDE. This problem is simplified in the sense that it has constant rather than variable coefficientsas in a more realistic application. This code is a good test of both short and long distance highlystructured communication. The Class B problem uses the same size grid as of Class A but agreater number of inner loop iterations. Results for this benchmark are shown in Table 3.

3.1.3: Conjugate Gradient (CG) Benchmark

In this benchmark, a conjugate gradient method is used to compute an approximation to thesmallest eigenvalue of a large, sparse, symmetric positive definite matrix. This kernel is typical ofunstructured grid computations in that it tests irregular long-distance communication and employssparse matrix-vector multiplication. Results are shown in Table 4.

3.1.4: 3-D FFT PDE (FT) Benchmark

In this benchmark a 3-D partial differential equation is solved using FFTs. This kernel performsthe essence of many spectral methods. It is a good test of long-distance communicationperformance. The rules of the NPB specify that assembly-coded, library routines may be used toperform matrix multiplication and one-dimensional, two-dimensional, or three-dimensional FFTs.Thus this benchmark is somewhat unique in that computational library routines may be legallyemployed. Results are shown in Table 5.

3.1.5: Integer Sort (IS) Benchmark

This benchmark tests a sorting operation that is important inparticle method codes. This typeof application is similar to particle-in-cell applications of physics, wherein particles are assignedto cells and may drift out. The sorting operation is used to reassign particles to the appropriatecells. This benchmark tests both integer computation speed and communication performance.This problem is unique in that floating point arithmetic is not involved. Significant datacommunication, however, is required. Results are shown in Table 6.

3.2: Simulated CFD Application Benchmarks

The three simulated CFD application benchmarks are intended to accurately represent theprincipal computational and data movement requirements of modern CFD applications.

3.2.1: LU Simulated CFD Application (LU) Benchmark

The first of these is the so-called the lower-upper diagonal (LU) benchmark. It does not performa LU factorization but instead employs a symmetric successive over-relaxation (SSOR) numericalscheme to solve a regular-sparse, block5x5 lower and upper triangular system. This problemrepresents the computations associated with a newer class of implicit CFD algorithms, typified atNASA Ames by the codeINS3D-LU. This problem exhibits a somewhat limited amount ofparallelism compared to the next two benchmarks. A complete solution of the LU benchmarkrequires 250 iterations. Results are given in Table 7.

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3.2.2: SP Simulated CFD Application (SP) Benchmark

The second simulated CFD application is called the scalar pentadiagonal (SP) benchmark. Inthis benchmark, multiple independent systems of nondiagonally dominant, scalar pentadiagonalequations are solved. A complete solution of the SP benchmark requires 400 iteration. Results aregiven in Table 8.

3.2.3: BT Simulated CFD Application (BT) Benchmark

The third simulated CFD application is called the block tridiagonal (BT) benchmark. In thisbenchmark, multiple independent systems of non-diagonally dominant, block tridiagonalequations with a5x5 block size are solved.

SP and BT are representative of computations associated with the implicit operators of CFDcodes such asARC3D at NASA Ames. SP and BT are similar in many respects, but there is afundamental difference with respect to the communication to computation ratio. Timings are citedas complete run times, in seconds, as with the other benchmarks. For the BT benchmark, 200iterations are required. Results of BT benchmark are given in Table 9.

3.3 NPB 1.0 Class C Results

In Table 10 are given the Class C NPB 1.0 results for EP, MG, CG, FT, LU, SP and BTbenchmarks on CRAY T3E.

4: Sustained Performance Per Dollar

One aspect of the relative performance of these systems has not been addressed so far, namelythe differences in price between these systems. One should not be too surprised that the CRAYC90 system, for example, exhibits superior performance rates on these benchmarks, since itscurrent list price is much greater than that of the other systems tested.

One way to compensate for these price differences is to compute sustained performance permillion dollars,i.e. the performance ratio figures shown in Tables 2 through 9 divided by the listprice in millions. Some figures of this type are shown in Tables 11-13 for Class B LU, SP, and BTbenchmarks, respectively. The table includes the list price of the minimal system (in terms ofmemory per node and number of processors) required to run the full Class B size NPB asimplemented by the vendor. These prices were provided by the vendors and include anyassociated software costs, i.e. operating system, compilers, scientific libraries as required,etc. butdo not include maintenance. Note that some vendors’ standard configurations may includesubstantially more hardware than required for the benchmark.

5 High Performance Fortran Based NPB

High Performance Fortran (HPF), the high-level language for parallel Fortran programming, isbased on Fortran 90. HPF was defined by an informal standards committee known as the HighPerformance Fortran Forum (HPFF) in 1993, and modeled on TMC’s CM Fortran language.Several HPF features have since been incorporated into the draft ANSI/ISO Fortran 95, the nextformal revision of the Fortran standard.

HPF allows users to write a single parallel program that can execute on a serial machine, ashared-memory parallel machine, or a distributed-memory parallel machine. HPF eliminates the

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complex, error-prone task of explicitly specifying how, where, and when to pass messagesbetween processors on distributed-memory machines, or when to synchronize processors onshared-memory machines. HPF is designed in a way that allows the programmer to code anapplication at a high level, and then selectively optimize portions of the code by dropping intomessage-passing or calling tuned library routines as “extrinsics”.

Compilers supporting High Performance Fortran features first appeared in late 1994 and early1995 from Applied Parallel Research (APR) Digital Equipment Corporation, and The PortlandGroup (PGI). IBM introduced an HPF compiler for the IBM RS/6000 SP in April of 1996. Overthe past year, these implementations have shown steady improvement in terms of both featuresand performance. NAS is working toward a standard set of HPF NPBs which can be used as ameasure of both HPF compilers and hardware systems. In advance of that release we have chosento publish here results achieved using versions of the HPF NPBs developed outside of NAS andsubmitted by APR and PGI. These results can be compared to the MPI results in NPB 2.2 [4] andthe other NPB 1.0 results supplied here to provide perspective on performance currentlyobtainable using HPF versus MPI or versus hand-tuned implementations such as those suppliedby the hardware vendors.

For more details on HPF, see reference 3 and references therein. HPF NPB results appear inTables 14-18.

References

[1] D. H. Bailey, E. Barszcz, J. T. Barton, D. S. Browning, R. L. Carter, L. Dagum, R. A. Fatoohi, P. O. Frederickson, T. A. Lasinski, R. S. Schreiber, H. D. Simon, V. Venkatakrishnan, and S. K. Weeratunga, ‘‘The NAS Parallel Benchmarks,’’ International Journal of Supercomputer Applications, Vol 5, No.3 (Fall1991), pp. 63-73.

[2] D. H. Bailey, J. Barton, T. Lasinski, and H. D. Simon, eds., “The NAS Parallel Benchmarks,’’NASA Technical Memorandum 103863, NASA Ames Research Center, Moffett Field, CA 94035-1000, July 1993.

[3] S. Saini, “NAS Experiences of Porting CM Fortran Codes to HPF on IBM SP2 and SGIPower Challenge”, pp. 873-880, inThe Proceedings of IEEE 10th International ParallelProcessing Symposium (IPPS), Honolulu, Hawaii, April 15-19, 1996.

[4] David Bailey, Tim Harris, William Saphir, Rob van der Wijngaart, Alex Woo, and MauriceYarrow, “The NAS Parallel Benchmarks 2.0”, Report NAS-95-020, December, 1995.

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Table 1: NAS Parallel Benchmarks Problem Size.

Benchmark Name Abb.

Class A Class B Class C

NominalSize

Operation Count (x 109)

Mflop/sCRAY

Y-MP/1

Nominal Size

OperationCount(x109)

Mflop/sCRAYC90/1

NominalSize

EmbarrassinglyParallel

EP 228 26.68 211 230 100.9 689 232

Multigrid MG 2563 3.905 176 2563 18.81 557 5123

Conjugate Gradient CG 14x103 1.508 127 75x103 54.89 447 1.5 x 105

3-D FFT PDE FT 2562x128 5.631 196 512x2562 71.37 645 5123

Integer Sort IS 223x219 0.7812 68 225x221 3.150 244 227

LU Simulated CFDAppl.

LU 643 64.57 194 1023 319.6 711 1623

SP Simulated CFDAppl.

SP 643 102.0 216 1023 447.1 648 1623

BT Simulated CFDAppl.

BT 643 181.3 229 1023 721.5 705 1623

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Table 2: Results of the Embarrassingly Parallel (EP) benchmark.

Computer System

DateReceived

NumberProcessor

Class A Class B

Time in seconds

Ratio toCRAY

Y-MP/1

Time in seconds

Ratio toCRAYC90/1

BBN TC2000 Dec 91 64 284.0 0.44 NA NA

Convex ExemplarSPP1000

Mar 95 18

163264

376.848.124.311.86.1

0.332.625.19

10.6920.68

NA191.096.048.024.5

NA0.771.533.055.98

HP/Convex ExemplarSPP2000

Nov 96 148

16

160.941.220.710.5

0.783.066.10

12.02

NANANANA

NANANANA

CRAY C90 Feb 95 1248

16

36.6218.429.154.612.36

3.456.85

13.7927.3753.46

146.4173.6636.7818.379.35

1.01.993.987.97

15.66

CRAY J916 Feb 95 1248

16

169.4486.7043.0921.5410.78

0.741.462.935.86

11.70

675.71340.13170.1585.4943.16

0.220.430.861.713.39

CRAY T3D Feb 95 163264

128256512

1024

22.7411.375.682.871.440.720.55

5.5511.1022.2143.9687.62

175.24229.40

91.8345.9222.9511.475.742.872.19

1.593.196.38

12.7625.5151.0166.85

CRAY T3E Nov 96 248

163264

128256

56.228.114.17.03.51.80.90.4

2.254.498.95

18.0236.0570.09

140.19315.43

224.5112.256.128.114.07.03.51.8

0.651.312.615.21

10.4620.9241.8381.34

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CRAY T916 July 95 1248

18.569.544.772.42

6.8013.2326.4552.14

76.1338.1119.129.65

1.923.847.66

15.17

CRAY Y-MP Aug 92 18

126.1715.87

1.07.95

NANA

NANA

DEC Alpha Server8400 5/300(300 MHz)

Oct 95 148

16

155.677.9739.1

19.71

0.811.613.236.40

622.22311.9

156.6978.43

0.240.470.931.87


Nov 96 1248

12

94.632847.375023.812512.10168.4609

1.332.665.30

10.4314.91

378.3750189.234494.859447.617233.1172

0.390.771.543.074.42

Fujitsu VPP500 Aug 94 1248

163264

44.2522.3411

11.245.672.871.460.75

2.855.65

11.2322.2643.9686.42

168.23

176.6488.7866

44.5222.3611.265.682.88

0.831.653.296.5

13.0025.7850.84

Fujitsu VX Nov 96 124

30.331215.31057.3720

4.168.24

17.11

120.948557.690730.4367

1.212.544.81

Fujitsu VPP300 Nov 96 1248

16

30.331215.31057.37203.92171.9962

4.168.24

17.1132.1763.20

120.948557.690730.436714.60487.7563

1.212.544.81

10.0218.88


1632

30.331215.31057.37203.92171.99621.0265

4.168.24

17.1132.1763.20

122.91

120.948557.690730.436714.60487.75633.7444

1.212.544.81

10.0218.8839.10

IBM RS/6000 SPWide-node1 (67 MHz)

Mar 95 8163264

128

19.919.954.982.491.25

6.3412.6925.3450.67

100.94

79.7539.8919.99.954.99

1.843.677.36

14.7129.34


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IBM RS/6000 SPP2SC node (120 MHz)

Nov 96 8163264

NANANANA

NANANANA

39.8420.0410.025.02

3.687.31

14.6129.17

IBM RS/6000 SPThin-node2 (67 MHz)

Mar 95 8163264

128

20.8210.425.232.621.31

6.0612.1124.1248.1696.31

82.9441.4720.7510.375.19

1.773.537.06

14.1228.21

Intel iPSC/860 May 92 3264

128

102.751.425.7

1.232.464.91

NANANA

NANANA

Intel ParagonOSF R 1.2

Jan 95 64128256512

1024

15.29 7.673.872.231.15

8.2516.4532.6056.58

109.71

61.0430.5715.378.934.45

2.404.799.53

16.4032.90

Intel Paragon(SunMos turbo)

Jan 95 64128256512

1024

7.803.93 2.001.12 .59

16.1832.1063.09

112.65213.85

31.1515.607.823.982.05

4.709.39

18.6236.7971.42

Intel Paragon MPOSF R1.3

Jan 95 64128256512

8.024.172.261.28

15.7330.2655.8395.57

31.4215.888.114.23

4.669.22

18.0534.61

Intel Paragon MP(SunMos turbo)

Nov 95 64128256512

5.752.941.540.87

21.9442.9281.93

145.02

22.7011.405.782.98

6.4512.8425.3449.13

Kendall Square KSR1 Oct 93 163264

128

101.951.426.012.8

1.232.454.859.86

NANANANA

NANANANA

Kendall Square KSR2 Feb 94May 94

3264

24.813.0

5.099.71

NA46.6

NA3.14

Kyoto/MatsushitaADENART

Feb 94 256 32.9 3.83 NA NA


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MasPar MP-1 Aug 92 4K 16K

248.0 69.3

0.511.82

NANA

NANA

MasPar MP-2 Nov 92 16K 22.4 5.63 NA NA

Meiko CS-1 Aug 92 16 116.8 1.08 NA NA

Meiko CS-2 Oct 94 16326496

128

39.3920.4511.007.846.29

3.206.16

11.4616.0720.06

152.8177.2039.4826.8421.16

0.961.903.715.456.92

nCUBE-2S Mar 94 64128256512

1024

83.841.9320.9710.505.25

1.513.016.02

12.0224.03

336.3168.284.142.121.0

0.440.871.743.486.97

NEC SX-3 Oct 94 1 21.27 5.93 NA NA

NEC SX-4/32 Nov 96 1248

1632

NANANANANANA

NANANANANANA

89.5644.79

22.41711.2245.6582.944

1.633.276.53

13.0425.8749.73

Silicon GraphicsPower Challenge XL(75 MHz)

Oct 94 148

16

242.9561.4430.7715.48

0.522.054.108.15

973.62245.74122.9861.79

0.150.601.192.37

SGIPower Challenge XL(90 MHz)

May 95 1248

16

169.1087.4643.8721.9811.05

0.751.442.885.74

11.42

676.78352.31176.5287.8044.22

0.220.420.831.673.31

SGI Origin200(180 MHz)

Nov 96 124

110.4756.6829.43

1.142.234.29

442.77224.93114.87

0.330.651.27


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Nov 96 1248

163132

101.9351.7025.8313.006.68NA

3.55

1.242.444.889.71

18.89NA

35.54

408.25207.22103.4452.0626.71

NA14.17

0.360.711.422.815.48NA

10.33

Thinking MachinesCM-2

Oct 91 8K16K32K64K

126.663.9 33.718.8

1.001.973.746.71

NANANANA

NANANANA


Oct 91 8K16K32K64K

76.939.220.710.9

1.643.226.10

11.58

NANANANA

NANANANA


Nov 92 163264

128256512

42.421.510.95.42.71.4

2.985.87

11.5823.3646.7390.12

NANANANANANA

NANANANANANA

Thinking MachinesCM-5E

Sep 95 1632

27.213.6

4.649.28

108.554.3

1.352.70


Sept 95 64128256

6.93.62.0

18.2935.0463.09

27.113.7 7.0

5.4010.6920.92


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Table 3: Results of the Multigrid (MG) benchmark.

Computer System

DateReceived

NumberProcessor

Class A Class B

Time in seconds

Ratio toCRAY

Y-MP/1

Time in seconds

Ratio toCRAYC90/1


Mar 95 18

163264

208.029.917.311.0NA

0.110.741.282.02NA

NA150.485.152.739.6

NA0.220.400.640.85


Nov. 96 148

16

28.18.05.34.3

0.792.784.195.17

NANANANA

NANANANA


16

7.273.711.921.100.71

3.065.99

11.5820.2031.30

33.7817.248.894.593.43

1.001.963.807.369.85

CRAY EL Aug 92 148

89.1927.9422.30

0.25 0.800.95

NANANA

NANANA

CRAY J916 Feb 95 1248

16

39.0820.5210.755.883.82

0.571.092.073.782.06

184.8894.7148.6926.6016.12

0.180.360.691.272.10


128256512

1024

13.786.402.611.360.740.390.25

1.613.478.51

16.3430.0356.9788.88

66.5830.1012.566.573.371.741.15

0.511.112.695.14

10.0219.4129.38

CRAY T3E Nov 96 248

163264

128256

NA11.25.62.81.50.80.40.2

NA1.983.977.94

14.8127.7855.55111.1

NA52.726.413.47.03.82.01.1

NA0.641.282.524.838.89

16.8930.71

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4.432.281.270.99

5.029.75

17.5022.44

20.3010.505.544.06

1.663.226.108.32

CRAY Y-MP Aug 92 18

22.222.96

1.007.51

NANA

NANA

Fujitsu VPP500 Mar 95 48

1632

1.440.750.420.26

15.4329.6352.9085.46

6.813.592.011.26

4.969.41

16.8126.81

Fujitsu VX Nov 96 4 1.38 16.10 6.58 5.13


16

1.380.750.41

6.1029.6354.20

6.583.591.95

5.139.41

17.32


1632

1.380.750.410.25

6.1029.6354.2088.88

6.583.591.951.30

5.139.41

17.3225.98

IBM SP-1 Mar 94 8163264

17.509.495.102.89

1.272.344.367.69

82.0344.57 24.3713.86

0.410.761.392.44


Oct 94 8163264

128

6.043.171.690.950.53

3.687.01

13.1523.3941.92

27.9214.587.724.362.46

1.212.324.387.75

13.73


Nov 96 8163264

NANANANA

NANANANA

17.009.024.912.91

1.993.756.88

11.61


Feb 95 8163264

128

7.183.741.991.120.63

3.095.94

11.1719.8435.27

32.7317.139.145.202.95

1.041.973.966.50

11.45

Intel iPSC/860 Aug 92 128 8.6 2.58 NA NA


15 - 53

Intel Paragon MP(OSF1.3)

Jan 95 64128256

6.13.532.48

3.646.298.96

28.715.910.4

1.182.123.24

Intel Paragon( SunMos )

Jan 95 64128256512

7.724.052.351.75

2.885.499.46

12.70

36.919.511.4 8.51

0.921.732.963.97

Intel Paragon(SunMos Turbo)

Nov 95 64128256512

5.853.171.871.46

3.87.01

11.8815.22

27.915.29.057.01

1.212.223.734.82

Intel Paragon MP SunMos Turbo

Jan 95 64128256512

4.832.781.671.37

4.607.99

13.3116.22

23.313.48.126.72

1.452.524.165.03

Kendall Square KSR1 Feb 94 3264

128

19.710.35.6

1.132.163.97

NANANA

NANANA


32 64

10.35.7

2.20 3.90

NA26.1

NA1.29

MasPar MP-1 Aug 92 16K 12.0 1.86 NA NA


Meiko CS-1 Aug 92 16 42.8 0.52 NA NA

Meiko CS-2 Oct 94 16 64128

7.602.351.43

2.93 9.8315.54

35.4610.766.55

0.953.145.16

NEC SX-3 Oct 94 1 2.80 7.94 13.16 2.57

NEC SX-4/32 Nov 96 1248

1632

NANANANANANA

NANANANANANA

19.289.765.002.631.460.95

1.753.466.76

12.8423.1435.56


16 - 53

nCUBE-2S Mar 94 64128512

1024

37.619.2 5.3 2.8

0.591.164.197.94

NANANANA

NANANANA

SGIPower Challenge90 MHz

Oct 95 1248

16

37.9720.0310.63 6.55 5.71

0.591.112.093.393.89

176.22 93.3049.4530.4326.30

0.190.360.681.111.28


Nov 96 124

34.6921.7712.89

0.641.021.72

245.09151.0477.05

0.140.220.44


Nov 96 1248

163132

30.1417.7510.676.003.34NA

2.12

0.741.252.083.706.65NA

10.48

194.88113.7956.1928.4115.03

NA8.61

0.170.300.601.192.25NA

3.92


Dec 91 16K32K64K

45.826.014.1

0.490.851.58

NANANA

NANANA


Dec 91 16K32K

30.217.2

0.741.29

NANA

NANA


Aug 93 3264

128

19.510.96.1

1.142.033.64

NANANA

NANANA


Sep 95 1632

7.73.8

2.895.85

36.118.7

0.941.81


Sep 95 64128256

2.21.410.91

10.115.7624.42

10.66.23.9

3.195.498.67


17 - 53

Table 4: Results of the Conjugate Gradient (CG) benchmark.

Computer System

DateReceived

.NumberProcessor

Class A Class B

Time in seconds

Ratio toCRAYY-MP/1

Time in seconds

Ratio toCRAYC90/1

BBN TC2000 Dec 91 40 51.4 0.23 NA NA


Mar 95 18

163264

202.922.28.944.30NA

0.060.541.332.77NA

NANA

837.0485.4292.1

NANA

0.150.250.42


Nov 96 148

16

37.79.85.02.7

0.321.222.384.41

NANANANA

NANANANA


16

3.431.790.950.530.34

3.486.66

12.5522.4935.06

122.9063.1133.2518.1110.61

1.001.953.706.79

11.58

CRAY EL Sep 93 148

45.2414.2910.14

0.260.831.18

NANANA

NANANA

CRAY J916 July 95 1248

16

15.938.424.422.611.68

0.751.422.704.577.10

532.03293.24150.9280.6742.86

0.230.420.811.522.87


128256512

1024

14.377.443.932.111.210.720.58

0.831.603.035.659.85

16.5620.55

570.11291.30158.8182.0747.1527.3416.58

0.220.420.771.502.614.507.41

18 - 53

CRAY T3E Nov 96 128

163264

128256

NANA6.52.91.60.90.60.4

NANA

1.834.117.45

13.2419.8729.80

802.3404.5205.6107.159.333.822.922.2

0.150.300.601.152.073.645.375.54


16

1.951.100.580.38

6.1110.8420.5531.37

73.9837.7919.6511.43

1.663.256.25

10.75

CRAY Y-MP Aug 92 18

11.922.38

1.005.01

NANA

NANA

Fujitsu VPP500 Aug 94 1248

151630

5.683.061.721.04NA

0.80NA

2.103.906.93

11.46NA

14.90NA

NA104.5155.4031.8020.85

NA15.21

NA1.182.223.865.89NA

8.08


5.87033.18021.8185

2.033.756.55

NA104.140857.8277

NA1.182.13


1516

5.87033.18021.81851.0656

NA0.7514

2.033.756.55

11.19NA

15.86

NA104.140857.827732.060519.7696

NA

NA1.182.133.836.22NA


15163035

5.87033.18021.81851.0656

NA0.7514

NA0.6726

2.033.756.55

11.19NA

15.8NA

17.72

NA104.140857.827732.060519.7696

NA13.4585

NA

NA1.182.133.836.22NA

9.13NA


19 - 53

IBM SP-1 Feb 94 8163264

21.3712.827.984.72

0.560.931.492.53

NA 638.2362.9193.4

NA 0.190.340.64


Mar 94 8163264

128

4.913.092.091.6

1.38

2.433.865.707.458.64

156.2188.4

52.5333.7925.44

0.791.392.343.644.83


Nov 96 8163264

NANANANA

NANANANA

115.8862.2136.2222.71

1.061.983.395.41


Mar 95 8163264

128

5.603.482.341.721.48

2.133.435.096.938.05

234.46120.2367.1638.5228.50

0.521.021.833.194.31

Intel iPSC/860 Sep 93 128 7.0 1.70 NA NA

Intel Paragon(OSF1.2)

Mar 94 64128256512

4.103.302.83NA

2.913.614.21NA

NA132.570.0 47.6

NA0.931.762.58

Intel Paragon(SunMos)

Nov 95 64128256512

3.592.76 2.44

NA

3.324.314.89NA

NA125.4 63.640.5

NA0.981.933.03


19.013.4

0.630.89

NANA

NANA


9.8 6.1

1.221.95

NA182.0

NA0.67

MasPar MP-1 Aug 92 4K16K

64.514.6

0.180.82

NANA

NANA


Meiko CS-1 Aug 92 16 67.5 0.18 NA NA

Meiko CS-2 Oct 94 1632

7.185.60

1.662.13

248.30156.50

0.490.79


20 - 53

nCUBE-2S Mar 94 64128256512

1024

29.616.9 9.66.24.1

0.400.7 11.241.922.91

NANANANANA

NANANANANA

NEC SX-4/32 Nov 96 124

NANANA

NANANA

81.7745.1226.31

1.502.724.67


Oct 94 1248

16

39.016.97.24.53.5

0.310.711.662.653.41

NANANANANA

NANANANANA

SGIPower Challenge(90 MHz)

May 95

Oct 95

1248

16

35.1419.588.794.032.54

0.340.611.352.964.69

NANANANANA

NANANANANA


Nov 96 124

31.3818.679.76

0.380.641,22

1731.181002.32624.62

0.070.120.20


Nov 96 1248

1631

26.8914.376.233.022.04NA

0.440.831.913.955.84NA

1538.71851.82490.76283.19156.5779.65

0.080.140.250.430.781.54


Mar 92 8K16K32K

25.614.1 8.8

0.470.851.35

NANANA

NANANA


Aug 93 32 64128

20.710.66.2

0.581.121.92

NANANA

NANANA


Sep 95 1632

13.58.0

0.881.49

454251

0.270.49


Sep 95 64128256

5.43.93.4

2.213.063.51

14991 62

0.821.351.98


21 - 53

Table 5: Results of the 3-D FFT PDE (FT) benchmark.

Computer System

DateReceived

NumberProcessor

Class A Class B

Time in seconds

Ratio toCRAY

Y-MP/1

Time in seconds

Ratio toCRAYC90/1


Mar 95 18

1632

178.625.520.513.9

0.161.131.402.07

NA375.4

NANA

NA0.29NANA


16

8.954.532.291.290.80

3.216.35

12.5622.3035.96

110.6055.7527.9514.127.65

1.001.983.967.83

14.46

CRAY EL May 93 148

105.127.918.5

0.271.031.56

NANANA

NANANA


16

42.8422.0811.215.803.41

0.671.302.574.978.44

530.06267.92134.9270.5138.06

0.210.410.821.572.91


128256512

1024

11.805.902.991.520.770.510.32

2.444.879.62

18.9337.3656.4189.91

NANA

40.5720.6810.776.443.76

NANA

2.735.35

10.2717.1729.41

CRAY T3E Nov 96 248

163264

128256

28.914.47.33.71.91.00.50.2

1.002.003.947.78

15.1428.7757.54

143.85

NANA

86.243.121.811.05.52.8

NANA

1.282.575.07

10.0520.1139.5

22 - 53


5.232.671.400.98

5.5010.7820.5529.36

64.8132.3916.659.48

1.713.416.64

11.67

CRAY Y-MP Aug 92 18

28.774.19

1.06.87

NANA

NANA

Fujitsu VPP500 Sept 95 1248

163264

11.255.672.881.440.750.400.24

2.565.079.99

19.9838.3671.93

119.88

NANA

31.2115.927.944.072.18

NANA

3.546.95

13.9127.1750.73


6.32724.37882.2557

4.556.57

12.75

NA49.688524.5128

NA2.234.51


16

6.32724.37882.25571.14910.6005

4.556.57

12.7525.0447.91

NA49.688524.512812.37586.3013

NA2.234.518.94

17.55


1632

6.32724.37882.25571.14910.60050.3345

4.556.57

12.7525.0447.9186.01

NA49.688524.512812.37586.30133.2577

NA2.234.518.94

17.5533.95

IBM SP-1 Feb 94 8163264

43.6822.8612.086.46

0.661.262.384.45

NA286.5143.274.5

NA0.390.771.49


Oct 94 8163264

128

13.317.173.962.191.23

2.164.017.2713.4

23.39

NA91.8

47.2326.0514.52

NA1.202.344.257.62


23 - 53


Nov 96 8163264

NANANANA

NANANANA

83.2440.5221.0715.07

1.332.735.257.34


Mar 95 8163264

128

14.788.094.312.391.30

1.953.566.68

12.0422.13

NA101.0351.3828.0215.68

NA1.092.153.957.05

Intel iPSC/860 Dec 91Apr 92

64128

20.99.7

1.38 2.97

NANA

NANA

Intel ParagonOSF R 1.2

Nov 95 163264

128256

24.712.996.833.853.46

1.162.214.217.478.32

NANA

83.642.0725.93

NANA

1.322.634.27

Intel ParagonSunMos

Nov 95 163264

128256512

20.4610.545.473.132.82NA

1.412.735.269.19

10.20NA

NANA

60.932.1518.6616.17

NANA

1.823.445.936.84

Intel Paragon MPR1.3

Nov 95 163264

128256

17.69.525.162.932.73

1.633.025.589.82

10.54

NANA

60.931.0

19.87

NANA

1.823.575.57

Intel Paragon MPSunMos Turbo

Nov 95 64 128256512

3.872.382.201.92

7.4312.0913.0814.98

41.822.7614.212.4

2.654.867.798.92


16.29.2

1.783.13

NANA

NANA


3264

9.06.5

3.204.43

NA124.0

NA0.89


Feb 94 256 72.7 0.4 NA NA


24 - 53



Meiko CS-1 Aug 92 16 170.0 0.17 NA NA

Meiko CS-2 Oct 94 16 3264

12.677.174.53

2.274.016.35

NA82.7148.04

NA1.342.30

nCUBE-2S Mar 94 64128256512

1024

62.832.916.08.44.1

0.460.871.8

3.437.02

NANANANANA

NANANANANA

NEC SX-3 Oct 94 1 2.79 10.31 37.52 2.95

NEC SX-4/32 Nov 96 1248

1632

NANANANANANA

NANANANANANA

56.5728.1414.798.034.743.14

1.963.937.48

13.7723.3335.22


Oct 94 1248

16

61.1735.5319.9812.5711.18

0.470.811.442.292.57

761.67414.52223.97130.15110.37

0.150.270.490.851.00


May 95 1248

16

51.8927.4916.6410.479.23

0.551.051.732.753.12

642.3331.5181.4110.693.9

0.170.330.611.001.18


Nov 96 124

66.5635.5118.61

0.430.811.55

NANANA

NANANA


25 - 53


Nov 96 1248

1632

55.4329.5315.568.054.553.16

0.520.971.853.576.329.10

810.41419.72215.95108.4254.8828.66

0.140.260.511.022.023.85


Dec 91 16K 32K64K

37.018.211.4

0.781.582.52

NANANA

NANANA


Dec 91 8K 45.6 0.63 NA NA


Aug 93 32 64

128

14.97.96.6

1.933.644.36

NANANA

NANANA


Sep 95

Feb 94

1632 64

128

12.86.73.92.9

2.254.297.389.92

16082.046.034.0

0.691.352.403.25


Sep 95 64 128256

3.51.961.33

8.2214.6721.63

41.922.513.2

2.644.928.38


26 - 53

Table 6: Results of the Integer Sort (IS) benchmark.

Computer System Date

ReceivedNumber

Processor

Class A Class B

Time in seconds

Ratio toCray

Y-MP/1

Time in seconds

Ratio toCrayC90/1


Mar 95 18

83.210.1

0.141.13

NA43.5

NA0.30


Nov 96 148

16

30.67.043.492.21

0.371.633.285.19

NANANANA

NANANANA


16

3.331.640.850.460.27

3.446.99

13.4824.9142.44

12.926.503.301.730.98

1.01.993.927.47

13.18

CRAY EL Sep 93 148

43.7612.99 8.45

0.260.881.35

NANANA

NANANA


16

13.757.023.812.211.63

0.831.633.005.197.03

54.4127.9613.937.604.91

0.240.460.931.702.63


128256512

1024

7.073.892.091.050.550.310.44

1.622.955.48

10.9120.8436.9726.05

NA16.578.744.562.361.331.22

NA0.781.482.835.479.71

10.59

27 - 53

CRAY T3E Nov 96 248

163264

128256

16.98.14.02.21.20.60.30.2

0.681.422.875.219.55

19.1038.2057.30

NA38.918.69.85.12.91.60.8

NA0.330.691.322.534.468.08

16.15


2.021.020.520.38

5.6711.2422.0430.16

7.443.741.921.41

1.743.456.739.16

CRAY Y-MP Aug 92 18

11.461.85

1.006.19

NANA

NANA

Fujitsu VPP500 Apr 94 1248

2.1891.5741.0980.917

5.247.28

10.4412.50

NANA

3.703.03

NANA

3.494.26


2.39681.80381.2519

4.786.359.15

9.19646.08754.1363

1.412.123.12


16

2.39681.80381.25191.12491.0204

4.786.359.15

10.1911.23

9.19646.08754.13633.19592.7231

1.412.123.124.044.74


1632

2.39681.80381.25191.12491.02040.9839

4.786.359.15

10.1911.2311.64

9.19646.08754.13633.19592.72312.7211

1.412.123.124.044.744.75

IBM SP-1 Feb 94 8163264

16.818.855.043.06

0.681.29 2.273.75

NA 37.320.111.2

NA0.350.641.15


28 - 53


Mar 95 8163264

128

4.932.651.540.890.59

2.324.327.44

12.8819.42

19.7510.605.923.411.98

0.651.222.183.796.53


Nov 96 8163264

NANANANA

NANANANA

11.165.853.201.75

1.162.214.047.38


Feb 95 8163264

128

5.162.891.660.910.61

2.223.976.90

12.5918.79

20.7911.466.373.582.05

0.621.132.033.616.30

Intel iPSC/860 May 92 3264

128

25.717.313.6

0.450.660.84

NANANA

NANANA


Mar 94 3264

128256512

7.814.342.41NANA

1.472.644.76NANA

NA17.339.525.94 4.69

NA0.751.362.182.75


Mar 94 3264

128

5.483.772.29

2.093.045.00

NA11.987.22

NA1.081.79


10.86.6

1.06 1.74

NANA

NANA


3264

7.03.9

1.642.94

NA20.3

NA0.64


Feb 94 256 46.6 0.25 NA NA

MasPar MP-1 Jan 93 16K 11.5 1.00 NA NA

MasPar MP-2 Jan 93 16K 7.7 1.49 NA NA

Meiko CS-1 Aug 92 16 62.7 0.18 NA NA


29 - 53

nCUBE-2S Mar 94 64128256512

1024

23.2 12.0 6.13.21.7

0.490.961.883.58 6.74

NA47.5NA

12.5 6.5

NA0.27NA

1.031.99

NEC SX-4/32 Nov 96 1248

16

NANANANANA

NANANANANA

6.773.50

1.8771.1390.896

1.913.696.88

11.3414.42


Oct 95 1248

20.011.97.15.0

0.570.961.612.29

NANANANA

NANANANA


Nov 96 124

17.269.184.89

0.661.252.34

235.05154.2879.18

0.0550.0840.16


Nov 96 1248

1632

13.667.073.802.141.341.21

0.841.623.025.368.559.47

104.4854.3627.2515.098.895.76

0.120.240.470.861.452.24


Dec 91 64K 5.7 2.01 NA NA


Aug 93 3264

128

43.124.2 12.0

0.270.470.96

NANA

NANANA


Sep 95

Feb 94

163264

128

11.96.13.1

1.66

0.961.88 3.706.90

NA31.416.4 8.4

NA0.41 0.791.54


Sep 95 64128256

3.161.67 1.16

3.636.869.88

16.18.2 4.3

0.801.583.0


30 - 53

Table 7: Results of the LU CFD Application (LU)benchmark..

ComputerSystem

DateReceived

No.Proc.

Class A Class B

Time in seconds

Ratio toCray

YMP/1

Time in seconds

Ratio toCrayC90/1

BBN TC2000 Dec 91 62 3032.0 0.11 NA NA


Mar 95 18

1632

2668331 196 126

0.131.001.702.65

NA1492827

465.9

NA0.300.540.9


16

119.7862.2932.2017.1510.17

2.785.35

10.3619.4532.79

449.54231.98121.2663.0337.93

1.001.943.717.13

11.85

CRAY EL Aug 92 148

1449.0522.3351.6

0.23 0.64 0.95

NANANA

NANANA


16

492.83254.94135.0772.7347.59

0.681.312.474.517.01

1994.051024.74526.29286.17170.26

0.230.440.851.572.64


128256512

1024

205.69106.8955.3228.7115.949.027.09

1.623.126.03

11.6220.9236.9747.04

844.53451.18233.45120.5365.0636.3920.77

0.531.001.933.736.9

12.3521.64

31 - 53

CRAY T3E Nov 96 248

163264

128256

356.4179.290.246.924.012.97.14.2

0.941.863.707.11

13.9025.8546.9779.41

1497.4728.9365.8185.195.951.529.516.8

0.300.621.232.434.698.73

15.2426.76


16

82.6746.9123.6815.74

NA

4.037.11

14.0821.19

NA

293.38149.3377.9543.1328.26

1.533.015.77

10.4215.91

CRAY Y-MP Aug 92 18

333.549.5

1.006.74

NANA

NANA


Oct 95 1248

12

528.6301.77158.7891.7279.13

0.631.112.103.644.21

2304.91350.0691.8

376.23296.19

0.200.330.651.191.51


Nov 96 1248

378.61219.41115.8367.965

0.881.522.884.91

1684.47987.54500.12271.32

0.270.460.901.66

Fujitsu VPP500 Oct 95 123468

161734

101.96061.409

NA35.789

NA21.04113.944

NANA

3.275.43NA

9.31NA

15.8523.92

NANA

414.82242.23175.20

NA97.851

NANA

43.64428.095

1.081.862.57NA

4.59NANA

10.3016.00


77.73250.880

NA30.500

4.296.55NA

10.93

297.94190.00138.34

NA

1.512.373.25NA

32 - 53


16

77.73250.880

NA30.500

NA18.44412.553

4.296.55NA

10.93NA

18.0826.57

297.94190.00138.34

NA78.026

NANA

1.512.373.25NA

5.76NANA


161732

77.73250.880

NA30.500

NA18.44412.553

NA10.063

4.296.55NA

10.93NA

18.0826.57

NA33.14

297.94190.00138.34

NA78.026

NANA

36.736NA

1.512.373.25NA

5.76NANA

12.24NA

IBM SP-1 Feb 94 8163264

291.4172.9101.863.2

1.141.933.285.28

NA604.8348.1207.5

NA0.741.292.17


Mar 95 8163264

128

112.564.636.522.715.2

2.965.169.14

14.6921.94

429.8234.4129.776.847.8

1.051.923.475.859.4


Oct 95 18

163264

501.580.8148.3629.4119.20

0.674.136.90

11.3417.37

2066.6311.53171.7998.0459.45

0.221.442.624.59 7.56


Nov 96 8163264

NANANANA

NANANANA

236.64126.7773.1642.89

1.903.556.14

10.48


Mar 95 8163264

128

120.870.940.124.515.9

2.764.708.32

13.6120.97

477.3255.4141.382.951.2

0.941.763.185.428.78

Intel iPSC/860 Mar 91 64128

690.8 442.5

0.480.75

NANA

NANA

33 - 53

Intel Paragon (OSF1.2) Jul 94 64128256512

190.0118.075.0NA

1.762.834.45NA

675.0406.0254.0175.0

0.671.111.772.57


128

341.0199.0155.0

0.981.682.15

NANANA

NANANA


32 64

172.0102.0

1.933.27

NA424.0

NA1.06



Meiko CS-1 Aug 92 16 2937.0 0.11 NA NA

nCUBE-2S Mar 94 64128256512

1024

1322.0712.5389.1226.1134.1

0.250.47 0.861.482.49

NANANANANA

NANANANANA

NEC SX-4/32 Nov 96 1248

161732

NANANANANANANA

NANANANANANANA

291.06148.2977.24643.08727.15125.29420.909

1.543.035.82

10.4316.5617.7721.50


Oct 94 148

16

604.0231.8111.765.3

0.551.442.995.11

2617.91010.5550.2308.1

0.170.440.821.46

SGIPower Challenge - XL(90 MHz)

Oct 94 1248

16

549.02356.73188.33101.0065.90

0.610.931.773.305.06

2439.901500.30774.93419.90292.02

0.180.300.581.071.54


Nov 96 124

397.30206.52114.39

0.841.612.92

1873.60958.01519.32

0.240.470.87

34 - 53


Nov 96 1248

162531

351.35181.3997.5250.5629.91

NA18.93

0.951.843.426.60

11.15NA

17.62

1522.30777.43401.80221.32130.4189.75

NA

0.300.581.122.033.455.01NA


Mar 91 8K16K32K

1307.0850.0546.0

0.260.39 0.61

NANANA

NANANA


Aug 93 3264

128

418.0272.0171.0

0.801.231.95

NANANA

NANANA


Sep 95

Feb 94

163264

128

25614397.065.0

1.302.333.445.13

957533

367.0318.0

0.470.841.221.41


Sep 95 64128256

90 6143

3.715.477.76

336247149

1.341.823.02

35 - 53

Table 8: Results of the SP simulated CFD application (SP) benchmark.

Computer System

DateReceived

NumberProcessor

Class A Class B

Time in seconds

Ratio toCray

YMP/1

Time in seconds

Ratio toCrayC90/1

BBN TC2000 Dec 91 112 880.0 0.54 NA NA

Convex Exemplar SPP1000

Mar 95 18

163264

2533345228144102

0.191.372.073.274.62

NA15841068697.4449.5

NA0.440.650.991.5

HP/Convex Exemplar SPP2000

Nov 96 148

16

770.9198.6101.656.6

0.612.374.648.33

NANANANA

NANANANA


16

174.5087.3244.7522.7412.82

2.705.40

10.5420.7336.78

689.60345.57175.8590.8052.22

1.002.003.927.59

13.21

CRAY EL Aug 92 148

2025.7601.9488.4

0.23 0.78 0.97

NANANA

NANANA


16

870.47436.91226.66118.3077.54

0.541.082.083.996.08

3728.691927.50941.08521.73316.58

0.180.360.731.322.18


128256512

1024

202.11104.1053.2627.5414.718.915.41

2.334.538.85

17.1232.0552.9287.15

818.07463.62233.52130.4574.8942.6325.23

0.841.492.955.299.21

16.1827.33

36 - 53

CRAY T3E Nov 96 248

163264

128256

621.9313.0157.579.839.220.411.26.0

0.761.513.005.91

12.0323.1142.1078.58

2427.71230.5611.7312.9162.785.548.126.9

0.280.561.132.204.248.07

14.3425.64

CRAY T916 Jul 95 1248

16

112.3756.4630.4218.69

NA

4.208.35

15.5025.23

NA

427.56214.63113.0260.6140.59

1.613.216.10

11.3816.99

CRAY Y-MP Aug 92 18

471.564.6

1.017.30

NANA

NANA


Mar 95 148

12

749.61199.17118.04102.75

0.632.373.994.59

3448.10904.45452.13364.54

0.200.761.531.89


Nov 96 1248

575.80290.83153.8991.430

0.821.623.065.16

2569.51294.9661.45363.35

0.270.531.041.90


161732345164

99.30961.58832.114

NA16.3998.5761

NA4.5355

NANA

2.5483

4.757.66

14.68NA

28.7554.98

NA103.96

NANA

185.03

404.08241.23127.4883.71064.930

NA30.474

NA15.67410.654

NA

1.712.865.418.24

10.62NA

22.63NA

44.064.73

NA


80.50460.43631.324

5.867.80

15.05

331.36219.11114.41

2.083.156.03


37 - 53


16

80.50460.43631.324

NA16.0548.2465

5.867.80

15.05NA

29.3757.18

331.36219.11114.4178.38158.781

NA

2.083.156.038.80

11.73NA


16173234

80.50460.43631.324

NA16.0548.2465

NA4.5311

NA

5.867.80

15.05NA

29.3757.18

NA104.06

NA

331.36219.11114.4178.38158.781

NA27.860

NA14.621

2.083.156.038.80

11.73NA

24.75NA

47.17

IBM SP-1 Feb 94 8163264

441.6268.7165.0100.4

1.071.752.864.69

NA941.2522.4 302.3

NA0.731.322.28


Mar 95 8163264

128

143.883.248.730.118.7

3.285.679.68

15.6625.21

589.3300.6163.891.754.8

1.172.294.217.52

12.58


Oct 95 18

163264

711.8114.1569.3243.2026.46

0.664.136.80

10.9117.82

3087.0453.66248.51142.8880.17

0.221.522.774.838.60


Nov 96 8163264

NANANANA

NANANANA

359.81182.30107.1658.35

1.923.786.44

11.82


Mar 95 8163264

128

161.193.353.632.720.6

2.935.058.80

14.4222.89

640.9342.3184.4101.659.9

1.082.013.746.79

11.51


38 - 53

Intel iPSC/860 Jul 94Aug 92

64128

640.0 449.5

0.741.05

NANA

NANA


Jul 94 64102128204256324400484

226.0NA

143.0NA

97.089.0NANA

2.09NA

3.30NA

4.865.30NANA

960.0610.0

NA387.0301.0262.0246.0209.0

0.721.13NA

1.782.292.632.803.30


128

418.0257.0160.0

1.131.83 2.95

NANANA

NANANA

Kendall Square KSR2 Feb 94 May 94

3264

221.0131.0

2.133.59

NA495.0

NA1.39


Feb 94 256 209.9 2.24 NA NA

MasPar MP-1 Aug 92 4K 1772 0.27 NA NA

MasPar MP-2 Nov 92 4K 615 0.77 NA NA

Meiko CS-1 Aug 92 16 2975 0.16 NA NA

nCUBE-2S Mar 94 64128256512

1024

1243.2717.4387.3208.6120.9

0.380.661.222.263.90

NANANANANA

NANANANANA

NEC SX-3 Oct 94 1 75.72 6.23 495.0 1.39

NEC SX-4/32 Nov 96 1248

16172632

NANANANANANANANA

NANANANANANANANA

398.77199.0899.98452.35328.82324.69717.41017.130

1.733.466.90

13.1723.9327.9239.6140.26


39 - 53


Oct 94 148

16

858.3225.8119.567.2

0.552.093.957.02

3719.5947.6491.4313.1

0.190.731.402.20

SGIPower Challenge - XL(90 MHz)

May 95 1248

16

757.00387.90200.44106.4363.18

0.621.222.354.437.46

3343.901685.30853.35445.38294.22

0.210.410.811.552.34


Nov 96 124

768.25408.32222.04

0.611.152.12

4036.902259.901229.30

0.170.310.56


Nov 96 1248

162531

675.28346.02187.8697.9752.01

NA30.47

0.701.362.514.819.07NA

15.47

3068.701628.00803.64423.61234.99140.48

NA

0.220.420.861.632.944.91NA


Dec 91 16K 32K64K

1444.0917.0640.0

0.330.510.74

NANANA

NANANA


3264

128

289.0170.0119.0

1.632.773.96

NANANA

NANANA


Sep 95

Feb 94

163264

128

268144

104.061.0

1.763.274.537.73

1580771

595.0320.0

0.440.891.162.16


Sep 95 64128256

85 51 34

5.559.25

13.87

405 236140

1.702.924.93


40 - 53

Table 9: Results of the BT simulated CFD application (BT) benchmark.

Computer System Date

ReceivedNumber

Processor

Class A Class B

Time inseconds

Ratio toCRAY

Y-MP/1

Time in seconds

RatioCRAYC90/1

BBN TC2000 Dec 91 112 1378.0 0.58 NA NA


Mar 95 18

163264

282536621112578

0.282.173.766.34

10.16

NA1675984

559.8338.2

NA0.611.041.823.03


Nov 96 148

16

829.4212.9107.255.3

0.963.727.39

14.33

NANANANA

NANANANA


16

276.80139.4472.1136.9920.30

2.865.68

10.9921.4239.03

1023.4519.46265.20138.1678.80

1.001.973.867.41

12.99

CRAY EL May 93 148

3832.81090.2764.1

0.210.731.04

NANANA

NANANA


16

1202.53608.83317.62168.4698.80

0.661.302.494.708.02

5356.592789.741414.43765.60426.91

0.190.370.721.342.40


128256512

1024

230.41115.5359.0129.9615.898.394.56

3.446.85

13.4326.4449.8794.45

173.77

918.04476.97252.86128.2168.3838.0120.45

1.112.154.047.9815.0

26.9250.04

41 - 53

CRAY T3E Nov 96 248

163264

128256

677.9339.8172.588.644.622.711.96.2

1.172.334.598.94

17.7734.9166.59

127.81

2988.71480.7735.6370.3192.299.954.529.3

0.340.691.392.765.32

10.2418.7834.93


16

193.19100.1053.2330.66

4.107.92

14.8925.84

649.10332.38169.2792.4364.06

1.583.086.05

11.0715.98

CRAY Y-MP Aug 92 18

792.4114.0

1.006.95

NANA

NANA


Oct 95 1248

12

1048.7527.04271.13146.91103.47

0.761.502.925.397.66

4076.502525.001278.60649.53458.21

0.250.410.801.582.23


Nov 96 1248

747.75376.03192.67103.54

1.062.114.117.65

3390.41727.7881.90454.39

0.300.591.162.25


161732345164

142.4275.1739.1419.829.99NA

5.09NANA

2.66

5.5610.5420.2539.9879.32

NA155.68

NANA

297.90

NANANANANA

37.26NA

18.8212.61

NA

NANANANANA

27.47NA

54.3881.16

NA


129.4068.51035.518

6.1211.5722.31

487.29258.20175.09

2.103.965.84


42 - 53


16

129.4068.510

NA35.518

NA18.0889.2841

6.1211.57

NA22.31

NA43.8185.35

487.29258.20175.09

NA88.541

NANA

2.103.965.84NA

11.56NANA


16173234

129.4068.510

NA35.518

NA18.0889.2841

NA4.9286

NA

6.1211.57

NA22.31

NA43.8185.35

NA160.78

NA

487.29258.20175.09

NA88.541

NANA

31.634NA

16.824

2.103.965.84NA

11.56NANA

32.35NA

60.83

IBM SP-1 Aug 94 8163264

443.9249.2143.083.1

1.793.18 5.54 9.54

NA987.4511.2274.6

NA1.042.003.73


Mar 95 8163264

128

206.7112.961.834.720.1

3.837.02

12.8222.8439.42

862.8440.6226.8119.167.0

1.192.324.518.59

15.27


Oct 95 18

163264

1130.7170.7495.4851.3429.01

0.704.648.30

15.4427.31

4775.7708.47375.76197.91105.19

0.211.442.725.179.73


Nov 96 8163264

NANANANA

NANANANA

504.58263.77143.7776.49

2.033.887.12

13.38


Feb 95 8163264

128

216.6118.064.936.320.8

3.666.72

12.2121.8338.10

889.8459.2237.2124.869.6

1.152.234.318.20

14.70


43 - 53

Intel iPSC/860 Aug 92 64128

714.7414.3

1.11 1.91

NANA

NANA


Mar 94 64102128204256306408510512

235.0NA

129.0NA

83.0NANANA

63.0

3.37NA

6.14NA

9.55NANANA

12.58

NA633.0

NA359.0

NA257.0226.0196.0

NA

NA1.62NA

2.86NA

3.984.535.22NA


Nov 93Mar 94

64102128204306

224.0NA

113.0NANA

3.54NA

7.01NANA

NA598.0

NA324.0215.0

NA1.71NA

3.164.76


128

457256 145

1.743.1

5.46

NANANA

NANANA


3264

225130

3.526.10

NA542.0

NA1.89


Feb 94 256 314.1 2.52 NA NA



Meiko CS-1 Aug 92 16 2984.0 0.27 NA NA

Meiko CS-2 Oct 94 81632

570.4 286.6 149.3

1.392.775.31

NANANA

NANANA

nCUBE-2S Mar 94

Jul 94

64128256512

1024

1243.2644.7336.7179.1100.9

0.641.222.354.427.85

NANANANANA

NANANANANA

NEC SX-3 Oct 94 1 100.31 7.90 NA NA


44 - 53

NEC SX-4/32 Nov 96 1248

16172632

NANANANANANANANA

NANANANANANANANA

577.16288.72146.5975.39340.93235.57423.99624.042

1.773.546.98

13.5725.0028.7742.6542.57


Oct 94 148

16

1330.3355.9177.091.8

0.602.234.488.63

5698.71450.0775.0426.0

0.180.711.322.40

SGIPower Challneg XL(90 MHz)

May 95 1248

16

1145.20574.37298.74152.6580.20

0.691.382.655.199.88

5089.602537.701278.60672.56391.88

0.200.400.801.522.61


Nov 96 124

826.53420.08222.57

0.961.893.56

3953.702091.501069.20

0.260.490.95


Nov 96 1248

162531

768.42388.43196.13103.4155.44

NA30.05

1.032.044.047.66

14.29NA

26.37

3437.701767.00904.23468.77253.07151.87

NA

0.300.581.132.184.046.73NA


Dec 91 16K 32K64K

1118.0634.0370.0

0.71 1.25 2.14

NANANA

NANANA


Dec 91 16K 32K

832.0601.0

0.951.32

NANA

NANA


May 93 3264

128

284.0175.0119.0

2.794.506.66

NANANA

NANANA


45 - 53


Sep 95

Feb 94

163264

128

25913584.048.0

3.065.879.43

16.50

1480 712

464.0253.0

0.691.442.214.05


Sep 95 64128256

7543 27

10.5618.4329.34

370209114

2.774.908.98


46 - 53

Table 10: Results for NPB 1.0 Class C on CRAY T3E.

No. ofCPUs

Wall Clock Time in Seconds

EP MG CG FT IS LU SP BT

1 NA NA NA NA NA NA NA NA

4 448.8 NA NA NA NA NA NA NA

8 224.4 NA NA NA NA NA NA NA

16 112.2 NA 272.9 NA 48.9 773.4 1352.7 1806.5

32 56.1 53.0 146.2 93.4 23.8 387.8 661.5 904.3

64 28.1 26.7 78.5 47.2 14.5 195.3 327.0 454.4

128 14.0 13.6 51.7 23.7 7.5 101.5 174.3 230.6

256 7.0 7.1 46.9 12.1 4.0 52.8 93.9 115.4

47 - 53

Table 11: Approximate sustained performance per dollar for Class B LU benchmark..

Computer System

#

Proc.

Memory Ratioto

C90/1

List PriceMillionDollars

Performanceper Million

Dollars

Date

CRAY T3E 128 64 MB/PE 15.24 5.0 3.05 Nov 96

DEC Alpha Server8400 5/440 (437 MHz)

8 2 GB 1.66 0.58 2.86 Nov 96

Fujitsu VX 3 2 GB /PE 3.25 1.11 2.93 Nov 96

Fujitsu VPP300 6 512 MB /PE 5.76 1.54 3.74 Nov 96

Fujitsu VPP700 17 512 MB/PE 12.24 5.17 2.37 Nov 96


64 128 MB/PE 10.48 3.52 2.98 Nov 96

NEC SX-4/32 32 4 GB 21.50 10.7 2.0 Nov 96


26 2 GB 5.01 0.96 5.21 Nov 96

48 - 53

Table 12: Approximate sustained performance per dollar for Class B SP benchmark..

Computer System

# Proc Memory Ratioto

C90/1


Performanceper Million

Dollars

Date

CRAY T3E 128 64 MB/PE 14.34 5.0 2.87 Nov 96


8 2 GB 1.90 0.58 3.28 Nov 96

Fujitsu VX 4 512 MB/PE 6.03 1.0 6.03 Nov 96




64 128 MB/PE 11.82 3.52 3.36 Nov 96

NEC SX-4/32 32 4 GB 40.26 10.7 3.76 Nov 96


26 2 GB 4.91 0.96 5.11 Nov 96

49 - 53

Table 13: Approximate sustained performance per dollar for Class B BT benchmark..

Computer System

#Proc

Memory Ratioto

C90/1


Performance per Million

Dollars

Date

CRAY T3E 128 64 MB/PE 18.78 5.0 3.76 Nov 96


8 2 GB 2.25 0.58 3.88 Nov 96

Fujitsu VX 3 512 MB/PE 5.84 1.11 5.26 Nov 96




64 128 MB/PE 13.38 3.52 3.80 Nov 96

NEC SX-4/32 32 4 GB 42.57 10.7 3.98 Nov 96


26 2 GB 6.73 0.96 7.01 Nov 96

50 - 53

Table 14: Results of the HPF based EP benchmark.

Computer System DateReceived

NumberProcessor

Time in seconds

Class A Class B

APR PGI APR PGI

HP/ConvexExemplar SPP200

Oct 96 1248

16

NANANANANA

6172891457539

NANANANANA

NANANANANA

IBM SP2Wide Nodes

Sept 96 1248

163264

NANANANA794223

947473237119593015

NANANANANANANA

NA189594647423711959

SGI/CRAY T3D Sept 96 1248

163264

NANANANA864322

1190596302151743719

NANANANANANANA

478223981190595298149NA

51 - 53

Table 15: Results of the HPF based MG benchmark.


NumberProcessor

Time in seconds

Class A Class B

APR PGI APR PGI

IBM SP2Wide Nodes

Sept 96 163264

1297

NANANA

NANANA

NANANA


643725

NANANA

NANANA

NANANA

Table 16: Results of the HPF based FT benchmark.


NumberProcessor

Time in seconds

Class A Class B

APR PGI APR PGI

IBM SP2Wide Nodes(67 mHz)

Sept 96 163264

NANANA

6.23.12.6

NANANA

NANANA


128

NANANANA

27.215.69.55.6

NANANANA

NANANA

19.6

52 - 53

Table 17: Results of the HPF based SP benchmark.


NumberProcessor

Time in seconds

Class A Class B

APR PGI APR PGI


Oct 96 1248

16

NANANANANA

38261908966504274

NANANANANA

NANANANANA

IBM SP2Wide Nodes(67 MHz)

Sept 96 163264

315207130

23714299

NANANA

NANANA


NA803420226

1618834425228

NANANANA

NA332719501012

53 - 53

Table 18: Results of the HPF based BT benchmark.


NumberProcessor

Time in seconds

Class A Class B

APR PGI APR PGI


Oct 96 1248

16

NANANANANA

23721161699335175

NANANANANA

NANANANANA

IBM SP2Wide Nodes(67 MHz)

Sept 96 1248

163264

NANANANA332184109

3273169790746924913581

NANANANANANANA

NANA

378819631111652350


NA1044536275

1669855438226

NANANANA

6795363421191096

NAS Parallel Benchmark Version 1.0 Results 11-96 · 2016. 2. 26. · processors operating in...

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