amazon testing on Ubuntu 22.04 via the Phoronix Test Suite.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2310055-NE-2310039NE76
GCE c3d-standard-60
amazon testing on Ubuntu 22.04 via the Phoronix Test Suite.
,,"c3d-standard-60 AMD Genoa","t2d-standard-60 AMD Milan","c6g.16xlarge"
Processor,,AMD EPYC 9B14 (30 Cores / 60 Threads),AMD EPYC 7B13 (60 Cores),ARMv8 Neoverse-N1 (64 Cores)
Motherboard,,Google Compute Engine c3d-standard-60,Google Compute Engine t2d-standard-60,Amazon EC2 c6g.16xlarge (1.0 BIOS)
Chipset,,Intel 440FX 82441FX PMC,Intel 440FX 82441FX PMC,Amazon Device 0200
Memory,,240GB,240GB,128GB
Disk,,215GB nvme_card-pd,215GB PersistentDisk,215GB Amazon Elastic Block Store
Network,,Google Compute Engine Virtual,Red Hat Virtio device,Amazon Elastic
OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04
Kernel,,6.2.0-1014-gcp (x86_64),6.2.0-1014-gcp (x86_64),5.19.0-1025-aws (aarch64)
Vulkan,,1.3.238,1.3.238,1.3.238
Compiler,,GCC 11.4.0,GCC 11.4.0,GCC 11.4.0
File-System,,ext4,ext4,ext4
System Layer,,KVM,KVM,amazon
,,"c3d-standard-60 AMD Genoa","t2d-standard-60 AMD Milan","c6g.16xlarge"
"BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,510819,629363,
"nekRS - Input: Kershaw (flops/rank)",HIB,4289858333,3681935833,1758860000
"nekRS - Input: TurboPipe Periodic (flops/rank)",HIB,4723940000,2730620000,2221710000
"OpenRadioss - Model: Bumper Beam (sec)",LIB,92.87,75.68,
"OpenRadioss - Model: Chrysler Neon 1M (sec)",LIB,337.70,327.88,
"OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,38.82,30.12,
"HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128 (GFLOP/s)",HIB,148.575,196.948,202.445
"OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,147.31,123.61,
"OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,89.65,72.06,
"Laghos - Test: Sedov Blast Wave, ube_922_hex.mesh (Major Kernels Rate)",HIB,259.55,364.64,321.29
"HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128 (GFLOP/s)",HIB,88.6301,109.676,129.172
"libxsmm - M N K: 64 (GFLOPS/s)",HIB,489.7,554.2,589.5
"Laghos - Test: Triple Point Problem (Major Kernels Rate)",HIB,209.00,222.30,179.52
"HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128 (GFLOP/s)",HIB,57.3116,60.0343,32.3575
"libxsmm - M N K: 32 (GFLOPS/s)",HIB,255.4,289.2,312.7
"OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,,,
"TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,50.99,18.29,
"TensorFlow - Device: CPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,69.68,20.90,
"GROMACS - Implementation: MPI CPU - Input: water_GMX50_bare (Ns/Day)",HIB,4.391,5.289,2.766
"LAMMPS Molecular Dynamics Simulator - Model: 20k Atoms (ns/day)",HIB,19.776,26.734,25.059
"HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128 (GFLOP/s)",HIB,93.6005,106.029,79.0156
"TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,62.74,20.36,
"LAMMPS Molecular Dynamics Simulator - Model: Rhodopsin Protein (ns/day)",HIB,17.423,27.828,26.041
"NAS Parallel Benchmarks - Test / Class: CG.C (Mop/s)",HIB,19597.86,16649.37,13343.35
"Remhos - Test: Sample Remap Example (sec)",LIB,33.362,16.326,20.816
"NAS Parallel Benchmarks - Test / Class: BT.C (Mop/s)",HIB,96257.48,122720.61,24229.14
"NAS Parallel Benchmarks - Test / Class: EP.D (Mop/s)",HIB,3783.60,4935.68,2213.76
"NAS Parallel Benchmarks - Test / Class: FT.C (Mop/s)",HIB,39647.47,54846.18,21386.37
"NAS Parallel Benchmarks - Test / Class: IS.D (Mop/s)",HIB,2422.40,1752.62,915.80
"NAS Parallel Benchmarks - Test / Class: LU.C (Mop/s)",HIB,73563.13,94247.77,18807.75
"NAS Parallel Benchmarks - Test / Class: MG.C (Mop/s)",HIB,42701.83,47291.96,25661.04
"NAS Parallel Benchmarks - Test / Class: SP.C (Mop/s)",HIB,39919.71,43228.11,9716.99
"Rodinia - Test: OpenMP LavaMD (sec)",LIB,64.862,50.974,62.301
"Rodinia - Test: OpenMP HotSpot3D (sec)",LIB,84.166,88.535,
"Rodinia - Test: OpenMP Leukocyte (sec)",LIB,45.498,42.010,
"Rodinia - Test: OpenMP CFD Solver (sec)",LIB,10.025,7.368,5.983
"Rodinia - Test: OpenMP Streamcluster (sec)",LIB,6.448,6.423,14.212
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,18.39,10.73,0.1
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,648.81,1393.56,9996.56
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,142.75,73.74,1.06
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,83.99,208.47,947.59
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,142.90,78.96,1.06
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,83.91,193.45,947.86
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,1389.69,368.39,6.53
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,8.62,40.67,153.12
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,35.19,26.28,0.04
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,340.29,568.77,22391.86
"OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (FPS)",HIB,4166.39,1285.47,20.79
"OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (ms)",LIB,2.87,11.65,48.08
"OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (FPS)",HIB,576.94,225.48,2.61
"OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (ms)",LIB,20.77,66.46,382.47
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,2043.05,1512.57,0.14
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,5.86,9.90,6990.10
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,1875.28,1014.70,8.39
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,15.98,14.76,119.17
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,6605.12,4239.52,0.46
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,4.53,3.52,2186.81
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,645.74,565.34,0.15
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,18.56,26.50,6773.31
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,185.29,96.58,1.36
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,64.70,155.14,735.58
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,3650.57,2646.58,5.50
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,8.20,11.32,181.94
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,1764.21,633.76,7.36
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,6.79,23.64,135.87
"OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (FPS)",HIB,964.46,370.03,2.53
"OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (ms)",LIB,31.08,81.00,394.94
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,43607.04,29668.12,178.82
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,0.52,0.99,5.58
"OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (FPS)",HIB,761.14,390.72,2.36
"OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (ms)",LIB,39.38,76.72,423.95
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,54971.26,44049.15,136.16
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.4,0.61,7.33
"Algebraic Multi-Grid Benchmark - (Figure Of Merit)",HIB,962889833,920427767,1032893667
"Xcompact3d Incompact3d - Input: input.i3d 129 Cells Per Direction (sec)",LIB,5.87157885,5.63057327,5.61811686
"Xcompact3d Incompact3d - Input: input.i3d 193 Cells Per Direction (sec)",LIB,28.0196877,24.5721181,25.8748328
"Coremark - CoreMark Size 666 - Iterations Per Second (Iterations/Sec)",HIB,1445843.521552,1730658.449440,1259870.716902
"Stockfish - Total Time (Nodes/s)",HIB,105894457,112958788,81807706
"7-Zip Compression - Test: Compression Rating (MIPS)",HIB,271795,278973,239735
"7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,226211,247255,234046
"Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,,33.399,102.216
"Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,,333.351,409.097
"Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,,34.27,
"Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,,89.35,
"Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,,45.22,
"Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,,351.58,
"Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,,112.64,
"libavif avifenc - Encoder Speed: 0 (sec)",LIB,78.068,78.350,270.068
"libavif avifenc - Encoder Speed: 2 (sec)",LIB,41.538,41.989,167.946
"libavif avifenc - Encoder Speed: 6 (sec)",LIB,3.250,3.205,4.467
"libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,6.889,7.639,8.879
"Timed Gem5 Compilation - Time To Compile (sec)",LIB,176.767,170.930,224.414
"Timed Node.js Compilation - Time To Compile (sec)",LIB,198.394,191.706,286.201
"nginx - Connections: 500 (Reqs/sec)",HIB,187350.44,162957.75,162553.85
"nginx - Connections: 1000 (Reqs/sec)",HIB,180537.84,155609.04,158700.36
"OpenSSL - Algorithm: SHA256 (byte/s)",HIB,46211821313,50884997103,42288513973
"OpenSSL - Algorithm: SHA512 (byte/s)",HIB,14702270573,22244804183,14384917863
"OpenSSL - Algorithm: RSA4096 (sign/s)",HIB,20079.5,12973.0,2640.0
"OpenSSL - Algorithm: RSA4096 (verify/s)",HIB,493077.6,860844.6,215683.2
"OpenSSL - Algorithm: ChaCha20 (byte/s)",HIB,173980949893,180249145770,67324778360
"OpenSSL - Algorithm: AES-128-GCM (byte/s)",HIB,343095284440,234604082610,158788510970
"OpenSSL - Algorithm: AES-256-GCM (byte/s)",HIB,293328048497,216025967640,129198197600
"OpenSSL - Algorithm: ChaCha20-Poly1305 (byte/s)",HIB,123909304773,119647720337,46715126487
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400 (point/sec)",HIB,33268158,33466804,
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400 (Latency)",LIB,418.59,415.08,
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400 (point/sec)",HIB,34762565,34925899,
"Apache IoTDB - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400 (Latency)",LIB,623.89,633.58,
"Apache IoTDB - Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400 (point/sec)",HIB,34332237,34123810,
"Apache IoTDB - Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 500 - Client Number: 400 (Latency)",LIB,447.68,433.96,
"Apache IoTDB - Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400 (point/sec)",HIB,35359884,35068557,
"Apache IoTDB - Device Count: 800 - Batch Size Per Write: 100 - Sensor Count: 800 - Client Number: 400 (Latency)",LIB,682.12,709.46,
"Apache Cassandra - Test: Writes (Op/s)",HIB,228640,187169,217355
"PostgreSQL - Scaling Factor: 100 - Clients: 800 - Mode: Read Only (TPS)",HIB,,2003784,1043267
"PostgreSQL - Scaling Factor: 100 - Clients: 1000 - Mode: Read Only (TPS)",HIB,,2008186,975031
"PostgreSQL - Scaling Factor: 100 - Clients: 800 - Mode: Read Write (TPS)",HIB,,5682,4784
"PostgreSQL - Scaling Factor: 100 - Clients: 1000 - Mode: Read Write (TPS)",HIB,,5793,4776
"PostgreSQL - Scaling Factor: 100 - Clients: 800 - Mode: Read Only - Average Latency (ms)",LIB,,0.399,0.767
"PostgreSQL - Scaling Factor: 100 - Clients: 1000 - Mode: Read Only - Average Latency (ms)",LIB,,0.498,1.026
"PostgreSQL - Scaling Factor: 100 - Clients: 800 - Mode: Read Write - Average Latency (ms)",LIB,,140.916,168.191
"PostgreSQL - Scaling Factor: 100 - Clients: 1000 - Mode: Read Write - Average Latency (ms)",LIB,,172.717,210.608