2 x AMD EPYC 7601 32-Core testing with a Dell 02MJ3T (1.2.5 BIOS) and Matrox G200eW3 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 2211191-NE-ZEN1EPYC673
zen 1 epyc
2 x AMD EPYC 7601 32-Core testing with a Dell 02MJ3T (1.2.5 BIOS) and Matrox G200eW3 on Ubuntu 22.04 via the Phoronix Test Suite.
,,"a","b"
Processor,,2 x AMD EPYC 7601 32-Core (64 Cores / 128 Threads),2 x AMD EPYC 7601 32-Core (64 Cores / 128 Threads)
Motherboard,,Dell 02MJ3T (1.2.5 BIOS),Dell 02MJ3T (1.2.5 BIOS)
Chipset,,AMD 17h,AMD 17h
Memory,,512GB,512GB
Disk,,280GB INTEL SSDPED1D280GA + 12 x 500GB Samsung SSD 860 + 120GB INTEL SSDSCKJB120G7R,280GB INTEL SSDPED1D280GA + 12 x 500GB Samsung SSD 860 + 120GB INTEL SSDSCKJB120G7R
Graphics,,Matrox G200eW3,Matrox G200eW3
Monitor,,VE228,VE228
Network,,2 x Broadcom BCM57416 NetXtreme-E Dual-Media 10G RDMA + 2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom BCM57416 NetXtreme-E Dual-Media 10G RDMA + 2 x Broadcom NetXtreme BCM5720 PCIe
OS,,Ubuntu 22.04,Ubuntu 22.04
Kernel,,5.15.0-40-generic (x86_64),5.15.0-40-generic (x86_64)
Desktop,,GNOME Shell 42.2,GNOME Shell 42.2
Display Server,,X Server 1.21.1.3,X Server 1.21.1.3
Vulkan,,1.2.204,1.2.204
Compiler,,GCC 11.3.0,GCC 11.3.0
File-System,,ext4,ext4
Screen Resolution,,1600x1200,1600x1200
,,"a","b"
"Stress-NG - Test: x86_64 RdRand ()",,,
"miniBUDE - Implementation: OpenMP - Input Deck: BM1 (Billion Interactions/s)",HIB,27.872,27.515
"miniBUDE - Implementation: OpenMP - Input Deck: BM2 (Billion Interactions/s)",HIB,30.127,29.692
"Stress-NG - Test: MMAP (Bogo Ops/s)",HIB,2418.27,2342.6
"Stress-NG - Test: NUMA (Bogo Ops/s)",HIB,140.8,140.65
"Stress-NG - Test: Futex (Bogo Ops/s)",HIB,802471.3,796565.52
"Stress-NG - Test: MEMFD (Bogo Ops/s)",HIB,1751.42,1743.95
"Stress-NG - Test: Mutex (Bogo Ops/s)",HIB,17481256.34,17702491.79
"Stress-NG - Test: Atomic (Bogo Ops/s)",HIB,156802.93,172559.2
"Stress-NG - Test: Crypto (Bogo Ops/s)",HIB,67640.35,67622.54
"Stress-NG - Test: Malloc (Bogo Ops/s)",HIB,146984386.17,148029623.74
"Stress-NG - Test: Forking (Bogo Ops/s)",HIB,19768.12,19540.99
"Stress-NG - Test: IO_uring (Bogo Ops/s)",HIB,45731.6,45863.96
"Stress-NG - Test: SENDFILE (Bogo Ops/s)",HIB,678380.72,678714.22
"Stress-NG - Test: CPU Cache (Bogo Ops/s)",HIB,199.02,259.54
"Stress-NG - Test: CPU Stress (Bogo Ops/s)",HIB,106647.2,107074.79
"Stress-NG - Test: Semaphores (Bogo Ops/s)",HIB,7247266.69,7261328.18
"Stress-NG - Test: Matrix Math (Bogo Ops/s)",HIB,215006.68,215110.79
"Stress-NG - Test: Vector Math (Bogo Ops/s)",HIB,266411.19,266535.54
"Stress-NG - Test: Memory Copying (Bogo Ops/s)",HIB,2328.14,2485.61
"Stress-NG - Test: Socket Activity (Bogo Ops/s)",HIB,25316.76,25937.03
"Stress-NG - Test: Context Switching (Bogo Ops/s)",HIB,14423511.17,15090386.73
"Stress-NG - Test: Glibc C String Functions (Bogo Ops/s)",HIB,5250106.25,5386266.71
"Stress-NG - Test: Glibc Qsort Data Sorting (Bogo Ops/s)",HIB,673.06,667.4
"Stress-NG - Test: System V Message Passing (Bogo Ops/s)",HIB,7616183.78,7408445.43
"srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM (eNb Mb/s)",HIB,252.8,252.3
"srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM (eNb Mb/s)",HIB,257.5,256.9
"srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM (eNb Mb/s)",HIB,274.2,273
"srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM (eNb Mb/s)",HIB,279.8,279.4
"srsRAN - Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM (eNb Mb/s)",HIB,69.7,69.7
"nekRS - Input: TurboPipe Periodic (FLOP/s)",HIB,184723000000,184827000000
"FFmpeg - Encoder: libx264 - Scenario: Live (FPS)",HIB,129.99,130.30
"FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,58.22,57.01
"FFmpeg - Encoder: libx264 - Scenario: Upload (FPS)",HIB,8.03,8.01
"FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,10.45,10.50
"FFmpeg - Encoder: libx264 - Scenario: Platform (FPS)",HIB,30.42,30.18
"FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,21.24,21.27
"FFmpeg - Encoder: libx264 - Scenario: Video On Demand (FPS)",HIB,30.20,30.25
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,21.21,21.12
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,5.85,5.82
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,3.9,3.89
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,3.85,3.89
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,352.62,351.6
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,7.61,7.61
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,614.56,613.31
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,626.61,626.42
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,59.76,61.27
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,751.84,751.3
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,513.24,508.7
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,16068.58,16149.43
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,19469.8,19580.12
"Natron - Input: Spaceship (FPS)",HIB,3.5,3.6
"AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,0.21,0.21
"AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,5.59,5.56
"AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K (FPS)",HIB,16.41,15.89
"AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,8.95,8.71
"AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K (FPS)",HIB,18.51,17.14
"AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K (FPS)",HIB,21.01,21.39
"AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K (FPS)",HIB,21.95,21.83
"AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,0.6,0.59
"AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,11.06,10.84
"AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p (FPS)",HIB,33.12,33.44
"AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,24.96,24.36
"AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p (FPS)",HIB,41.79,38.47
"AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p (FPS)",HIB,48.34,42.57
"AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p (FPS)",HIB,45.43,42.01
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,1.314,1.321
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,27.818,28.06
"SVT-AV1 - Encoder Mode: Preset 10 - Input: Bosphorus 4K (FPS)",HIB,46.683,52.96
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,67.124,69.476
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,3.531,3.561
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,76.278,76.731
"SVT-AV1 - Encoder Mode: Preset 10 - Input: Bosphorus 1080p (FPS)",HIB,161.41,159.55
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,209.488,234.707
"miniBUDE - Implementation: OpenMP - Input Deck: BM1 (GFInst/s)",HIB,696.801,687.884
"miniBUDE - Implementation: OpenMP - Input Deck: BM2 (GFInst/s)",HIB,753.17,742.296
"Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,12797.7,10914.9
"Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,19243.7,19140.2
"TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,42.69,42.91
"TensorFlow - Device: CPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,48.66,48.45
"TensorFlow - Device: CPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,59.55,59.76
"TensorFlow - Device: CPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,69.6,69.33
"TensorFlow - Device: CPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,69.82,69.69
"TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,24.77,24.47
"TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,8.13,8.12
"TensorFlow - Device: CPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,29.09,28.44
"TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,9.6,9.69
"TensorFlow - Device: CPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,30.13,30.12
"TensorFlow - Device: CPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,10.11,10.17
"TensorFlow - Device: CPU - Batch Size: 256 - Model: GoogLeNet (images/sec)",HIB,30.11,29.87
"TensorFlow - Device: CPU - Batch Size: 256 - Model: ResNet-50 (images/sec)",HIB,10.92,10.86
"TensorFlow - Device: CPU - Batch Size: 512 - Model: GoogLeNet (images/sec)",HIB,30.61,30.42
"TensorFlow - Device: CPU - Batch Size: 512 - Model: ResNet-50 (images/sec)",HIB,11.24,11.32
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,22.6007,22.568
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,8.3625,8.2919
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,87.6373,87.3202
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (items/sec)",HIB,17.7786,19.1958
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,121.842,121.8565
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,39.942,40.071
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,249.2856,250.8978
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,73.5683,73.866
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,192.2873,192.6373
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,51.2365,51.6311
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,96.0986,96.5473
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (items/sec)",HIB,26.3211,26.046
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,22.6456,22.674
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,8.1225,8.2228
"GraphicsMagick - Operation: Swirl (Iterations/min)",HIB,1243,1247
"GraphicsMagick - Operation: Rotate (Iterations/min)",HIB,443,448
"GraphicsMagick - Operation: Sharpen (Iterations/min)",HIB,561,555
"GraphicsMagick - Operation: Enhanced (Iterations/min)",HIB,743,740
"GraphicsMagick - Operation: Resizing (Iterations/min)",HIB,167,135
"GraphicsMagick - Operation: Noise-Gaussian (Iterations/min)",HIB,692,619
"GraphicsMagick - Operation: HWB Color Space (Iterations/min)",HIB,1107,957
"Aircrack-ng - (k/s)",HIB,76103.367,74378.891
"Cpuminer-Opt - Algorithm: Magi (kH/s)",HIB,1711.45,1702.45
"Cpuminer-Opt - Algorithm: x25x (kH/s)",HIB,1458.5,1452.6
"Cpuminer-Opt - Algorithm: scrypt (kH/s)",HIB,496.52,499.97
"Cpuminer-Opt - Algorithm: Deepcoin (kH/s)",HIB,27510,27490
"Cpuminer-Opt - Algorithm: Ringcoin (kH/s)",HIB,18480,18440
"Cpuminer-Opt - Algorithm: Blake-2 S (kH/s)",HIB,1098730,1098280
"Cpuminer-Opt - Algorithm: Garlicoin (kH/s)",HIB,13970,14530
"Cpuminer-Opt - Algorithm: Skeincoin (kH/s)",HIB,222070,222040
"Cpuminer-Opt - Algorithm: Myriad-Groestl (kH/s)",HIB,154070,152420
"Cpuminer-Opt - Algorithm: LBC, LBRY Credits (kH/s)",HIB,56960,56960
"Cpuminer-Opt - Algorithm: Quad SHA-256, Pyrite (kH/s)",HIB,374460,374430
"Cpuminer-Opt - Algorithm: Triple SHA-256, Onecoin (kH/s)",HIB,718010,718140
"C-Blosc - Test: blosclz shuffle (MB/s)",HIB,8493.2,8534.5
"C-Blosc - Test: blosclz bitshuffle (MB/s)",HIB,5328.2,5318.7
"SMHasher - Hash: wyhash (MiB/sec)",HIB,30087.23,30062.54
"SMHasher - Hash: SHA3-256 (MiB/sec)",HIB,171.09,171.13
"SMHasher - Hash: Spooky32 (MiB/sec)",HIB,17912.16,17951.6
"SMHasher - Hash: fasthash32 (MiB/sec)",HIB,8316.13,8317.14
"SMHasher - Hash: FarmHash128 (MiB/sec)",HIB,19050.24,19028.89
"SMHasher - Hash: t1ha2_atonce (MiB/sec)",HIB,18815.25,18809.49
"SMHasher - Hash: FarmHash32 x86_64 AVX (MiB/sec)",HIB,32899.32,32884.37
"SMHasher - Hash: t1ha0_aes_avx2 x86_64 (MiB/sec)",HIB,77196.31,76443.61
"SMHasher - Hash: MeowHash x86_64 AES-NI (MiB/sec)",HIB,41424.16,41393.48
"JPEG XL libjxl - Input: PNG - Quality: 80 (MP/s)",HIB,6.37,6.38
"JPEG XL libjxl - Input: PNG - Quality: 90 (MP/s)",HIB,6.27,6.29
"JPEG XL libjxl - Input: JPEG - Quality: 80 (MP/s)",HIB,6.1,6.06
"JPEG XL libjxl - Input: JPEG - Quality: 90 (MP/s)",HIB,5.91,5.94
"JPEG XL libjxl - Input: PNG - Quality: 100 (MP/s)",HIB,0.4,0.4
"JPEG XL libjxl - Input: JPEG - Quality: 100 (MP/s)",HIB,0.4,0.4
"JPEG XL Decoding libjxl - CPU Threads: 1 (MP/s)",HIB,26.86,27.01
"JPEG XL Decoding libjxl - CPU Threads: All (MP/s)",HIB,151.09,151.66
"WebP Image Encode - Encode Settings: Default (MP/s)",HIB,12.25,12.23
"WebP Image Encode - Encode Settings: Quality 100 (MP/s)",HIB,7.73,7.71
"WebP Image Encode - Encode Settings: Quality 100, Lossless (MP/s)",HIB,1.06,1.05
"WebP Image Encode - Encode Settings: Quality 100, Highest Compression (MP/s)",HIB,2.43,2.43
"WebP Image Encode - Encode Settings: Quality 100, Lossless, Highest Compression (MP/s)",HIB,0.41,0.42
"WebP2 Image Encode - Encode Settings: Default (MP/s)",HIB,5.77,6.38
"WebP2 Image Encode - Encode Settings: Quality 75, Compression Effort 7 (MP/s)",HIB,0.38,0.37
"WebP2 Image Encode - Encode Settings: Quality 95, Compression Effort 7 (MP/s)",HIB,0.20,0.20
"WebP2 Image Encode - Encode Settings: Quality 100, Compression Effort 5 (MP/s)",HIB,7.42,7.35
"WebP2 Image Encode - Encode Settings: Quality 100, Lossless Compression (MP/s)",HIB,0.04,0.04
"ASTC Encoder - Preset: Fast (MT/s)",HIB,382.0137,376.393
"ASTC Encoder - Preset: Medium (MT/s)",HIB,151.8067,152.2417
"ASTC Encoder - Preset: Thorough (MT/s)",HIB,19.4177,19.4423
"ASTC Encoder - Preset: Exhaustive (MT/s)",HIB,2.2087,2.2093
"LAMMPS Molecular Dynamics Simulator - Model: 20k Atoms (ns/day)",HIB,24.029,23.033
"LAMMPS Molecular Dynamics Simulator - Model: Rhodopsin Protein (ns/day)",HIB,24.104,24.069
"Facebook RocksDB - Test: Random Read (Op/s)",HIB,198794977,196826975
"Facebook RocksDB - Test: Update Random (Op/s)",HIB,199394,198198
"Facebook RocksDB - Test: Read While Writing (Op/s)",HIB,5807440,6220606
"Facebook RocksDB - Test: Read Random Write Random (Op/s)",HIB,1551427,1558868
"ClickHouse - 100M Rows Web Analytics Dataset, First Run / Cold Cache (Queries/min, Geo Mean)",HIB,241.18,253.55
"ClickHouse - 100M Rows Web Analytics Dataset, Second Run (Queries/min, Geo Mean)",HIB,260.83,271.13
"ClickHouse - 100M Rows Web Analytics Dataset, Third Run (Queries/min, Geo Mean)",HIB,272.09,256.64
"nginx - Connections: 1 (Reqs/sec)",HIB,,
"nginx - Connections: 20 (Reqs/sec)",HIB,,
"nginx - Connections: 100 (Reqs/sec)",HIB,,
"nginx - Connections: 200 (Reqs/sec)",HIB,100112.06,101709.29
"nginx - Connections: 500 (Reqs/sec)",HIB,99535.87,98639.62
"nginx - Connections: 1000 (Reqs/sec)",HIB,96265.52,95346.38
"nginx - Connections: 4000 (Reqs/sec)",HIB,,
"Node.js V8 Web Tooling Benchmark - (runs/s)",HIB,7.13,7.02
"srsRAN - Test: OFDM_Test (Samples / Second)",HIB,65700000,66100000
"AI Benchmark Alpha - Device Inference Score (Score)",HIB,1245,1232
"AI Benchmark Alpha - Device Training Score (Score)",HIB,764,760
"AI Benchmark Alpha - Device AI Score (Score)",HIB,2009,1992
"spaCy - Model: en_core_web_lg (tokens/sec)",HIB,6798,6795
"spaCy - Model: en_core_web_trf (tokens/sec)",HIB,701,685
"srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM (UE Mb/s)",HIB,86.2,85.9
"srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM (UE Mb/s)",HIB,93.7,93.6
"srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM (UE Mb/s)",HIB,92,91.5
"srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM (UE Mb/s)",HIB,98.9,99
"srsRAN - Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM (UE Mb/s)",HIB,38,38.1
"BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,413004,406201
"SMHasher - Hash: wyhash (cycles/hash)",LIB,20.507,20.508
"SMHasher - Hash: SHA3-256 (cycles/hash)",LIB,2294.234,2294.164
"SMHasher - Hash: Spooky32 (cycles/hash)",LIB,40.875,40.792
"SMHasher - Hash: fasthash32 (cycles/hash)",LIB,29.558,29.586
"SMHasher - Hash: FarmHash128 (cycles/hash)",LIB,51.419,51.419
"SMHasher - Hash: t1ha2_atonce (cycles/hash)",LIB,27.774,27.774
"SMHasher - Hash: FarmHash32 x86_64 AVX (cycles/hash)",LIB,34.619,34.546
"SMHasher - Hash: t1ha0_aes_avx2 x86_64 (cycles/hash)",LIB,27.314,27.314
"SMHasher - Hash: MeowHash x86_64 AES-NI (cycles/hash)",LIB,47.356,47.348
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,5.12686,5.03993
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,20.1433,20.2831
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4.23625,3.81237
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4.52585,4.58464
"oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,
"oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,21.0326,20.0581
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,19.1966,19.1791
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,6.0371,5.6399
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,28.7725,28.7918
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4.14024,4.63109
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.51501,2.51294
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,7823,8504.29
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,5300.36,5167.81
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,7893.57,8148.11
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,5167.4,5128.18
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,9.48918,7.74858
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,8045.7,8013.88
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,5157.6,5207.64
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,29.7727,28.8968
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,
"OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer (ms)",LIB,4233,4239
"OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer (ms)",LIB,4416,4403
"OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer (ms)",LIB,5127,5130
"OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer (ms)",LIB,78125,78264
"OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,145358,145660
"OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer (ms)",LIB,80769,80340
"OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,150980,151192
"OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer (ms)",LIB,91958,92675
"OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,173492,173590
"OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer (ms)",LIB,1062,1060
"OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer (ms)",LIB,1096,1100
"OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer (ms)",LIB,1282,1277
"OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer (ms)",LIB,17188,17139
"OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,34160,34140
"OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer (ms)",LIB,17838,17792
"OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,35696,35397
"OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer (ms)",LIB,20597,20517
"OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,41292,41490
"Mobile Neural Network - Model: nasnet (ms)",LIB,42.874,40.336
"Mobile Neural Network - Model: mobilenetV3 (ms)",LIB,5.475,5.35
"Mobile Neural Network - Model: squeezenetv1.1 (ms)",LIB,10.633,10.152
"Mobile Neural Network - Model: resnet-v2-50 (ms)",LIB,50.815,47.115
"Mobile Neural Network - Model: SqueezeNetV1.0 (ms)",LIB,15.675,15.008
"Mobile Neural Network - Model: MobileNetV2_224 (ms)",LIB,9.862,9.957
"Mobile Neural Network - Model: mobilenet-v1-1.0 (ms)",LIB,7.677,7.386
"Mobile Neural Network - Model: inception-v3 (ms)",LIB,56.231,56.096
"NCNN - Target: CPU - Model: mobilenet (ms)",LIB,70.65,82.64
"NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,74.59,48.21
"NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,45.3,58.67
"NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,64,43.74
"NCNN - Target: CPU - Model: mnasnet (ms)",LIB,51.66,41.96
"NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,55.09,56.92
"NCNN - Target: CPU - Model: blazeface (ms)",LIB,42.63,31.18
"NCNN - Target: CPU - Model: googlenet (ms)",LIB,111.2,100.95
"NCNN - Target: CPU - Model: vgg16 (ms)",LIB,139.33,123.73
"NCNN - Target: CPU - Model: resnet18 (ms)",LIB,81.24,63.2
"NCNN - Target: CPU - Model: alexnet (ms)",LIB,65.6,53.71
"NCNN - Target: CPU - Model: resnet50 (ms)",LIB,178.31,110.59
"NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,75.13,78.03
"NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,100.38,94.37
"NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,286.78,208.14
"NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,319.23,298.72
"NCNN - Target: CPU - Model: FastestDet (ms)",LIB,76.99,51.75
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,5452.5,5492
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,8087.11,8150.2
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,8245.26,8119.63
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,90.64,90.91
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,4182.46,4185.2
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,52.03,52.14
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,51.03,51.04
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,533.65,520.79
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,85.05,85.09
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,62.29,62.84
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,3.94,3.92
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,3.26,3.24
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,1387.0925,1398.9258
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,119.5632,120.5776
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,362.7795,364.9851
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,56.2277,52.0728
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,261.4175,261.4233
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,25.014,24.9281
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,128.0038,127.2104
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,13.5743,13.5155
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,166.1119,165.7009
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,19.4996,19.3504
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,331.234,330.5267
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,37.9743,38.3752
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,1387.2953,1390.6109
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,123.0974,121.5902
"Unpacking The Linux Kernel - linux-5.19.tar.xz (sec)",LIB,10.559,10.649
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,34.098937,34.188105
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,61.454018,62.974805
"OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Mesh Time (sec)",LIB,167.0036,167.06876
"OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Execution Time (sec)",LIB,541.95263,542.44501
"OpenRadioss - Model: Bumper Beam (sec)",LIB,108.51,108.31
"OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,41.65,41.58
"OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,185.26,186.71
"OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,118,117.84
"OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,210.39,207.85
"libavif avifenc - Encoder Speed: 0 (sec)",LIB,136.608,136.591
"libavif avifenc - Encoder Speed: 2 (sec)",LIB,78.895,79.112
"libavif avifenc - Encoder Speed: 6 (sec)",LIB,5.268,5.268
"libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,9.994,10.085
"libavif avifenc - Encoder Speed: 10, Lossless (sec)",LIB,7.613,7.653
"Timed Node.js Compilation - Time To Compile (sec)",LIB,217.334,215.92
"Timed PHP Compilation - Time To Compile (sec)",LIB,62.123,62.178
"Timed CPython Compilation - Build Configuration: Default (sec)",LIB,22.619,22.707
"Timed CPython Compilation - Build Configuration: Released Build, PGO + LTO Optimized (sec)",LIB,399.66,400.368
"Primesieve - Length: 1e12 (sec)",LIB,4.638,4.66
"Primesieve - Length: 1e13 (sec)",LIB,56.028,56.246
"Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,21.577,21.561
"Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,11.184,10.987
"Timed Erlang/OTP Compilation - Time To Compile (sec)",LIB,124.066,124.216
"Timed Wasmer Compilation - Time To Compile (sec)",LIB,73.78,73.485
"FLAC Audio Encoding - WAV To FLAC (sec)",LIB,28.868,28.744
"FFmpeg - Encoder: libx264 - Scenario: Live (sec)",LIB,38.85,38.76
"FFmpeg - Encoder: libx265 - Scenario: Live (sec)",LIB,86.74,88.58
"FFmpeg - Encoder: libx264 - Scenario: Upload (sec)",LIB,314.58,315.290203876
"FFmpeg - Encoder: libx265 - Scenario: Upload (sec)",LIB,241.646159513,240.519283432
"FFmpeg - Encoder: libx264 - Scenario: Platform (sec)",LIB,249.00936878,250.99
"FFmpeg - Encoder: libx265 - Scenario: Platform (sec)",LIB,356.59243127,356.16
"FFmpeg - Encoder: libx264 - Scenario: Video On Demand (sec)",LIB,250.83,250.37
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (sec)",LIB,357.150956529,358.61
"Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,35.5,35.62
"Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,87.25,87.77
"Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,51.46,51.66
"Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,409.74,408.93
"Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,126.81,126.75
"EnCodec - Target Bandwidth: 3 kbps (sec)",LIB,66.471,68.291
"EnCodec - Target Bandwidth: 6 kbps (sec)",LIB,74.538,74.885
"EnCodec - Target Bandwidth: 24 kbps (sec)",LIB,78.457,81.167
"EnCodec - Target Bandwidth: 1.5 kbps (sec)",LIB,67.588,75.036