AMD EPYC 7F32 8-Core testing with a ASRockRack EPYCD8 (P2.40 BIOS) and ASPEED on Debian 11 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 2211207-NE-EPTC7F32776
eptc-7f32
AMD EPYC 7F32 8-Core testing with a ASRockRack EPYCD8 (P2.40 BIOS) and ASPEED on Debian 11 via the Phoronix Test Suite.
,,"EPYC 7F32","AMD EPYC 7F32"
Processor,,AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads),AMD EPYC 7F32 8-Core @ 3.70GHz (8 Cores / 16 Threads)
Motherboard,,ASRockRack EPYCD8 (P2.40 BIOS),ASRockRack EPYCD8 (P2.40 BIOS)
Chipset,,AMD Starship/Matisse,AMD Starship/Matisse
Memory,,28GB,28GB
Disk,,Samsung SSD 970 EVO Plus 250GB,Samsung SSD 970 EVO Plus 250GB
Graphics,,ASPEED,ASPEED
Network,,2 x Intel I350,2 x Intel I350
OS,,Debian 11,Debian 11
Kernel,,5.10.0-10-amd64 (x86_64),5.10.0-10-amd64 (x86_64)
Desktop,,GNOME Shell 3.38.6,GNOME Shell 3.38.6
Display Server,,X Server,X Server
Compiler,,GCC 10.2.1 20210110,GCC 10.2.1 20210110
File-System,,ext4,ext4
Screen Resolution,,1024x768,1024x768
,,"EPYC 7F32","AMD EPYC 7F32"
"miniBUDE - Implementation: OpenMP - Input Deck: BM1 (Billion Interactions/s)",HIB,10.827,10.781
"miniBUDE - Implementation: OpenMP - Input Deck: BM2 (Billion Interactions/s)",HIB,10.844,10.803
"Stress-NG - Test: MMAP (Bogo Ops/s)",HIB,,141.82
"Stress-NG - Test: NUMA (Bogo Ops/s)",HIB,,236.71
"Stress-NG - Test: Futex (Bogo Ops/s)",HIB,,2310980.46
"Stress-NG - Test: MEMFD (Bogo Ops/s)",HIB,,371.54
"Stress-NG - Test: Mutex (Bogo Ops/s)",HIB,,5679683.1
"Stress-NG - Test: Atomic (Bogo Ops/s)",HIB,,392425.59
"Stress-NG - Test: Crypto (Bogo Ops/s)",HIB,,13693.66
"Stress-NG - Test: Malloc (Bogo Ops/s)",HIB,,8923251.96
"Stress-NG - Test: Forking (Bogo Ops/s)",HIB,,22867.22
"Stress-NG - Test: IO_uring (Bogo Ops/s)",HIB,,4364.73
"Stress-NG - Test: SENDFILE (Bogo Ops/s)",HIB,,150426.21
"Stress-NG - Test: CPU Cache (Bogo Ops/s)",HIB,,85.33
"Stress-NG - Test: CPU Stress (Bogo Ops/s)",HIB,,18122.93
"Stress-NG - Test: Semaphores (Bogo Ops/s)",HIB,,1194194.95
"Stress-NG - Test: Matrix Math (Bogo Ops/s)",HIB,,35043.73
"Stress-NG - Test: Vector Math (Bogo Ops/s)",HIB,,39578.06
"Stress-NG - Test: Memory Copying (Bogo Ops/s)",HIB,,1918.98
"Stress-NG - Test: Socket Activity (Bogo Ops/s)",HIB,,5664.93
"Stress-NG - Test: Context Switching (Bogo Ops/s)",HIB,,5247399
"Stress-NG - Test: Glibc C String Functions (Bogo Ops/s)",HIB,,1327261.3
"Stress-NG - Test: Glibc Qsort Data Sorting (Bogo Ops/s)",HIB,,134.03
"Stress-NG - Test: System V Message Passing (Bogo Ops/s)",HIB,,3150570.51
"srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM (eNb Mb/s)",HIB,328.5,327.5
"srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM (eNb Mb/s)",HIB,328.3,329.5
"srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM (eNb Mb/s)",HIB,353.7,355.1
"srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM (eNb Mb/s)",HIB,353.7,354
"srsRAN - Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM (eNb Mb/s)",HIB,95.1,95.3
"nekRS - Input: TurboPipe Periodic (FLOP/s)",HIB,,
"FFmpeg - Encoder: libx264 - Scenario: Live (FPS)",HIB,177.00,179.34
"FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,73.77,74.10
"FFmpeg - Encoder: libx264 - Scenario: Upload (FPS)",HIB,11.09,11.07
"FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,14.32,14.38
"FFmpeg - Encoder: libx264 - Scenario: Platform (FPS)",HIB,42.05,42.14
"FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,29.88,30.04
"FFmpeg - Encoder: libx264 - Scenario: Video On Demand (FPS)",HIB,41.93,41.96
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,29.88,29.97
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,,2.03
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,,1.55
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,,1.53
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,,162.3
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,,2.71
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,,219.4
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,,212.74
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,,24
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,,267.05
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,,224.93
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,,5762.94
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,,6432.39
"Natron - Input: Spaceship (FPS)",HIB,,2.1
"AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,0.19,0.19
"AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,5.56,5.67
"AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K (FPS)",HIB,20.97,21.44
"AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K (FPS)",HIB,9.74,9.89
"AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K (FPS)",HIB,30.22,30.97
"AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K (FPS)",HIB,41.56,42.81
"AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K (FPS)",HIB,42.08,43.34
"AOM AV1 - Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,0.54,0.54
"AOM AV1 - Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,12.26,12.51
"AOM AV1 - Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p (FPS)",HIB,43.34,42.43
"AOM AV1 - Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p (FPS)",HIB,28.29,28.46
"AOM AV1 - Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p (FPS)",HIB,75.1,76.92
"AOM AV1 - Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p (FPS)",HIB,97.35,100.17
"AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p (FPS)",HIB,107.35,102.07
"miniBUDE - Implementation: OpenMP - Input Deck: BM1 (GFInst/s)",HIB,270.67,269.522
"miniBUDE - Implementation: OpenMP - Input Deck: BM2 (GFInst/s)",HIB,271.092,270.067
"Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,7090,7304
"Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,7488.2,7636.1
"TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,53.09,
"TensorFlow - Device: CPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,65.36,
"TensorFlow - Device: CPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,74.8,
"TensorFlow - Device: CPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,82.48,
"TensorFlow - Device: CPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,83.98,
"TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,32.89,
"TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,9.98,
"TensorFlow - Device: CPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,32.58,
"TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,10.22,
"TensorFlow - Device: CPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,32.75,
"TensorFlow - Device: CPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,11.08,
"TensorFlow - Device: CPU - Batch Size: 256 - Model: GoogLeNet (images/sec)",HIB,34.99,
"TensorFlow - Device: CPU - Batch Size: 256 - Model: ResNet-50 (images/sec)",HIB,12.67,
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,6.4357
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,,5.3725
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,22.5985
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (items/sec)",HIB,,13.1116
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,36.801
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,,26.9827
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,70.0202
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,,50.8038
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,49.9119
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,,36.759
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,25.2198
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (items/sec)",HIB,,18.221
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,6.3581
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,,5.3593
"GraphicsMagick - Operation: Swirl (Iterations/min)",HIB,444,443
"GraphicsMagick - Operation: Rotate (Iterations/min)",HIB,739,739
"GraphicsMagick - Operation: Sharpen (Iterations/min)",HIB,129,130
"GraphicsMagick - Operation: Enhanced (Iterations/min)",HIB,205,206
"GraphicsMagick - Operation: Resizing (Iterations/min)",HIB,1028,1046
"GraphicsMagick - Operation: Noise-Gaussian (Iterations/min)",HIB,271,271
"GraphicsMagick - Operation: HWB Color Space (Iterations/min)",HIB,1184,1195
"Cpuminer-Opt - Algorithm: Magi (kH/s)",HIB,413.8,423.63
"Cpuminer-Opt - Algorithm: x25x (kH/s)",HIB,401.99,387.05
"Cpuminer-Opt - Algorithm: scrypt (kH/s)",HIB,145.88,146.09
"Cpuminer-Opt - Algorithm: Deepcoin (kH/s)",HIB,7494.5,7487.49
"Cpuminer-Opt - Algorithm: Ringcoin (kH/s)",HIB,1566.83,1612.04
"Cpuminer-Opt - Algorithm: Blake-2 S (kH/s)",HIB,349500,348760
"Cpuminer-Opt - Algorithm: Garlicoin (kH/s)",HIB,2139.28,2123.04
"Cpuminer-Opt - Algorithm: Skeincoin (kH/s)",HIB,68290,68130
"Cpuminer-Opt - Algorithm: Myriad-Groestl (kH/s)",HIB,12640,12640
"Cpuminer-Opt - Algorithm: LBC, LBRY Credits (kH/s)",HIB,20140,20260
"Cpuminer-Opt - Algorithm: Quad SHA-256, Pyrite (kH/s)",HIB,66230,66230
"Cpuminer-Opt - Algorithm: Triple SHA-256, Onecoin (kH/s)",HIB,132280,132340
"C-Blosc - Test: blosclz shuffle (MB/s)",HIB,15057.9,15048.7
"C-Blosc - Test: blosclz bitshuffle (MB/s)",HIB,5662.8,5399.4
"SMHasher - Hash: wyhash (MiB/sec)",HIB,21044.04,21040.94
"SMHasher - Hash: SHA3-256 (MiB/sec)",HIB,136.17,136.22
"SMHasher - Hash: Spooky32 (MiB/sec)",HIB,13214.7,13216.41
"SMHasher - Hash: fasthash32 (MiB/sec)",HIB,6027.75,6027.73
"SMHasher - Hash: FarmHash128 (MiB/sec)",HIB,14311.97,14312.8
"SMHasher - Hash: t1ha2_atonce (MiB/sec)",HIB,14595.36,14583.4
"SMHasher - Hash: FarmHash32 x86_64 AVX (MiB/sec)",HIB,24494.95,24384.85
"SMHasher - Hash: t1ha0_aes_avx2 x86_64 (MiB/sec)",HIB,59489.5,59287.09
"SMHasher - Hash: MeowHash x86_64 AES-NI (MiB/sec)",HIB,34313.46,34206.07
"7-Zip Compression - Test: Compression Rating (MIPS)",HIB,73076,74973
"7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,58662,58704
"JPEG XL libjxl - Input: PNG - Quality: 80 (MP/s)",HIB,8.44,8.71
"JPEG XL libjxl - Input: PNG - Quality: 90 (MP/s)",HIB,8.26,8.54
"JPEG XL libjxl - Input: JPEG - Quality: 80 (MP/s)",HIB,8.15,8.43
"JPEG XL libjxl - Input: JPEG - Quality: 90 (MP/s)",HIB,8.03,8.25
"JPEG XL libjxl - Input: PNG - Quality: 100 (MP/s)",HIB,0.59,0.59
"JPEG XL libjxl - Input: JPEG - Quality: 100 (MP/s)",HIB,0.58,0.58
"JPEG XL Decoding libjxl - CPU Threads: 1 (MP/s)",HIB,43.36,43.72
"JPEG XL Decoding libjxl - CPU Threads: All (MP/s)",HIB,198.76,246.32
"WebP Image Encode - Encode Settings: Default (MP/s)",HIB,15.80,15.83
"WebP Image Encode - Encode Settings: Quality 100 (MP/s)",HIB,9.90,9.93
"WebP Image Encode - Encode Settings: Quality 100, Lossless (MP/s)",HIB,1.46,1.46
"WebP Image Encode - Encode Settings: Quality 100, Highest Compression (MP/s)",HIB,3.18,3.18
"WebP Image Encode - Encode Settings: Quality 100, Lossless, Highest Compression (MP/s)",HIB,0.58,0.58
"WebP2 Image Encode - Encode Settings: Default (MP/s)",HIB,6.29,6.22
"WebP2 Image Encode - Encode Settings: Quality 75, Compression Effort 7 (MP/s)",HIB,0.12,0.12
"WebP2 Image Encode - Encode Settings: Quality 95, Compression Effort 7 (MP/s)",HIB,0.05,0.05
"WebP2 Image Encode - Encode Settings: Quality 100, Compression Effort 5 (MP/s)",HIB,3.25,3.25
"WebP2 Image Encode - Encode Settings: Quality 100, Lossless Compression (MP/s)",HIB,0.01,0.01
"Facebook RocksDB - Test: Random Read (Op/s)",HIB,,39007583
"Facebook RocksDB - Test: Update Random (Op/s)",HIB,,352075
"Facebook RocksDB - Test: Read While Writing (Op/s)",HIB,,1565360
"Facebook RocksDB - Test: Read Random Write Random (Op/s)",HIB,,1196904
"nginx - Connections: 1 (Reqs/sec)",HIB,,
"nginx - Connections: 20 (Reqs/sec)",HIB,,46605.09
"nginx - Connections: 100 (Reqs/sec)",HIB,,51130.85
"nginx - Connections: 200 (Reqs/sec)",HIB,,51950.16
"nginx - Connections: 500 (Reqs/sec)",HIB,,52055.66
"nginx - Connections: 1000 (Reqs/sec)",HIB,,50516.45
"nginx - Connections: 4000 (Reqs/sec)",HIB,,
"srsRAN - Test: OFDM_Test (Samples / Second)",HIB,115600000,116100000
"spaCy - Model: en_core_web_lg (tokens/sec)",HIB,,11288
"spaCy - Model: en_core_web_trf (tokens/sec)",HIB,,618
"srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM (UE Mb/s)",HIB,133.3,133.4
"srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM (UE Mb/s)",HIB,144.6,144.4
"srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM (UE Mb/s)",HIB,143.3,143.3
"srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM (UE Mb/s)",HIB,152.3,152.5
"srsRAN - Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM (UE Mb/s)",HIB,53.5,53.6
"BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,,124747
"SMHasher - Hash: wyhash (cycles/hash)",LIB,28.387,28.387
"SMHasher - Hash: SHA3-256 (cycles/hash)",LIB,2843.5,2848.539
"SMHasher - Hash: Spooky32 (cycles/hash)",LIB,56.219,55.921
"SMHasher - Hash: fasthash32 (cycles/hash)",LIB,40.676,40.684
"SMHasher - Hash: FarmHash128 (cycles/hash)",LIB,70.29,70.29
"SMHasher - Hash: t1ha2_atonce (cycles/hash)",LIB,38.503,38.503
"SMHasher - Hash: FarmHash32 x86_64 AVX (cycles/hash)",LIB,47.677,47.677
"SMHasher - Hash: t1ha0_aes_avx2 x86_64 (cycles/hash)",LIB,37.774,37.774
"SMHasher - Hash: MeowHash x86_64 AES-NI (cycles/hash)",LIB,63.122,63.073
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,3.48079,3.49229
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,8.67144,7.35671
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.93735,
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.790351,
"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,9.55502,8.11567
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,9.60921,9.7682
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,6.50887,6.54697
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,12.2832,
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3.93432,
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,4.85806,
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,5083.34,4813.42
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,1921.08,1891.98
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,5251.89,
"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,1881.32,
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,1.28,1.26884
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,5154.61,
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,1864.92,
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1.42225,
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,
"Mobile Neural Network - Model: nasnet (ms)",LIB,,23.653
"Mobile Neural Network - Model: mobilenetV3 (ms)",LIB,,3.37
"Mobile Neural Network - Model: squeezenetv1.1 (ms)",LIB,,5.78
"Mobile Neural Network - Model: resnet-v2-50 (ms)",LIB,,29.525
"Mobile Neural Network - Model: SqueezeNetV1.0 (ms)",LIB,,9.2
"Mobile Neural Network - Model: MobileNetV2_224 (ms)",LIB,,5.523
"Mobile Neural Network - Model: mobilenet-v1-1.0 (ms)",LIB,,4.51
"Mobile Neural Network - Model: inception-v3 (ms)",LIB,,38.689
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,,1957.78
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,,2554.02
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,,2583.15
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,,24.63
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,,1468.22
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,,18.22
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,,18.79
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,,166.48
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,,29.95
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,,17.77
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,,1.38
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,,1.24
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,619.198
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,186.1226
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,176.8383
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,76.2557
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,108.5718
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,37.0454
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,57.0733
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,19.6733
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,80.0283
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,27.1948
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,158.3902
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,54.8712
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,623.1128
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,186.5811
"Unpacking The Linux Kernel - linux-5.19.tar.xz (sec)",LIB,7.832,7.814
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,42.034545,41.187216
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,212.63009,184.11155
"OpenRadioss - Model: Bumper Beam (sec)",LIB,173.95,174.04
"OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,130.17,122.99
"OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,330.91,331.32
"OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,187.5,188.19
"OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,638.29,627.35
"libavif avifenc - Encoder Speed: 0 (sec)",LIB,169.538,169.306
"libavif avifenc - Encoder Speed: 2 (sec)",LIB,80.966,80.886
"libavif avifenc - Encoder Speed: 6 (sec)",LIB,7.893,7.856
"libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,12.434,12.293
"libavif avifenc - Encoder Speed: 10, Lossless (sec)",LIB,6.421,6.206
"Timed Node.js Compilation - Time To Compile (sec)",LIB,550.805,549.975
"Timed PHP Compilation - Time To Compile (sec)",LIB,65.041,65.201
"Timed CPython Compilation - Build Configuration: Default (sec)",LIB,19.15,19.027
"Timed CPython Compilation - Build Configuration: Released Build, PGO + LTO Optimized (sec)",LIB,337.768,338.978
"Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,45.22,46.211
"Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,22.892,21.633
"Timed Erlang/OTP Compilation - Time To Compile (sec)",LIB,120.664,118.859
"FLAC Audio Encoding - WAV To FLAC (sec)",LIB,21.343,21.276
"FFmpeg - Encoder: libx264 - Scenario: Live (sec)",LIB,28.53,28.16
"FFmpeg - Encoder: libx265 - Scenario: Live (sec)",LIB,68.46,68.15
"FFmpeg - Encoder: libx264 - Scenario: Upload (sec)",LIB,227.67,228.158210067
"FFmpeg - Encoder: libx265 - Scenario: Upload (sec)",LIB,176.3322066,175.58
"FFmpeg - Encoder: libx264 - Scenario: Platform (sec)",LIB,180.15190048,179.76
"FFmpeg - Encoder: libx265 - Scenario: Platform (sec)",LIB,253.47,252.19
"FFmpeg - Encoder: libx264 - Scenario: Video On Demand (sec)",LIB,180.64,180.54
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (sec)",LIB,253.56,252.74
"Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,,149.11
"EnCodec - Target Bandwidth: 3 kbps (sec)",LIB,,36.202
"EnCodec - Target Bandwidth: 6 kbps (sec)",LIB,,34.991
"EnCodec - Target Bandwidth: 24 kbps (sec)",LIB,,39.865
"EnCodec - Target Bandwidth: 1.5 kbps (sec)",LIB,,33.965
"Scikit-Learn - Benchmark: MNIST Dataset (sec)",LIB,,119.569
"Scikit-Learn - Benchmark: TSNE MNIST Dataset (sec)",LIB,,38.601
"Scikit-Learn - Benchmark: Sparse Random Projections, 100 Iterations (sec)",LIB,,185.087