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.

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
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AV1 2 Tests
C++ Boost Tests 2 Tests
Timed Code Compilation 4 Tests
C/C++ Compiler Tests 7 Tests
Compression Tests 2 Tests
CPU Massive 12 Tests
Creator Workloads 14 Tests
Cryptocurrency Benchmarks, CPU Mining Tests 2 Tests
Cryptography 3 Tests
Encoding 4 Tests
HPC - High Performance Computing 11 Tests
Imaging 6 Tests
Common Kernel Benchmarks 2 Tests
Machine Learning 7 Tests
Multi-Core 14 Tests
Intel oneAPI 2 Tests
OpenMPI Tests 3 Tests
Programmer / Developer System Benchmarks 5 Tests
Python Tests 8 Tests
Renderers 2 Tests
Server 2 Tests
Server CPU Tests 7 Tests
Single-Threaded 2 Tests
Video Encoding 3 Tests
Common Workstation Benchmarks 2 Tests

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EPYC 7F32
November 20 2022
  6 Hours, 7 Minutes
AMD EPYC 7F32
November 20 2022
  6 Hours, 34 Minutes
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  6 Hours, 20 Minutes
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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" "Unpacking The Linux Kernel - linux-5.19.tar.xz (sec)",LIB,7.832,7.814 "C-Blosc - Test: blosclz shuffle (MB/s)",HIB,15057.9,15048.7 "C-Blosc - Test: blosclz bitshuffle (MB/s)",HIB,5662.8,5399.4 "miniBUDE - Implementation: OpenMP - Input Deck: BM1 (GFInst/s)",HIB,270.67,269.522 "miniBUDE - Implementation: OpenMP - Input Deck: BM1 (Billion Interactions/s)",HIB,10.827,10.781 "miniBUDE - Implementation: OpenMP - Input Deck: BM2 (GFInst/s)",HIB,271.092,270.067 "miniBUDE - Implementation: OpenMP - Input Deck: BM2 (Billion Interactions/s)",HIB,10.844,10.803 "SMHasher - Hash: wyhash (MiB/sec)",HIB,21044.04,21040.94 "SMHasher - Hash: wyhash (cycles/hash)",LIB,28.387,28.387 "SMHasher - Hash: SHA3-256 (MiB/sec)",HIB,136.17,136.22 "SMHasher - Hash: SHA3-256 (cycles/hash)",LIB,2843.5,2848.539 "SMHasher - Hash: Spooky32 (MiB/sec)",HIB,13214.7,13216.41 "SMHasher - Hash: Spooky32 (cycles/hash)",LIB,56.219,55.921 "SMHasher - Hash: fasthash32 (MiB/sec)",HIB,6027.75,6027.73 "SMHasher - Hash: fasthash32 (cycles/hash)",LIB,40.676,40.684 "SMHasher - Hash: FarmHash128 (MiB/sec)",HIB,14311.97,14312.8 "SMHasher - Hash: FarmHash128 (cycles/hash)",LIB,70.29,70.29 "SMHasher - Hash: t1ha2_atonce (MiB/sec)",HIB,14595.36,14583.4 "SMHasher - Hash: t1ha2_atonce (cycles/hash)",LIB,38.503,38.503 "SMHasher - Hash: FarmHash32 x86_64 AVX (MiB/sec)",HIB,24494.95,24384.85 "SMHasher - Hash: FarmHash32 x86_64 AVX (cycles/hash)",LIB,47.677,47.677 "SMHasher - Hash: t1ha0_aes_avx2 x86_64 (MiB/sec)",HIB,59489.5,59287.09 "SMHasher - Hash: t1ha0_aes_avx2 x86_64 (cycles/hash)",LIB,37.774,37.774 "SMHasher - Hash: MeowHash x86_64 AES-NI (MiB/sec)",HIB,34313.46,34206.07 "SMHasher - Hash: MeowHash x86_64 AES-NI (cycles/hash)",LIB,63.122,63.073 "nekRS - Input: TurboPipe Periodic (FLOP/s)",HIB,, "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 "Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,7090,7304 "Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,7488.2,7636.1 "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 "srsRAN - Test: OFDM_Test (Samples / Second)",HIB,115600000,116100000 "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 MIMO 64-QAM (UE Mb/s)",HIB,133.3,133.4 "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 SISO 64-QAM (UE Mb/s)",HIB,144.6,144.4 "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 MIMO 256-QAM (UE Mb/s)",HIB,143.3,143.3 "srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM (eNb Mb/s)",HIB,353.7,354 "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 (eNb Mb/s)",HIB,95.1,95.3 "srsRAN - Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM (UE Mb/s)",HIB,53.5,53.6 "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 "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 "7-Zip Compression - Test: Compression Rating (MIPS)",HIB,73076,74973 "7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,58662,58704 "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 "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,, "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: libx264 - Scenario: Live (FPS)",HIB,177.00,179.34 "FFmpeg - Encoder: libx265 - Scenario: Live (sec)",LIB,68.46,68.15 "FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,73.77,74.10 "FFmpeg - Encoder: libx264 - Scenario: Upload (sec)",LIB,227.67,228.158210067 "FFmpeg - Encoder: libx264 - Scenario: Upload (FPS)",HIB,11.09,11.07 "FFmpeg - Encoder: libx265 - Scenario: Upload (sec)",LIB,176.3322066,175.58 "FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,14.32,14.38 "FFmpeg - Encoder: libx264 - Scenario: Platform (sec)",LIB,180.15190048,179.76 "FFmpeg - Encoder: libx264 - Scenario: Platform (FPS)",HIB,42.05,42.14 "FFmpeg - Encoder: libx265 - Scenario: Platform (sec)",LIB,253.47,252.19 "FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,29.88,30.04 "FFmpeg - Encoder: libx264 - Scenario: Video On Demand (sec)",LIB,180.64,180.54 "FFmpeg - Encoder: libx264 - Scenario: Video On Demand (FPS)",HIB,41.93,41.96 "FFmpeg - Encoder: libx265 - Scenario: Video On Demand (sec)",LIB,253.56,252.74 "FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,29.88,29.97 "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 "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: Asynchronous Multi-Stream (ms/batch)",LIB,,619.198 "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 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 (items/sec)",HIB,,22.5985 "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 (items/sec)",HIB,,13.1116 "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 (items/sec)",HIB,,36.801 "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 (items/sec)",HIB,,26.9827 "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 (items/sec)",HIB,,70.0202 "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 (items/sec)",HIB,,50.8038 "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 (items/sec)",HIB,,49.9119 "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 (items/sec)",HIB,,36.759 "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 (items/sec)",HIB,,25.2198 "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 (items/sec)",HIB,,18.221 "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 (items/sec)",HIB,,6.3581 "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 (items/sec)",HIB,,5.3593 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,186.5811 "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 "spaCy - Model: en_core_web_lg (tokens/sec)",HIB,,11288 "spaCy - Model: en_core_web_trf (tokens/sec)",HIB,,618 "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 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,,149.11 "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,,2.03 "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,,1957.78 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,,1.55 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,,2554.02 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,,1.53 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,,2583.15 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,,162.3 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,,24.63 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,,2.71 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,,1468.22 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,,219.4 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,,18.22 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,,212.74 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,,18.79 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,,24 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,,166.48 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,,267.05 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,,29.95 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,,224.93 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,,17.77 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,,5762.94 "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 (FPS)",HIB,,6432.39 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,,1.24 "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,, "Natron - Input: Spaceship (FPS)",HIB,,2.1 "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 "BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,,124747