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.

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