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"
"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,,