tgls

Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 22.04 via the Phoronix Test Suite.

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a
November 12 2023
  8 Hours, 30 Minutes
b
November 12 2023
  21 Hours, 56 Minutes
c
November 13 2023
  21 Hours, 46 Minutes
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  17 Hours, 24 Minutes

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tgls Intel Core i7-1185G7 testing with a Dell 0DXP1F (3.7.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 22.04 via the Phoronix Test Suite. ,,"a","b","c" Processor,,Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads),Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads),Intel Core i7-1185G7 @ 4.80GHz (4 Cores / 8 Threads) Motherboard,,Dell 0DXP1F (3.7.0 BIOS),Dell 0DXP1F (3.7.0 BIOS),Dell 0DXP1F (3.7.0 BIOS) Chipset,,Intel Tiger Lake-LP,Intel Tiger Lake-LP,Intel Tiger Lake-LP Memory,,16GB,16GB,16GB Disk,,Micron 2300 NVMe 512GB,Micron 2300 NVMe 512GB,Micron 2300 NVMe 512GB Graphics,,Intel Xe TGL GT2 15GB (1350MHz),Intel Xe TGL GT2 15GB (1350MHz),Intel Xe TGL GT2 15GB (1350MHz) Audio,,Realtek ALC289,Realtek ALC289,Realtek ALC289 Network,,Intel Wi-Fi 6 AX201,Intel Wi-Fi 6 AX201,Intel Wi-Fi 6 AX201 OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04 Kernel,,5.19.0-46-generic (x86_64),5.19.0-46-generic (x86_64),6.2.0-36-generic (x86_64) Desktop,,GNOME Shell 42.2,GNOME Shell 42.2,GNOME Shell 42.2 Display Server,,X Server + Wayland,X Server + Wayland,X Server + Wayland OpenGL,,4.6 Mesa 22.0.1,4.6 Mesa 22.0.1,4.6 Mesa 22.0.1 OpenCL,,OpenCL 3.0,OpenCL 3.0,OpenCL 3.0 Vulkan,,1.3.204,1.3.204,1.3.204 Compiler,,GCC 11.4.0,GCC 11.4.0,GCC 11.4.0 File-System,,ext4,ext4,ext4 Screen Resolution,,1920x1200,1920x1200,1920x1200 ,,"a","b","c" "NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,0.92,21.67,15.59 "NCNN - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.48,66.64,54.85 "NCNN - Target: CPU - Model: alexnet (ms)",LIB,7.44,119.06,141.51 "NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,6.81,122.08,124.98 "NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,5.61,86.3,97.95 "NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,4.42,76.64,71.04 "NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,3.45,55.66,59.68 "NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,4.39,75.3,66.65 "NCNN - Target: CPU - Model: mnasnet (ms)",LIB,3.77,59.72,63.8 "NCNN - Target: Vulkan GPU - Model: mnasnet (ms)",LIB,3.77,62.71,63.33 "NCNN - Target: Vulkan GPU - Model: shufflenet-v2 (ms)",LIB,3.4,54.38,56.62 "NCNN - Target: Vulkan GPU - Model: regnety_400m (ms)",LIB,8.05,132.95,133.77 "NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,11.36,184.62,178.4 "NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,8.36,130.84,134.78 "NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.5,54.67,56.24 "NCNN - Target: CPU - Model: resnet18 (ms)",LIB,9.44,132.13,149.31 "NCNN - Target: CPU - Model: resnet50 (ms)",LIB,23.94,372.91,349.97 "NCNN - Target: Vulkan GPU - Model: squeezenet_ssd (ms)",LIB,11.9,177.2,164.33 "NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,18.97,282.29,266.51 "NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,23.98,354.34,328.87 "NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,11.91,174.87,174.48 "NCNN - Target: CPU - Model: mobilenet (ms)",LIB,18.82,273.8,265.17 "NCNN - Target: CPU - Model: googlenet (ms)",LIB,13.84,196.54,180.35 "NCNN - Target: CPU - Model: blazeface (ms)",LIB,1.29,13.67,17.89 "NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,10.75,143.48,127.58 "NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,26.69,354.78,336.66 "NCNN - Target: Vulkan GPU - Model: FastestDet (ms)",LIB,4.83,62.98,55.01 "NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,26.68,347.17,341.71 "NCNN - Target: CPU - Model: FastestDet (ms)",LIB,5.05,57.01,64.89 "NCNN - Target: CPU - Model: efficientnet-b0 (ms)",LIB,7.17,88.38,91.44 "NCNN - Target: Vulkan GPU - Model: vision_transformer (ms)",LIB,182.09,2069.02,1933.05 "NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,47.81,542.46,541.65 "NCNN - Target: CPU - Model: vgg16 (ms)",LIB,49.76,563.22,534.25 "NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,185.96,2056.91,1952.08 "Stress-NG - Test: MMAP (Bogo Ops/s)",HIB,69.5,69.31,36.33 "Stress-NG - Test: Socket Activity (Bogo Ops/s)",HIB,6702.46,4404.68,5819.48 "DaCapo Benchmark - Java Test: Tradebeans (msec)",LIB,7683,7183,10909 "Stress-NG - Test: CPU Cache (Bogo Ops/s)",HIB,788775.98,614301.31,541147.88 "Stress-NG - Test: Vector Floating Point (Bogo Ops/s)",HIB,11875.81,9743.95,8453.72 "Stress-NG - Test: System V Message Passing (Bogo Ops/s)",HIB,6382311.82,5221036.03,4574104.46 "Stress-NG - Test: NUMA (Bogo Ops/s)",HIB,91.38,90.4,67.68 "Stress-NG - Test: Glibc C String Functions (Bogo Ops/s)",HIB,3597888.5,3169430.98,2687720.74 "Cpuminer-Opt - Algorithm: Skeincoin (kH/s)",HIB,3997.83,5234.04,4034.91 "Stress-NG - Test: Forking (Bogo Ops/s)",HIB,19571.06,17963.97,15226.03 "QMCPACK - Input: FeCO6_b3lyp_gms (Execution Time - sec)",LIB,110.52,110.13,141.41 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,26473,26522,33836 "Stress-NG - Test: Semaphores (Bogo Ops/s)",HIB,8568428.8,7131559.06,9046086.62 "Stress-NG - Test: SENDFILE (Bogo Ops/s)",HIB,74606.13,58965.05,60163.92 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,29.051,27.9534,35.1265 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,68.7416,71.4338,56.8622 "Stress-NG - Test: Malloc (Bogo Ops/s)",HIB,1275453.62,1281240.89,1028677.94 "Cpuminer-Opt - Algorithm: Deepcoin (kH/s)",HIB,992.85,1232.9,1185.5 "Cpuminer-Opt - Algorithm: Blake-2 S (kH/s)",HIB,18920,23420,22910 "Stress-NG - Test: Mutex (Bogo Ops/s)",HIB,1800239.74,1732350.97,1454355.06 "Stress-NG - Test: Memory Copying (Bogo Ops/s)",HIB,1450.68,1175.93,1179.3 "Stress-NG - Test: Vector Math (Bogo Ops/s)",HIB,19001.52,15774.03,15404.09 "Cpuminer-Opt - Algorithm: Myriad-Groestl (kH/s)",HIB,1627.74,1337.88,1647.77 "Stress-NG - Test: AVX-512 VNNI (Bogo Ops/s)",HIB,575521.32,467858.43,497416.91 "Stress-NG - Test: Glibc Qsort Data Sorting (Bogo Ops/s)",HIB,104.16,85.03,85.43 "Cpuminer-Opt - Algorithm: scrypt (kH/s)",HIB,44.52,36.67,36.39 "Stress-NG - Test: Floating Point (Bogo Ops/s)",HIB,1644.27,1377.23,1350.58 "Stress-NG - Test: Context Switching (Bogo Ops/s)",HIB,1325769.49,1291162.21,1089870.73 "Cpuminer-Opt - Algorithm: LBC, LBRY Credits (kH/s)",HIB,1723.39,2080.34,1755.69 "Cpuminer-Opt - Algorithm: Ringcoin (kH/s)",HIB,526.74,436.98,436.97 "Stress-NG - Test: Function Call (Bogo Ops/s)",HIB,2533.58,2144.47,2126.84 "Stress-NG - Test: Vector Shuffle (Bogo Ops/s)",HIB,40150.8,34114.33,33753.34 "Stress-NG - Test: CPU Stress (Bogo Ops/s)",HIB,8190.18,7691.29,6915.21 "OpenVKL - Benchmark: vklBenchmarkCPU ISPC (Items / Sec)",HIB,124,124,105 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,33081,33073,39043 "Cpuminer-Opt - Algorithm: Garlicoin (kH/s)",HIB,530.61,451.17,456.13 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,12.139,12.66,14.2479 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,164.3389,157.5828,140.0582 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,191.606,189.286,221.835 "DaCapo Benchmark - Java Test: H2O In-Memory Platform For Machine Learning (msec)",LIB,3223,3772,3335 "Apache Cassandra - Test: Writes (Op/s)",HIB,43984,37649,37916 "Stress-NG - Test: Matrix Math (Bogo Ops/s)",HIB,19810.07,18411.16,16983.95 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,4.6989,5.0779,5.423 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,423.4998,391.9655,367.1136 "DaCapo Benchmark - Java Test: Apache Xalan XSLT (msec)",LIB,1248,1438,1264 "DaCapo Benchmark - Java Test: PMD Source Code Analyzer (msec)",LIB,3315,3645,3187 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,11.3325,10.2647,9.93517 "Stress-NG - Test: Fused Multiply-Add (Bogo Ops/s)",HIB,4206478.3,3753786.13,4280472.18 "oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,21.4412,24.3748,22.2758 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,37.702,37.903,33.441 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,4.593,4.801,4.25 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.47,0.53,0.53 "Stress-NG - Test: Wide Vector Math (Bogo Ops/s)",HIB,259593.94,230331.68,230559.53 "OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (ms)",LIB,65.4,73.4,72.42 "OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (FPS)",HIB,61.12,54.46,55.2 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,8360.99,7457.91,7460.73 "Stress-NG - Test: Pthread (Bogo Ops/s)",HIB,87060.44,83444.87,77712.52 "Stress-NG - Test: Pipe (Bogo Ops/s)",HIB,3286500.94,2941192.56,2989197.58 "Stress-NG - Test: Futex (Bogo Ops/s)",HIB,1556806.04,1573811.12,1409614.1 "OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (FPS)",HIB,53.07,47.86,47.69 "OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (ms)",LIB,75.35,83.53,83.82 "OpenVKL - Benchmark: vklBenchmarkCPU Scalar (Items / Sec)",HIB,41,40,37 "easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 (sec)",LIB,10.613,9.924,9.62 "OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,217399,218393,239831 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,858149,856610,943953 "OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,6673,6704,7343 "OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,111136,111078,122118 "OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,112613,113201,123787 "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,1.11,1.07,1.01 "OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,6768,6786,7425 "OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,221087,222412,242527 "C-Blosc - Test: blosclz shuffle - Buffer Size: 8MB (MB/s)",HIB,10149.8,10851.9,9898.3 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,429631,429276,470269 "OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,132433,132979,145066 "OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,260252,261073,285007 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,869726,870122,951381 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,1025430,1024292,1119430 "OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,7982,7987,8722 "Stress-NG - Test: Atomic (Bogo Ops/s)",HIB,297.71,298.85,325.29 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,514920,514145,561556 "oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,6.76989,6.76791,7.39175 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,436532,438395,476659 "QMCPACK - Input: H4_ae (Execution Time - sec)",LIB,76.19,69.78,75.96 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,6.04,6.59,6.56 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,72.268,66.2808,71.468 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,27.6648,30.1633,27.9721 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,660.54,606.16,608.75 "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,3600.29,3719.15,3922.05 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,86.8994,92.6993,94.6327 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,23.0079,21.5687,21.1279 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,287.28,312.41,312.33 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,37.89,41.18,41.07 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,13.9,12.79,12.79 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,105.49,97.09,97.33 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,42.127,41.54,38.791 "Cpuminer-Opt - Algorithm: Quad SHA-256, Pyrite (kH/s)",HIB,8552.11,7883.39,7888.21 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,11.59,10.78,10.72 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,4.05,3.75,3.75 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,344.94,370.73,372.34 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,48.04,51.72,51.79 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,83.21,77.29,77.19 "Stress-NG - Test: MEMFD (Bogo Ops/s)",HIB,151.83,163.56,155.8 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,985.39,1059.61,1061.06 "QMCPACK - Input: O_ae_pyscf_UHF (Execution Time - sec)",LIB,222.05,222.61,239.07 "DaCapo Benchmark - Java Test: Apache Lucene Search Index (msec)",LIB,3397,3655,3541 "Stress-NG - Test: x86_64 RdRand (Bogo Ops/s)",HIB,1190.72,1175.31,1107.03 "Stress-NG - Test: Mixed Scheduler (Bogo Ops/s)",HIB,3933.3,3841.89,3666.05 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,81,75.63,75.52 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,49.36,52.86,52.94 "FFmpeg - Encoder: libx264 - Scenario: Live (FPS)",HIB,189.77,185.32,177.32 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,346.37,369.62,370.61 "Stress-NG - Test: Hash (Bogo Ops/s)",HIB,814204.59,761130.78,808351.87 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,11.52,10.81,10.77 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,27.41,29.13,29.26 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,145.83,137.2,136.61 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,136.2099,145.1634,136.0052 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,14.6802,13.7748,14.6976 "OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (FPS)",HIB,41.06,38.82,38.72 "OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (ms)",LIB,97.39,103.02,103.24 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,93.6543,88.4776,92.4501 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,21.3453,22.5938,21.6236 "DaCapo Benchmark - Java Test: Spring Boot (msec)",LIB,5151,5416,5444 "Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,4.9067,4.9376,4.6745 "DaCapo Benchmark - Java Test: Batik SVG Toolkit (msec)",LIB,1392,1321,1362 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,17.97,18.93,18.88 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,222.27,211.09,211.63 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,3.3887,3.5666,3.3874 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,590.1719,560.7205,590.3738 "QMCPACK - Input: Li2_STO_ae (Execution Time - sec)",LIB,687.22,653.08,675.81 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,10.38,10.91,10.86 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,384.36,366.17,368 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,31.2889,31.2656,32.7516 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,63.8512,63.8942,61.0055 "Stress-NG - Test: IO_uring (Bogo Ops/s)",HIB,335053.51,350882.75,335942.42 "QMCPACK - Input: LiH_ae_MSD (Execution Time - sec)",LIB,83.217,83.167,87.017 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,5.2742,5.2679,5.0433 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,6.1486,6.1218,5.889 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,1.37,1.4,1.43 "C-Blosc - Test: blosclz bitshuffle - Buffer Size: 32MB (MB/s)",HIB,8299.4,8646.1,8660 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,469.6783,466.2515,485.9236 "C-Blosc - Test: blosclz bitshuffle - Buffer Size: 128MB (MB/s)",HIB,6601.2,6738.5,6470.2 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,2874.25,2834.17,2763.4 "VVenC - Video Input: Bosphorus 4K - Video Preset: Faster (FPS)",HIB,3.843,3.858,3.711 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,4.2577,4.2784,4.1156 "Stress-NG - Test: Zlib (Bogo Ops/s)",HIB,339.75,328.6,327.19 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (ms)",LIB,14.73,15.29,15.17 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (FPS)",HIB,271.08,261.21,263.43 "C-Blosc - Test: blosclz shuffle - Buffer Size: 32MB (MB/s)",HIB,8499.9,8751.4,8437.5 "DaCapo Benchmark - Java Test: Jython (msec)",LIB,4755,4585,4654 "Stress-NG - Test: Cloning (Bogo Ops/s)",HIB,773.96,801.63,773.35 "DaCapo Benchmark - Java Test: H2 Database Engine (msec)",LIB,5250,5440,5419 "VVenC - Video Input: Bosphorus 4K - Video Preset: Fast (FPS)",HIB,1.738,1.733,1.679 "DaCapo Benchmark - Java Test: Avrora AVR Simulation Framework (msec)",LIB,2554,2524,2612 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.15486,2.22896,2.18576 "QuantLib - Configuration: Single-Threaded (MFLOPS)",HIB,3489.3,3488.1,3375.6 "FFmpeg - Encoder: libx264 - Scenario: Platform (FPS)",HIB,50.35,51.03,49.38 "DaCapo Benchmark - Java Test: Apache Lucene Search Engine (msec)",LIB,6558,6472,6687 "C-Blosc - Test: blosclz noshuffle - Buffer Size: 16MB (MB/s)",HIB,8558.6,8842,8780.8 "C-Blosc - Test: blosclz shuffle - Buffer Size: 16MB (MB/s)",HIB,8877.9,9133.5,8841.6 "C-Blosc - Test: blosclz bitshuffle - Buffer Size: 8MB (MB/s)",HIB,9769.5,10085.2,10073.9 "QuantLib - Configuration: Multi-Threaded (MFLOPS)",HIB,13707,13689.3,13287 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,1.209,1.211,1.175 "C-Blosc - Test: blosclz bitshuffle - Buffer Size: 16MB (MB/s)",HIB,9000.6,9267.8,9052 "libavif avifenc - Encoder Speed: 0 (sec)",LIB,381.267,383.211,392.474 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,6.8296,6.7467,6.6347 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,292.8017,296.3991,301.4003 "libavif avifenc - Encoder Speed: 2 (sec)",LIB,168.165,168.557,172.811 "DaCapo Benchmark - Java Test: FOP Print Formatter (msec)",LIB,709,702,690 "C-Blosc - Test: blosclz noshuffle - Buffer Size: 8MB (MB/s)",HIB,9850.2,10107.7,9885.9 "C-Blosc - Test: blosclz shuffle - Buffer Size: 64MB (MB/s)",HIB,7801.5,8005.2,7884.2 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,501.8987,504.8649,514.9428 "C-Blosc - Test: blosclz noshuffle - Buffer Size: 256MB (MB/s)",HIB,4883.8,5007.6,4922.9 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,3.9794,3.9535,3.8837 "DaCapo Benchmark - Java Test: Zxing 1D/2D Barcode Image Processing (msec)",LIB,3123,3195,3198 "BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,54646,54938,53711 "C-Blosc - Test: blosclz shuffle - Buffer Size: 128MB (MB/s)",HIB,6629.3,6779.3,6665.5 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,16.4408,16.3077,16.0836 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,121.4974,122.5885,124.1804 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,7.88294,8.05175,7.95953 "FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,26.42,26.43,25.88 "C-Blosc - Test: blosclz shuffle - Buffer Size: 256MB (MB/s)",HIB,5080.8,5182.4,5107.4 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,42.302,42.441,43.136 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,9.87897,10.0704,10.0389 "C-Blosc - Test: blosclz bitshuffle - Buffer Size: 64MB (MB/s)",HIB,7691.6,7799.7,7839.9 "FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,26.42,26.40,25.93 "C-Blosc - Test: blosclz noshuffle - Buffer Size: 32MB (MB/s)",HIB,8124.8,8273.4,8221.1 "libavif avifenc - Encoder Speed: 10, Lossless (sec)",LIB,9.678,9.506,9.597 "QMCPACK - Input: simple-H2O (Execution Time - sec)",LIB,31.221,31.756,31.753 "CloverLeaf - Input: clover_bm64_short (sec)",LIB,206.97,203.68,203.49 "oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.40204,2.44303,2.40573 "DaCapo Benchmark - Java Test: Eclipse (msec)",LIB,14549,14537,14307 "Stress-NG - Test: Matrix 3D Math (Bogo Ops/s)",HIB,1503.69,1497.3,1479.59 "VVenC - Video Input: Bosphorus 1080p - Video Preset: Fast (FPS)",HIB,5.428,5.415,5.343 "Timed GCC Compilation - Time To Compile (sec)",LIB,2337.786,2342.485,2374.917 "Stress-NG - Test: AVL Tree (Bogo Ops/s)",HIB,38,38.26,38.6 "C-Blosc - Test: blosclz bitshuffle - Buffer Size: 256MB (MB/s)",HIB,5086.8,5087.2,5010.3 "libavif avifenc - Encoder Speed: 6 (sec)",LIB,14.727,14.834,14.951 "OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,245.14,243.36,241.64 "DaCapo Benchmark - Java Test: BioJava Biological Data Framework (msec)",LIB,6163,6160,6249 "Timed FFmpeg Compilation - Time To Compile (sec)",LIB,128.964,128.753,130.586 "FFmpeg - Encoder: libx264 - Scenario: Upload (FPS)",HIB,13.29,13.26,13.11 "CloverLeaf - Input: clover_bm (sec)",LIB,117.10,116.20,117.62 "Stress-NG - Test: Poll (Bogo Ops/s)",HIB,583755.41,577995.91,577081.19 "libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,22.311,22.193,22.449 "OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,653.24,650.51,657.96 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.45216,2.44729,2.4729 "FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,12.63,12.69,12.76 "Timed Gem5 Compilation - Time To Compile (sec)",LIB,1296.126,1299.277,1309.168 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,42.983,43.3943,43.1633 "DaCapo Benchmark - Java Test: Apache Tomcat (msec)",LIB,14326,14327,14456 "Stress-NG - Test: Crypto (Bogo Ops/s)",HIB,7870.33,7909.16,7843.28 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,290.542,289.778,288.155 "oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,5.96832,5.92005,5.93496 "Cpuminer-Opt - Algorithm: Magi (kH/s)",HIB,79.32,78.74,78.68 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,31575,31507,31324 "OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,482.8,479.06,480.7 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,36.725,36.7954,37.0116 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,54.411,54.3057,53.9931 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,14.86,14.841,14.759 "Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,4.4332,4.4038,4.4308 "DaCapo Benchmark - Java Test: Apache Cassandra (msec)",LIB,7845,7797,7848 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,7128.22,7138.73,7174.36 "DaCapo Benchmark - Java Test: GraphChi (msec)",LIB,4418,4400,4428 "FFmpeg - Encoder: libx264 - Scenario: Video On Demand (FPS)",HIB,49.70,50.01,49.79 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,8.49762,8.44523,8.47369 "FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,79.05,79.50,79.15 "DaCapo Benchmark - Java Test: jMonkeyEngine (msec)",LIB,6914,6893,6876 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,37.0815,37.1469,37.2447 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,53.8907,53.7706,53.6553 "C-Blosc - Test: blosclz noshuffle - Buffer Size: 128MB (MB/s)",HIB,6398.4,6413.8,6391.1 "Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,4.1966,4.2047,4.2112 "oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,6.08399,6.09457,6.07427 "oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1.5893,1.59378,1.5909 "easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 (sec)",LIB,189.03,188.679,188.515 "DaCapo Benchmark - Java Test: Tradesoap (msec)",LIB,2943,2939,2947 "C-Blosc - Test: blosclz noshuffle - Buffer Size: 64MB (MB/s)",HIB,7456.9,7472.9,7452.8 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,50.8812,51.0121,50.9697 "VVenC - Video Input: Bosphorus 1080p - Video Preset: Faster (FPS)",HIB,13.201,13.207,13.174 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3671.69,3680.74,3680.01 "DaCapo Benchmark - Java Test: Apache Kafka (msec)",LIB,5346,5341,5351 "Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,4.8695,4.8785,4.8776 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,3703.86,3697.25,3699.85 "oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,35.7172,35.7772,35.7339 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,7189.12,7178.37,7178.94 "oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,3701.08,3699.05,3703.5 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,7179.51,7178.23,7176.24 "Cpuminer-Opt - Algorithm: Triple SHA-256, Onecoin (kH/s)",HIB,9651.39,9651.58,9653.77 "Intel Open Image Denoise - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only (Images / Sec)",HIB,0.07,0.07,0.07 "Intel Open Image Denoise - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,0.15,0.15,0.15 "Intel Open Image Denoise - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,0.15,0.15,0.15 "RabbitMQ - Scenario: 200 Queues, 400 Producers, 400 Consumers (Messages/s)",HIB,,, "RabbitMQ - Scenario: 120 Queues, 400 Producers, 400 Consumers (Messages/s)",HIB,,, "RabbitMQ - Scenario: 60 Queues, 100 Producers, 100 Consumers (Messages/s)",HIB,,, "RabbitMQ - Scenario: 10 Queues, 100 Producers, 100 Consumers (Messages/s)",HIB,,, "RabbitMQ - Scenario: Simple 2 Publishers + 4 Consumers (Messages/s)",HIB,,,