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