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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2311135-PTS-TGLS547809
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"
"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
"OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,1025430,1024292,1119430
"NCNN - Target: CPU - Model: FastestDet (ms)",LIB,5.05,57.01,64.89
"NCNN - Target: CPU - Model: vision_transformer (ms)",LIB,185.96,2056.91,1952.08
"NCNN - Target: CPU - Model: regnety_400m (ms)",LIB,10.75,143.48,127.58
"NCNN - Target: CPU - Model: squeezenet_ssd (ms)",LIB,11.91,174.87,174.48
"NCNN - Target: CPU - Model: yolov4-tiny (ms)",LIB,26.69,354.78,336.66
"NCNN - Target: CPU - Model: resnet50 (ms)",LIB,23.94,372.91,349.97
"NCNN - Target: CPU - Model: alexnet (ms)",LIB,7.44,119.06,141.51
"NCNN - Target: CPU - Model: resnet18 (ms)",LIB,9.44,132.13,149.31
"NCNN - Target: CPU - Model: vgg16 (ms)",LIB,49.76,563.22,534.25
"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: efficientnet-b0 (ms)",LIB,7.17,88.38,91.44
"NCNN - Target: CPU - Model: mnasnet (ms)",LIB,3.77,59.72,63.8
"NCNN - Target: CPU - Model: shufflenet-v2 (ms)",LIB,3.45,55.66,59.68
"NCNN - Target: CPU-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.5,54.67,56.24
"NCNN - Target: CPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,4.42,76.64,71.04
"NCNN - Target: CPU - Model: mobilenet (ms)",LIB,18.82,273.8,265.17
"NCNN - Target: Vulkan GPU - Model: FastestDet (ms)",LIB,4.83,62.98,55.01
"NCNN - Target: Vulkan GPU - Model: vision_transformer (ms)",LIB,182.09,2069.02,1933.05
"NCNN - Target: Vulkan GPU - Model: regnety_400m (ms)",LIB,8.05,132.95,133.77
"NCNN - Target: Vulkan GPU - Model: squeezenet_ssd (ms)",LIB,11.9,177.2,164.33
"NCNN - Target: Vulkan GPU - Model: yolov4-tiny (ms)",LIB,26.68,347.17,341.71
"NCNN - Target: Vulkan GPU - Model: resnet50 (ms)",LIB,23.98,354.34,328.87
"NCNN - Target: Vulkan GPU - Model: alexnet (ms)",LIB,6.81,122.08,124.98
"NCNN - Target: Vulkan GPU - Model: resnet18 (ms)",LIB,8.36,130.84,134.78
"NCNN - Target: Vulkan GPU - Model: vgg16 (ms)",LIB,47.81,542.46,541.65
"NCNN - Target: Vulkan GPU - Model: googlenet (ms)",LIB,11.36,184.62,178.4
"NCNN - Target: Vulkan GPU - Model: blazeface (ms)",LIB,0.92,21.67,15.59
"NCNN - Target: Vulkan GPU - Model: efficientnet-b0 (ms)",LIB,5.61,86.3,97.95
"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-v3-v3 - Model: mobilenet-v3 (ms)",LIB,3.48,66.64,54.85
"NCNN - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 (ms)",LIB,4.39,75.3,66.65
"NCNN - Target: Vulkan GPU - Model: mobilenet (ms)",LIB,18.97,282.29,266.51
"OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,869726,870122,951381
"OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,858149,856610,943953
"OpenVKL - Benchmark: vklBenchmarkCPU ISPC (Items / Sec)",HIB,124,124,105
"BRL-CAD - VGR Performance Metric (VGR Performance Metric)",HIB,54646,54938,53711
"QMCPACK - Input: Li2_STO_ae (Execution Time - sec)",LIB,687.22,653.08,675.81
"OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,653.24,650.51,657.96
"OpenVKL - Benchmark: vklBenchmarkCPU Scalar (Items / Sec)",HIB,41,40,37
"OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,514920,514145,561556
"OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,482.8,479.06,480.7
"OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,436532,438395,476659
"OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,429631,429276,470269
"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
"VVenC - Video Input: Bosphorus 4K - Video Preset: Fast (FPS)",HIB,1.738,1.733,1.679
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,26.42,26.43,25.88
"FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,26.42,26.40,25.93
"FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,12.63,12.69,12.76
"OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,260252,261073,285007
"FFmpeg - Encoder: libx264 - Scenario: Upload (FPS)",HIB,13.29,13.26,13.11
"OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,245.14,243.36,241.64
"OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,221087,222412,242527
"OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,217399,218393,239831
"QMCPACK - Input: O_ae_pyscf_UHF (Execution Time - sec)",LIB,222.05,222.61,239.07
"CloverLeaf - Input: clover_bm64_short (sec)",LIB,206.97,203.68,203.49
"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
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 (sec)",LIB,189.03,188.679,188.515
"Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,4.4332,4.4038,4.4308
"Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,4.1966,4.2047,4.2112
"FFmpeg - Encoder: libx264 - Scenario: Video On Demand (FPS)",HIB,49.70,50.01,49.79
"FFmpeg - Encoder: libx264 - Scenario: Platform (FPS)",HIB,50.35,51.03,49.38
"libavif avifenc - Encoder Speed: 2 (sec)",LIB,168.165,168.557,172.811
"VVenC - Video Input: Bosphorus 4K - Video Preset: Faster (FPS)",HIB,3.843,3.858,3.711
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,5.2742,5.2679,5.0433
"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
"OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,132433,132979,145066
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,1.209,1.211,1.175
"Apache Cassandra - Test: Writes (Op/s)",HIB,43984,37649,37916
"Timed FFmpeg Compilation - Time To Compile (sec)",LIB,128.964,128.753,130.586
"OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,112613,113201,123787
"OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,111136,111078,122118
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,6.1486,6.1218,5.889
"QMCPACK - Input: FeCO6_b3lyp_gms (Execution Time - sec)",LIB,110.52,110.13,141.41
"CloverLeaf - Input: clover_bm (sec)",LIB,117.10,116.20,117.62
"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: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,4.2577,4.2784,4.1156
"VVenC - Video Input: Bosphorus 1080p - Video Preset: Fast (FPS)",HIB,5.428,5.415,5.343
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,7179.51,7178.23,7176.24
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,7189.12,7178.37,7178.94
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,7128.22,7138.73,7174.36
"OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,7982,7987,8722
"OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,6768,6786,7425
"OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,6673,6704,7343
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,3701.08,3699.05,3703.5
"FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,79.05,79.50,79.15
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,3703.86,3697.25,3699.85
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3671.69,3680.74,3680.01
"QMCPACK - Input: LiH_ae_MSD (Execution Time - sec)",LIB,83.217,83.167,87.017
"OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,26473,26522,33836
"QMCPACK - Input: H4_ae (Execution Time - sec)",LIB,76.19,69.78,75.96
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,3600.29,3719.15,3922.05
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,1.11,1.07,1.01
"DaCapo Benchmark - Java Test: Apache Cassandra (msec)",LIB,7845,7797,7848
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,985.39,1059.61,1061.06
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,4.05,3.75,3.75
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,287.28,312.41,312.33
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,13.9,12.79,12.79
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,344.94,370.73,372.34
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,11.59,10.78,10.72
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,346.37,369.62,370.61
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,11.52,10.81,10.77
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,49.36,52.86,52.94
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,81,75.63,75.52
"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
"OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (ms)",LIB,97.39,103.02,103.24
"OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (FPS)",HIB,41.06,38.82,38.72
"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: Handwritten English Recognition FP16 - Device: CPU (ms)",LIB,75.35,83.53,83.82
"OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (FPS)",HIB,53.07,47.86,47.69
"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
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,6.04,6.59,6.56
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,660.54,606.16,608.75
"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
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,37.89,41.18,41.07
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,105.49,97.09,97.33
"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
"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
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.47,0.53,0.53
"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 - Device: CPU (ms)",LIB,1.37,1.4,1.43
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,2874.25,2834.17,2763.4
"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
"QuantLib - Configuration: Multi-Threaded (MFLOPS)",HIB,13707,13689.3,13287
"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
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,590.1719,560.7205,590.3738
"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: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,292.8017,296.3991,301.4003
"Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,6.8296,6.7467,6.6347
"FFmpeg - Encoder: libx264 - Scenario: Live (FPS)",HIB,189.77,185.32,177.32
"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
"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 Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,3.9794,3.9535,3.8837
"DaCapo Benchmark - Java Test: Eclipse (msec)",LIB,14549,14537,14307
"DaCapo Benchmark - Java Test: Apache Tomcat (msec)",LIB,14326,14327,14456
"VVenC - Video Input: Bosphorus 1080p - Video Preset: Faster (FPS)",HIB,13.201,13.207,13.174
"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: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,16.4408,16.3077,16.0836
"OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,33081,33073,39043
"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
"DaCapo Benchmark - Java Test: H2 Database Engine (msec)",LIB,5250,5440,5419
"OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,31575,31507,31324
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,14.86,14.841,14.759
"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
"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
"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
"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
"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
"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
"SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p (FPS)",HIB,4.593,4.801,4.25
"Stress-NG - Test: IO_uring (Bogo Ops/s)",HIB,335053.51,350882.75,335942.42
"DaCapo Benchmark - Java Test: Apache Lucene Search Index (msec)",LIB,3397,3655,3541
"DaCapo Benchmark - Java Test: Tradebeans (msec)",LIB,7683,7183,10909
"QMCPACK - Input: simple-H2O (Execution Time - sec)",LIB,31.221,31.756,31.753
"Stress-NG - Test: MMAP (Bogo Ops/s)",HIB,69.5,69.31,36.33
"Stress-NG - Test: Cloning (Bogo Ops/s)",HIB,773.96,801.63,773.35
"Stress-NG - Test: Malloc (Bogo Ops/s)",HIB,1275453.62,1281240.89,1028677.94
"Stress-NG - Test: MEMFD (Bogo Ops/s)",HIB,151.83,163.56,155.8
"Cpuminer-Opt - Algorithm: Garlicoin (kH/s)",HIB,530.61,451.17,456.13
"Stress-NG - Test: x86_64 RdRand (Bogo Ops/s)",HIB,1190.72,1175.31,1107.03
"Stress-NG - Test: Zlib (Bogo Ops/s)",HIB,339.75,328.6,327.19
"Cpuminer-Opt - Algorithm: Quad SHA-256, Pyrite (kH/s)",HIB,8552.11,7883.39,7888.21
"Stress-NG - Test: NUMA (Bogo Ops/s)",HIB,91.38,90.4,67.68
"Stress-NG - Test: Atomic (Bogo Ops/s)",HIB,297.71,298.85,325.29
"Stress-NG - Test: Floating Point (Bogo Ops/s)",HIB,1644.27,1377.23,1350.58
"Stress-NG - Test: Function Call (Bogo Ops/s)",HIB,2533.58,2144.47,2126.84
"Stress-NG - Test: Pthread (Bogo Ops/s)",HIB,87060.44,83444.87,77712.52
"Stress-NG - Test: Hash (Bogo Ops/s)",HIB,814204.59,761130.78,808351.87
"Stress-NG - Test: Futex (Bogo Ops/s)",HIB,1556806.04,1573811.12,1409614.1
"Stress-NG - Test: SENDFILE (Bogo Ops/s)",HIB,74606.13,58965.05,60163.92
"Stress-NG - Test: Vector Floating Point (Bogo Ops/s)",HIB,11875.81,9743.95,8453.72
"Stress-NG - Test: Fused Multiply-Add (Bogo Ops/s)",HIB,4206478.3,3753786.13,4280472.18
"Stress-NG - Test: Memory Copying (Bogo Ops/s)",HIB,1450.68,1175.93,1179.3
"Stress-NG - Test: Matrix 3D Math (Bogo Ops/s)",HIB,1503.69,1497.3,1479.59
"Stress-NG - Test: Mixed Scheduler (Bogo Ops/s)",HIB,3933.3,3841.89,3666.05
"Stress-NG - Test: AVL Tree (Bogo Ops/s)",HIB,38,38.26,38.6
"Stress-NG - Test: Forking (Bogo Ops/s)",HIB,19571.06,17963.97,15226.03
"Stress-NG - Test: Crypto (Bogo Ops/s)",HIB,7870.33,7909.16,7843.28
"Stress-NG - Test: Mutex (Bogo Ops/s)",HIB,1800239.74,1732350.97,1454355.06
"Stress-NG - Test: Poll (Bogo Ops/s)",HIB,583755.41,577995.91,577081.19
"Stress-NG - Test: Pipe (Bogo Ops/s)",HIB,3286500.94,2941192.56,2989197.58
"Stress-NG - Test: Matrix Math (Bogo Ops/s)",HIB,19810.07,18411.16,16983.95
"Stress-NG - Test: CPU Cache (Bogo Ops/s)",HIB,788775.98,614301.31,541147.88
"Stress-NG - Test: System V Message Passing (Bogo Ops/s)",HIB,6382311.82,5221036.03,4574104.46
"Stress-NG - Test: Glibc Qsort Data Sorting (Bogo Ops/s)",HIB,104.16,85.03,85.43
"Stress-NG - Test: Glibc C String Functions (Bogo Ops/s)",HIB,3597888.5,3169430.98,2687720.74
"Stress-NG - Test: Context Switching (Bogo Ops/s)",HIB,1325769.49,1291162.21,1089870.73
"Stress-NG - Test: Wide Vector Math (Bogo Ops/s)",HIB,259593.94,230331.68,230559.53
"Stress-NG - Test: Socket Activity (Bogo Ops/s)",HIB,6702.46,4404.68,5819.48
"Stress-NG - Test: Vector Shuffle (Bogo Ops/s)",HIB,40150.8,34114.33,33753.34
"Stress-NG - Test: AVX-512 VNNI (Bogo Ops/s)",HIB,575521.32,467858.43,497416.91
"Stress-NG - Test: Vector Math (Bogo Ops/s)",HIB,19001.52,15774.03,15404.09
"Stress-NG - Test: Semaphores (Bogo Ops/s)",HIB,8568428.8,7131559.06,9046086.62
"Stress-NG - Test: CPU Stress (Bogo Ops/s)",HIB,8190.18,7691.29,6915.21
"Cpuminer-Opt - Algorithm: Triple SHA-256, Onecoin (kH/s)",HIB,9651.39,9651.58,9653.77
"Cpuminer-Opt - Algorithm: Blake-2 S (kH/s)",HIB,18920,23420,22910
"Cpuminer-Opt - Algorithm: LBC, LBRY Credits (kH/s)",HIB,1723.39,2080.34,1755.69
"Cpuminer-Opt - Algorithm: Skeincoin (kH/s)",HIB,3997.83,5234.04,4034.91
"Cpuminer-Opt - Algorithm: Deepcoin (kH/s)",HIB,992.85,1232.9,1185.5
"Cpuminer-Opt - Algorithm: Myriad-Groestl (kH/s)",HIB,1627.74,1337.88,1647.77
"Cpuminer-Opt - Algorithm: scrypt (kH/s)",HIB,44.52,36.67,36.39
"Cpuminer-Opt - Algorithm: Magi (kH/s)",HIB,79.32,78.74,78.68
"Cpuminer-Opt - Algorithm: Ringcoin (kH/s)",HIB,526.74,436.98,436.97
"DaCapo Benchmark - Java Test: Spring Boot (msec)",LIB,5151,5416,5444
"QuantLib - Configuration: Single-Threaded (MFLOPS)",HIB,3489.3,3488.1,3375.6
"DaCapo Benchmark - Java Test: Apache Lucene Search Engine (msec)",LIB,6558,6472,6687
"libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,22.311,22.193,22.449
"DaCapo Benchmark - Java Test: GraphChi (msec)",LIB,4418,4400,4428
"DaCapo Benchmark - Java Test: jMonkeyEngine (msec)",LIB,6914,6893,6876
"DaCapo Benchmark - Java Test: Tradesoap (msec)",LIB,2943,2939,2947
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.15486,2.22896,2.18576
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,42.983,43.3943,43.1633
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,11.3325,10.2647,9.93517
"DaCapo Benchmark - Java Test: BioJava Biological Data Framework (msec)",LIB,6163,6160,6249
"DaCapo Benchmark - Java Test: Apache Kafka (msec)",LIB,5346,5341,5351
"DaCapo Benchmark - Java Test: Jython (msec)",LIB,4755,4585,4654
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,37.702,37.903,33.441
"DaCapo Benchmark - Java Test: H2O In-Memory Platform For Machine Learning (msec)",LIB,3223,3772,3335
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,6.76989,6.76791,7.39175
"oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,21.4412,24.3748,22.2758
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1.5893,1.59378,1.5909
"SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p (FPS)",HIB,42.127,41.54,38.791
"libavif avifenc - Encoder Speed: 6 (sec)",LIB,14.727,14.834,14.951
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,42.302,42.441,43.136
"DaCapo Benchmark - Java Test: PMD Source Code Analyzer (msec)",LIB,3315,3645,3187
"DaCapo Benchmark - Java Test: Zxing 1D/2D Barcode Image Processing (msec)",LIB,3123,3195,3198
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 (sec)",LIB,10.613,9.924,9.62
"libavif avifenc - Encoder Speed: 10, Lossless (sec)",LIB,9.678,9.506,9.597
"oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,5.96832,5.92005,5.93496
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,6.08399,6.09457,6.07427
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.40204,2.44303,2.40573
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 256MB (MB/s)",HIB,4883.8,5007.6,4922.9
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 256MB (MB/s)",HIB,5086.8,5087.2,5010.3
"C-Blosc - Test: blosclz shuffle - Buffer Size: 256MB (MB/s)",HIB,5080.8,5182.4,5107.4
"DaCapo Benchmark - Java Test: Avrora AVR Simulation Framework (msec)",LIB,2554,2524,2612
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 128MB (MB/s)",HIB,6398.4,6413.8,6391.1
"DaCapo Benchmark - Java Test: Apache Xalan XSLT (msec)",LIB,1248,1438,1264
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 128MB (MB/s)",HIB,6601.2,6738.5,6470.2
"DaCapo Benchmark - Java Test: Batik SVG Toolkit (msec)",LIB,1392,1321,1362
"C-Blosc - Test: blosclz shuffle - Buffer Size: 128MB (MB/s)",HIB,6629.3,6779.3,6665.5
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,50.8812,51.0121,50.9697
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,7.88294,8.05175,7.95953
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,8.49762,8.44523,8.47369
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 64MB (MB/s)",HIB,7456.9,7472.9,7452.8
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 64MB (MB/s)",HIB,7691.6,7799.7,7839.9
"C-Blosc - Test: blosclz shuffle - Buffer Size: 64MB (MB/s)",HIB,7801.5,8005.2,7884.2
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 32MB (MB/s)",HIB,8124.8,8273.4,8221.1
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 32MB (MB/s)",HIB,8299.4,8646.1,8660
"C-Blosc - Test: blosclz shuffle - Buffer Size: 32MB (MB/s)",HIB,8499.9,8751.4,8437.5
"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: 16MB (MB/s)",HIB,9000.6,9267.8,9052
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 8MB (MB/s)",HIB,9850.2,10107.7,9885.9
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 8MB (MB/s)",HIB,9769.5,10085.2,10073.9
"C-Blosc - Test: blosclz shuffle - Buffer Size: 8MB (MB/s)",HIB,10149.8,10851.9,9898.3
"DaCapo Benchmark - Java Test: FOP Print Formatter (msec)",LIB,709,702,690
"SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p (FPS)",HIB,191.606,189.286,221.835
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,35.7172,35.7772,35.7339
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,9.87897,10.0704,10.0389
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.45216,2.44729,2.4729
"SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p (FPS)",HIB,290.542,289.778,288.155
"RabbitMQ - Scenario: Simple 2 Publishers + 4 Consumers (Messages/s)",HIB,,,
"RabbitMQ - Scenario: 200 Queues, 400 Producers, 400 Consumers (Messages/s)",HIB,,,
"RabbitMQ - Scenario: 120 Queues, 400 Producers, 400 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,,,