icelake 2023

Tests for a future article. Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus ICL GT2 16GB on Ubuntu 23.04 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 2310252-NE-ICELAKE2057
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AV1 3 Tests
C/C++ Compiler Tests 2 Tests
CPU Massive 3 Tests
Creator Workloads 6 Tests
Encoding 3 Tests
HPC - High Performance Computing 3 Tests
Machine Learning 2 Tests
Multi-Core 6 Tests
Intel oneAPI 3 Tests
Server CPU Tests 3 Tests
Video Encoding 3 Tests

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October 24 2023
  5 Hours, 52 Minutes
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October 24 2023
  5 Hours, 43 Minutes
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icelake 2023 Tests for a future article. Intel Core i7-1065G7 testing with a Dell 06CDVY (1.0.9 BIOS) and Intel Iris Plus ICL GT2 16GB on Ubuntu 23.04 via the Phoronix Test Suite. a: Processor: Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Dell 06CDVY (1.0.9 BIOS), Chipset: Intel Ice Lake-LP DRAM, Memory: 16GB, Disk: Toshiba KBG40ZPZ512G NVMe 512GB, Graphics: Intel Iris Plus ICL GT2 16GB (1100MHz), Audio: Realtek ALC289, Network: Intel Ice Lake-LP PCH CNVi WiFi OS: Ubuntu 23.04, Kernel: 6.2.0-24-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.4-0ubuntu1~23.04.1, OpenCL: OpenCL 3.0, Compiler: GCC 12.3.0, File-System: ext4, Screen Resolution: 1920x1200 b: Processor: Intel Core i7-1065G7 @ 3.90GHz (4 Cores / 8 Threads), Motherboard: Dell 06CDVY (1.0.9 BIOS), Chipset: Intel Ice Lake-LP DRAM, Memory: 16GB, Disk: Toshiba KBG40ZPZ512G NVMe 512GB, Graphics: Intel Iris Plus ICL GT2 16GB (1100MHz), Audio: Realtek ALC289, Network: Intel Ice Lake-LP PCH CNVi WiFi OS: Ubuntu 23.04, Kernel: 6.2.0-24-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.4-0ubuntu1~23.04.1, OpenCL: OpenCL 3.0, Compiler: GCC 12.3.0, File-System: ext4, Screen Resolution: 1920x1200 AOM AV1 3.7 Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 34.32 |==================================================================== b . 34.37 |==================================================================== AOM AV1 3.7 Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 34.32 |================================================================== b . 35.13 |==================================================================== AOM AV1 3.7 Encoder Mode: Speed 11 Realtime - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 33.21 |==================================================================== b . 33.31 |==================================================================== AOM AV1 3.7 Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 146.87 |=================================================================== b . 147.01 |=================================================================== AOM AV1 3.7 Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 144.80 |=================================================================== b . 143.67 |================================================================== AOM AV1 3.7 Encoder Mode: Speed 11 Realtime - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 150.75 |=================================================================== b . 150.93 |=================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 Seconds < Lower Is Better a . 11.91 |==================================================================== b . 11.93 |==================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 Seconds < Lower Is Better a . 225.68 |=================================================================== b . 225.76 |=================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 Seconds < Lower Is Better a . 560.79 |=================================================================== b . 560.99 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 2.5641 |================================================================= b . 2.6409 |=================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 2.8093 |================================================================== b . 2.8357 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 3.2657 |=================================================================== b . 3.2676 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 2.9828 |================================================================== b . 3.0350 |=================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 3.6724 |================================================================ b . 3.8233 |=================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 3.2088 |================================================================= b . 3.3091 |=================================================================== FluidX3D 2.9 Test: FP32-FP32 MLUPs/s > Higher Is Better a . 257 |==================================================================== b . 264 |====================================================================== FluidX3D 2.9 Test: FP32-FP16C MLUPs/s > Higher Is Better a . 210 |====================================================================== b . 209 |====================================================================== FluidX3D 2.9 Test: FP32-FP16S MLUPs/s > Higher Is Better a . 500 |====================================================================== b . 496 |===================================================================== Intel Open Image Denoise 2.1 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.09 |============================================================== b . 0.10 |===================================================================== Intel Open Image Denoise 2.1 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.09 |============================================================== b . 0.10 |===================================================================== Intel Open Image Denoise 2.1 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.04 |======================================================= b . 0.05 |===================================================================== libavif avifenc 1.0 Encoder Speed: 0 Seconds < Lower Is Better a . 581.56 |=================================================================== b . 540.79 |============================================================== libavif avifenc 1.0 Encoder Speed: 2 Seconds < Lower Is Better a . 257.08 |=================================================================== b . 238.25 |============================================================== libavif avifenc 1.0 Encoder Speed: 6 Seconds < Lower Is Better a . 28.76 |==================================================================== b . 26.31 |============================================================== libavif avifenc 1.0 Encoder Speed: 6, Lossless Seconds < Lower Is Better a . 39.91 |==================================================================== b . 36.85 |=============================================================== libavif avifenc 1.0 Encoder Speed: 10, Lossless Seconds < Lower Is Better a . 13.14 |==================================================================== b . 12.02 |============================================================== NCNN 20230517 Target: CPU - Model: mobilenet ms < Lower Is Better a . 24.14 |==================================================================== b . 22.94 |================================================================= NCNN 20230517 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better a . 4.37 |==================================================================== b . 4.46 |===================================================================== NCNN 20230517 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better a . 3.54 |===================================================================== b . 3.54 |===================================================================== NCNN 20230517 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better a . 4.33 |===================================================================== b . 2.73 |============================================ NCNN 20230517 Target: CPU - Model: mnasnet ms < Lower Is Better a . 5.83 |===================================================================== b . 4.02 |================================================ NCNN 20230517 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better a . 10.72 |==================================================================== b . 10.23 |================================================================= NCNN 20230517 Target: CPU - Model: blazeface ms < Lower Is Better a . 1.15 |===================================================================== b . 1.05 |=============================================================== NCNN 20230517 Target: CPU - Model: googlenet ms < Lower Is Better a . 17.18 |==================================================================== b . 16.11 |================================================================ NCNN 20230517 Target: CPU - Model: vgg16 ms < Lower Is Better a . 70.08 |==================================================================== b . 65.36 |=============================================================== NCNN 20230517 Target: CPU - Model: resnet18 ms < Lower Is Better a . 12.98 |==================================================================== b . 11.81 |============================================================== NCNN 20230517 Target: CPU - Model: alexnet ms < Lower Is Better a . 10.30 |==================================================================== b . 9.61 |=============================================================== NCNN 20230517 Target: CPU - Model: resnet50 ms < Lower Is Better a . 34.19 |==================================================================== b . 31.55 |=============================================================== NCNN 20230517 Target: CPU - Model: yolov4-tiny ms < Lower Is Better a . 32.22 |==================================================================== b . 30.62 |================================================================= NCNN 20230517 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better a . 13.81 |==================================================================== b . 13.15 |================================================================= NCNN 20230517 Target: CPU - Model: regnety_400m ms < Lower Is Better a . 11.97 |==================================================================== b . 11.26 |================================================================ NCNN 20230517 Target: CPU - Model: vision_transformer ms < Lower Is Better a . 267.05 |=================================================================== b . 254.37 |================================================================ NCNN 20230517 Target: CPU - Model: FastestDet ms < Lower Is Better a . 5.15 |==================================================================== b . 5.25 |===================================================================== NCNN 20230517 Target: Vulkan GPU - Model: mobilenet ms < Lower Is Better a . 24.15 |==================================================================== b . 22.83 |================================================================ NCNN 20230517 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better a . 4.35 |=================================================================== b . 4.47 |===================================================================== NCNN 20230517 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better a . 3.54 |===================================================================== b . 3.48 |==================================================================== NCNN 20230517 Target: Vulkan GPU - Model: shufflenet-v2 ms < Lower Is Better a . 2.71 |=================================================================== b . 2.79 |===================================================================== NCNN 20230517 Target: Vulkan GPU - Model: mnasnet ms < Lower Is Better a . 5.24 |===================================================================== b . 3.60 |=============================================== NCNN 20230517 Target: Vulkan GPU - Model: efficientnet-b0 ms < Lower Is Better a . 10.78 |==================================================================== b . 10.14 |================================================================ NCNN 20230517 Target: Vulkan GPU - Model: blazeface ms < Lower Is Better a . 1.17 |===================================================================== b . 1.08 |================================================================ NCNN 20230517 Target: Vulkan GPU - Model: googlenet ms < Lower Is Better a . 17.19 |==================================================================== b . 16.13 |================================================================ NCNN 20230517 Target: Vulkan GPU - Model: vgg16 ms < Lower Is Better a . 70.21 |==================================================================== b . 65.22 |=============================================================== NCNN 20230517 Target: Vulkan GPU - Model: resnet18 ms < Lower Is Better a . 13.06 |==================================================================== b . 11.79 |============================================================= NCNN 20230517 Target: Vulkan GPU - Model: alexnet ms < Lower Is Better a . 10.38 |==================================================================== b . 9.57 |=============================================================== NCNN 20230517 Target: Vulkan GPU - Model: resnet50 ms < Lower Is Better a . 34.28 |==================================================================== b . 32.25 |================================================================ NCNN 20230517 Target: Vulkan GPU - Model: yolov4-tiny ms < Lower Is Better a . 32.20 |==================================================================== b . 30.66 |================================================================= NCNN 20230517 Target: Vulkan GPU - Model: squeezenet_ssd ms < Lower Is Better a . 13.89 |==================================================================== b . 13.12 |================================================================ NCNN 20230517 Target: Vulkan GPU - Model: regnety_400m ms < Lower Is Better a . 11.95 |==================================================================== b . 11.33 |================================================================ NCNN 20230517 Target: Vulkan GPU - Model: vision_transformer ms < Lower Is Better a . 268.47 |=================================================================== b . 251.88 |=============================================================== NCNN 20230517 Target: Vulkan GPU - Model: FastestDet ms < Lower Is Better a . 5.64 |===================================================================== b . 4.84 |=========================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 13.39 |==================================================================== b . 10.73 |====================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 9.05715 |================================================================== b . 8.04914 |=========================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 6.00177 |================================================================== b . 4.91146 |====================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3.81175 |================================================================== b . 3.04390 |===================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.3 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 13.13 |==================================================================== b . 13.13 |==================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 21.44 |==================================================================== b . 12.93 |========================================= oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 15.18 |==================================================================== b . 15.08 |==================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 17.72 |==================================================================== b . 15.46 |=========================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 9.48511 |================================================================== b . 8.47414 |=========================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 8.16222 |================================================================== b . 8.14900 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 14396.7 |================================================================== b . 12976.6 |=========================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 7400.64 |================================================================== b . 6701.80 |============================================================ oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 14373.9 |================================================================== b . 13583.8 |============================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 7378.40 |================================================================== b . 6648.27 |=========================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 14376.4 |================================================================== b . 12945.5 |=========================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 7398.63 |================================================================== b . 6677.03 |============================================================ OpenRadioss 2023.09.15 Model: Bumper Beam Seconds < Lower Is Better a . 512.20 |================================================================== b . 516.66 |=================================================================== OpenRadioss 2023.09.15 Model: Chrysler Neon 1M Seconds < Lower Is Better a . 2917.08 |================================================================= b . 2947.38 |================================================================== OpenRadioss 2023.09.15 Model: Cell Phone Drop Test Seconds < Lower Is Better a . 337.47 |=================================================================== b . 338.36 |=================================================================== OpenRadioss 2023.09.15 Model: Bird Strike on Windshield Seconds < Lower Is Better a . 921.19 |================================================================= b . 953.64 |=================================================================== OpenRadioss 2023.09.15 Model: Rubber O-Ring Seal Installation Seconds < Lower Is Better a . 693.04 |=================================================================== b . 694.01 |=================================================================== OpenRadioss 2023.09.15 Model: INIVOL and Fluid Structure Interaction Drop Container Seconds < Lower Is Better a . 1818.21 |================================================================== b . 1824.13 |================================================================== QuantLib 1.32 Configuration: Multi-Threaded MFLOPS > Higher Is Better a . 7472.8 |=================================================================== b . 7336.6 |================================================================== QuantLib 1.32 Configuration: Single-Threaded MFLOPS > Higher Is Better a . 2898.3 |=================================================================== b . 2894.4 |=================================================================== Stress-NG 0.16.04 Test: Cloning Bogo Ops/s > Higher Is Better a . 641.54 |============================================================= b . 702.93 |=================================================================== Stress-NG 0.16.04 Test: AVX-512 VNNI Stress-NG 0.16.04 Test: Vector Shuffle Bogo Ops/s > Higher Is Better a . 2156.51 |============================================================== b . 2306.11 |================================================================== Stress-NG 0.16.04 Test: Wide Vector Math Bogo Ops/s > Higher Is Better a . 88229.80 |=========================================================== b . 96693.23 |================================================================= SVT-AV1 1.7 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 0.727 |================================================================ b . 0.769 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 9.095 |============================================================== b . 9.974 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 12 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 27.94 |============================================================ b . 31.48 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 13 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 30.09 |=============================================================== b . 32.58 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 2.726 |============================================================== b . 2.989 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 8 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 25.29 |============================================================= b . 28.36 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 12 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 191.28 |=================================================================== b . 190.60 |=================================================================== SVT-AV1 1.7 Encoder Mode: Preset 13 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 255.40 |=================================================================== b . 252.16 |==================================================================