icelake 2023 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 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 |===================================================================== 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 |=================================================================== 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 |================================================================== 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 |=================================================================== 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 |=================================================================== 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 |=================================================================== 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 |================================================================== 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 |============================================================== 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 |============================================================ 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 |================================================================= 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 |===========================================================