new okt Intel Xeon Silver 4216 testing with a TYAN S7100AG2NR (V4.02 BIOS) and ASPEED on Debian 12 via the Phoronix Test Suite. a: Processor: Intel Xeon Silver 4216 @ 3.20GHz (16 Cores / 32 Threads), Motherboard: TYAN S7100AG2NR (V4.02 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 46GB, Disk: 240GB Corsair Force MP500, Graphics: ASPEED, Audio: Realtek ALC892, Network: 2 x Intel I350 OS: Debian 12, Kernel: 6.1.0-11-amd64 (x86_64), Display Server: X Server, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1024x768 b: Processor: Intel Xeon Silver 4216 @ 3.20GHz (16 Cores / 32 Threads), Motherboard: TYAN S7100AG2NR (V4.02 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 46GB, Disk: 240GB Corsair Force MP500, Graphics: ASPEED, Audio: Realtek ALC892, Network: 2 x Intel I350 OS: Debian 12, Kernel: 6.1.0-11-amd64 (x86_64), Display Server: X Server, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1024x768 QuantLib 1.32 Configuration: Multi-Threaded MFLOPS > Higher Is Better a . 31381.4 |================================================================== b . 31348.2 |================================================================== QuantLib 1.32 Configuration: Single-Threaded MFLOPS > Higher Is Better a . 2056.3 |================================================================== b . 2076.5 |=================================================================== OpenRadioss 2023.09.15 Model: Bumper Beam Seconds < Lower Is Better a . 187.21 |================================================================== b . 188.77 |=================================================================== OpenRadioss 2023.09.15 Model: Chrysler Neon 1M Seconds < Lower Is Better a . 871.61 |=================================================================== b . 864.38 |================================================================== OpenRadioss 2023.09.15 Model: Cell Phone Drop Test Seconds < Lower Is Better a . 116.59 |=================================================================== b . 115.90 |=================================================================== OpenRadioss 2023.09.15 Model: Bird Strike on Windshield Seconds < Lower Is Better a . 312.50 |=================================================================== b . 311.49 |=================================================================== OpenRadioss 2023.09.15 Model: Rubber O-Ring Seal Installation Seconds < Lower Is Better a . 200.86 |=================================================================== b . 198.69 |================================================================== OpenRadioss 2023.09.15 Model: INIVOL and Fluid Structure Interaction Drop Container Seconds < Lower Is Better a . 553.97 |=================================================================== b . 553.87 |=================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 Seconds < Lower Is Better a . 7.976 |==================================================================== b . 7.159 |============================================================= easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 Seconds < Lower Is Better a . 157.06 |================================================================= b . 161.84 |=================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 Seconds < Lower Is Better a . 404.94 |=================================================================== b . 396.88 |================================================================== Embree 4.3 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 13.21 |==================================================================== b . 13.11 |=================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 9.9432 |=================================================================== b . 9.9097 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 16.09 |==================================================================== b . 15.96 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 14.47 |==================================================================== b . 14.45 |==================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 13.69 |==================================================================== b . 13.62 |==================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 11.76 |==================================================================== b . 11.76 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 1.938 |==================================================================== b . 1.950 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 29.89 |=================================================================== b . 30.16 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 12 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 73.23 |=================================================================== b . 73.80 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 13 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 73.36 |==================================================================== b . 73.22 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 5.348 |=================================================================== b . 5.442 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 8 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 44.23 |==================================================================== b . 44.41 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 12 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 181.54 |=================================================================== b . 177.56 |================================================================== SVT-AV1 1.7 Encoder Mode: Preset 13 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 180.47 |================================================================== b . 182.35 |=================================================================== Intel Open Image Denoise 2.1 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.32 |===================================================================== b . 0.32 |===================================================================== Intel Open Image Denoise 2.1 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.32 |=================================================================== b . 0.33 |===================================================================== Intel Open Image Denoise 2.1 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.15 |===================================================================== b . 0.15 |===================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU ISPC Items / Sec > Higher Is Better a . 275 |====================================================================== b . 274 |====================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU Scalar Items / Sec > Higher Is Better a . 95 |======================================================================= b . 94 |====================================================================== libavif avifenc 1.0 Encoder Speed: 0 Seconds < Lower Is Better a . 189.70 |=================================================================== b . 188.63 |=================================================================== libavif avifenc 1.0 Encoder Speed: 2 Seconds < Lower Is Better a . 90.46 |=================================================================== b . 91.59 |==================================================================== libavif avifenc 1.0 Encoder Speed: 6 Seconds < Lower Is Better a . 7.867 |================================================================== b . 8.129 |==================================================================== libavif avifenc 1.0 Encoder Speed: 6, Lossless Seconds < Lower Is Better a . 13.27 |==================================================================== b . 13.36 |==================================================================== libavif avifenc 1.0 Encoder Speed: 10, Lossless Seconds < Lower Is Better a . 7.667 |==================================================================== b . 7.708 |==================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.28255 |================================================================== b . 1.17212 |============================================================ oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.54511 |================================================================== b . 1.46367 |=============================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 10.58 |=============================================================== b . 11.44 |==================================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3.12064 |================================================================== b . 3.10326 |================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 6.25910 |================================================================== b . 6.14564 |================================================================= oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.59994 |================================================================== b . 1.38733 |=================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.90079 |================================================================== b . 1.90069 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 4007.84 |================================================================== b . 3545.80 |========================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 16.30 |==================================================================== b . 16.31 |==================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 23.78 |==================================================================== b . 22.27 |================================================================ oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 21.90 |==================================================================== b . 21.91 |==================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1824.27 |================================================================== b . 1807.68 |================================================================= oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3614.70 |================================================================== b . 3495.73 |================================================================ oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 1797.93 |========================================================= b . 2094.22 |================================================================== OpenVINO 2023.1 Model: Face Detection FP16 - Device: CPU FPS > Higher Is Better a . 2.31 |===================================================================== b . 2.30 |===================================================================== OpenVINO 2023.1 Model: Face Detection FP16 - Device: CPU ms < Lower Is Better a . 3455.53 |================================================================== b . 3462.59 |================================================================== OpenVINO 2023.1 Model: Person Detection FP16 - Device: CPU FPS > Higher Is Better a . 24.51 |==================================================================== b . 24.29 |=================================================================== OpenVINO 2023.1 Model: Person Detection FP16 - Device: CPU ms < Lower Is Better a . 325.69 |================================================================== b . 328.78 |=================================================================== OpenVINO 2023.1 Model: Person Detection FP32 - Device: CPU FPS > Higher Is Better a . 24.46 |==================================================================== b . 24.52 |==================================================================== OpenVINO 2023.1 Model: Person Detection FP32 - Device: CPU ms < Lower Is Better a . 326.23 |=================================================================== b . 325.91 |=================================================================== OpenVINO 2023.1 Model: Vehicle Detection FP16 - Device: CPU FPS > Higher Is Better a . 170.73 |================================================================== b . 172.22 |=================================================================== OpenVINO 2023.1 Model: Vehicle Detection FP16 - Device: CPU ms < Lower Is Better a . 46.82 |==================================================================== b . 46.41 |=================================================================== OpenVINO 2023.1 Model: Face Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 8.53 |===================================================================== b . 8.59 |===================================================================== OpenVINO 2023.1 Model: Face Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 935.89 |=================================================================== b . 925.88 |================================================================== OpenVINO 2023.1 Model: Face Detection Retail FP16 - Device: CPU FPS > Higher Is Better a . 586.21 |=================================================================== b . 587.05 |=================================================================== OpenVINO 2023.1 Model: Face Detection Retail FP16 - Device: CPU ms < Lower Is Better a . 13.62 |==================================================================== b . 13.60 |==================================================================== OpenVINO 2023.1 Model: Road Segmentation ADAS FP16 - Device: CPU FPS > Higher Is Better a . 80.07 |==================================================================== b . 79.50 |==================================================================== OpenVINO 2023.1 Model: Road Segmentation ADAS FP16 - Device: CPU ms < Lower Is Better a . 99.82 |=================================================================== b . 100.56 |===================================================================