ddds Intel Core i7-1280P testing with a MSI MS-14C6 (E14C6IMS.115 BIOS) and MSI Intel ADL GT2 15GB on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: Intel Core i7-1280P @ 4.70GHz (14 Cores / 20 Threads), Motherboard: MSI MS-14C6 (E14C6IMS.115 BIOS), Chipset: Intel Alder Lake PCH, Memory: 16GB, Disk: 1024GB Micron_3400_MTFDKBA1T0TFH, Graphics: MSI Intel ADL GT2 15GB (1450MHz), Audio: Realtek ALC274, Network: Intel Alder Lake-P PCH CNVi WiFi OS: Ubuntu 23.10, Kernel: 6.3.0-7-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.1.7-1ubuntu1, OpenCL: OpenCL 3.0, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1080 b: Processor: Intel Core i7-1280P @ 4.70GHz (14 Cores / 20 Threads), Motherboard: MSI MS-14C6 (E14C6IMS.115 BIOS), Chipset: Intel Alder Lake PCH, Memory: 16GB, Disk: 1024GB Micron_3400_MTFDKBA1T0TFH, Graphics: MSI Intel ADL GT2 15GB (1450MHz), Audio: Realtek ALC274, Network: Intel Alder Lake-P PCH CNVi WiFi OS: Ubuntu 23.10, Kernel: 6.3.0-7-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.1.7-1ubuntu1, OpenCL: OpenCL 3.0, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1080 c: Processor: Intel Core i7-1280P @ 4.70GHz (14 Cores / 20 Threads), Motherboard: MSI MS-14C6 (E14C6IMS.115 BIOS), Chipset: Intel Alder Lake PCH, Memory: 16GB, Disk: 1024GB Micron_3400_MTFDKBA1T0TFH, Graphics: MSI Intel ADL GT2 15GB (1450MHz), Audio: Realtek ALC274, Network: Intel Alder Lake-P PCH CNVi WiFi OS: Ubuntu 23.10, Kernel: 6.3.0-7-generic (x86_64), Desktop: GNOME Shell, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.1.7-1ubuntu1, OpenCL: OpenCL 3.0, Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 1920x1080 FluidX3D 2.9 Test: FP32-FP32 MLUPs/s > Higher Is Better a . 369 |====================================================================== b . 365 |===================================================================== c . 368 |====================================================================== FluidX3D 2.9 Test: FP32-FP16C MLUPs/s > Higher Is Better a . 609 |===================================================================== b . 616 |====================================================================== c . 618 |====================================================================== FluidX3D 2.9 Test: FP32-FP16S MLUPs/s > Higher Is Better a . 646 |====================================================================== b . 649 |====================================================================== c . 644 |===================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 Seconds < Lower Is Better a . 10.322 |=================================================================== b . 9.919 |================================================================ c . 9.803 |================================================================ easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 Seconds < Lower Is Better a . 215.08 |======================================================== b . 240.10 |=============================================================== c . 255.60 |=================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 Seconds < Lower Is Better a . 555.28 |============================================================= b . 593.05 |================================================================== c . 605.18 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 7.5237 |=================================================================== b . 5.8001 |==================================================== c . 4.9874 |============================================ Embree 4.3 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 7.7035 |=================================================================== b . 5.8382 |=================================================== c . 5.3040 |============================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 9.4849 |=================================================================== b . 7.3744 |==================================================== c . 6.2796 |============================================ Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 8.5685 |=================================================================== b . 6.5378 |=================================================== c . 5.6884 |============================================ Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 10.1820 |================================================================== b . 7.8561 |=================================================== c . 7.1952 |=============================================== Embree 4.3 Binary: Pathtracer oneAPI SYCL - Model: Crown Frames Per Second > Higher Is Better Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 8.8968 |=================================================================== b . 6.8812 |==================================================== c . 6.8098 |=================================================== Embree 4.3 Binary: Pathtracer oneAPI SYCL - Model: Asian Dragon Frames Per Second > Higher Is Better Embree 4.3 Binary: Pathtracer oneAPI SYCL - Model: Asian Dragon Obj Frames Per Second > Higher Is Better Intel Open Image Denoise 2.1 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.22 |===================================================================== b . 0.18 |======================================================== c . 0.19 |============================================================ Intel Open Image Denoise 2.1 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.21 |===================================================================== b . 0.17 |======================================================== c . 0.17 |======================================================== Intel Open Image Denoise 2.1 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.10 |===================================================================== b . 0.08 |======================================================= c . 0.08 |======================================================= OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU ISPC Items / Sec > Higher Is Better a . 161 |====================================================================== b . 132 |========================================================= c . 131 |========================================================= OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU Scalar Items / Sec > Higher Is Better a . 74 |======================================================================= b . 57 |======================================================= c . 58 |======================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkGPU Intel oneAPI SYCL Items / Sec > Higher Is Better a . 137 |================================================================== b . 139 |=================================================================== c . 145 |====================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 11.45740 |================================================================= b . 9.14804 |==================================================== c . 7.77802 |============================================ oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 5.63896 |===================================================== b . 6.98825 |================================================================== c . 5.85137 |======================================================= oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.27679 |================================================ b . 3.14049 |================================================================== c . 2.49493 |==================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.71431 |===================================== b . 3.08209 |================================================================== c . 2.25098 |================================================ 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 . 8.75450 |================================================================= b . 8.83358 |================================================================== c . 8.76650 |================================================================= oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 10.05 |============================================================== b . 10.25 |================================================================ c . 10.95 |==================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 9.51050 |================================================================== b . 9.55980 |================================================================== c . 9.55125 |================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 7.79179 |============================================================== b . 7.84281 |============================================================== c . 8.28649 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.72830 |============================================================ b . 2.57218 |======================================================== c . 3.01476 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3.66772 |================================================================== b . 3.68241 |================================================================== c . 3.68788 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 8810.16 |============================================================= b . 9201.00 |================================================================ c . 9513.20 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 4847.73 |============================================================== b . 5161.73 |================================================================== c . 5159.09 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 9189.71 |============================================================= b . 9853.70 |================================================================= c . 9946.69 |================================================================== 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 . 4517.55 |================================================================ b . 4625.90 |================================================================== c . 4623.65 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 9056.79 |=========================================================== b . 10044.60 |================================================================= c . 9116.27 |=========================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 4772.43 |============================================================ b . 5236.44 |================================================================== c . 4733.46 |============================================================