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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2310187-NE-DDDS2145567
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
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 |====================================================
easyWave r34
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240
Seconds < Lower Is Better
a . 10.322 |===================================================================
b . 9.919 |================================================================
c . 9.803 |================================================================
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: 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 |==================================================================
easyWave r34
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400
Seconds < Lower Is Better
a . 555.28 |=============================================================
b . 593.05 |==================================================================
c . 605.18 |===================================================================
easyWave r34
Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200
Seconds < Lower Is Better
a . 215.08 |========================================================
b . 240.10 |===============================================================
c . 255.60 |===================================================================
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: 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 |============================================================
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 |======================================================================
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 |=====================================================================