dd Intel Core i7-1165G7 testing with a Dell 0GG9PT (3.15.0 BIOS) and Intel Xe TGL GT2 15GB on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.15.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 15GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201 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: 1920x1200 b: Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.15.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 15GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201 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: 1920x1200 c: Processor: Intel Core i7-1165G7 @ 4.70GHz (4 Cores / 8 Threads), Motherboard: Dell 0GG9PT (3.15.0 BIOS), Chipset: Intel Tiger Lake-LP, Memory: 16GB, Disk: Kioxia KBG40ZNS256G NVMe 256GB, Graphics: Intel Xe TGL GT2 15GB (1300MHz), Audio: Realtek ALC289, Network: Intel Wi-Fi 6 AX201 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: 1920x1200 FluidX3D 2.9 Test: FP32-FP32 MLUPs/s > Higher Is Better a . 247 |====================================================================== b . 242 |==================================================================== c . 248 |====================================================================== FluidX3D 2.9 Test: FP32-FP16C MLUPs/s > Higher Is Better a . 411 |====================================================================== b . 406 |===================================================================== c . 413 |====================================================================== FluidX3D 2.9 Test: FP32-FP16S MLUPs/s > Higher Is Better a . 397 |==================================================================== b . 398 |===================================================================== c . 406 |====================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 Seconds < Lower Is Better a . 9.604 |=================================================================== b . 9.740 |==================================================================== c . 9.506 |================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 Seconds < Lower Is Better a . 187.40 |================================================================== b . 191.03 |=================================================================== c . 190.93 |=================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 Seconds < Lower Is Better a . 469.30 |=================================================================== b . 468.63 |=================================================================== c . 464.48 |================================================================== Embree 4.3 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 4.2691 |=================================================================== b . 4.2385 |=================================================================== c . 4.2100 |================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 4.5354 |================================================================ b . 4.5430 |================================================================ c . 4.7405 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 4.7910 |=================================================================== b . 4.7841 |=================================================================== c . 4.8127 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 4.3470 |================================================================== b . 4.3827 |================================================================== c . 4.4294 |=================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 5.8162 |=================================================================== b . 5.8017 |=================================================================== c . 5.8330 |=================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 5.1835 |=================================================================== b . 5.0059 |================================================================= c . 5.0153 |================================================================= Intel Open Image Denoise 2.1 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.15 |===================================================================== b . 0.15 |===================================================================== c . 0.15 |===================================================================== Intel Open Image Denoise 2.1 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.15 |===================================================================== b . 0.15 |===================================================================== c . 0.15 |===================================================================== Intel Open Image Denoise 2.1 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.07 |===================================================================== b . 0.07 |===================================================================== c . 0.07 |===================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU ISPC Items / Sec > Higher Is Better a . 104 |===================================================================== b . 105 |====================================================================== c . 104 |===================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU Scalar Items / Sec > Higher Is Better a . 37 |===================================================================== b . 38 |======================================================================= c . 37 |===================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkGPU Intel oneAPI SYCL Items / Sec > Higher Is Better a . 144 |================================================================ b . 152 |==================================================================== c . 157 |====================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 7.95343 |============================================================== b . 8.46338 |================================================================== c . 8.16196 |================================================================ oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 5.65906 |================================================================= b . 5.70130 |================================================================== c . 5.70609 |================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.71879 |=============================================================== b . 1.59984 |========================================================== c . 1.81446 |================================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.17152 |================================================================= b . 2.20171 |================================================================== c . 2.17957 |================================================================= oneDNN 3.3 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 18.66 |=================================================================== b . 18.74 |=================================================================== c . 18.93 |==================================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 5.50889 |============================================================== b . 5.86677 |================================================================== c . 5.75674 |================================================================= oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 8.78691 |================================================================= b . 8.77815 |================================================================= c . 8.88503 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 11.55 |===================================================== b . 14.72 |==================================================================== c . 10.73 |================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 10.33 |================================================================== b . 10.34 |================================================================== c . 10.60 |==================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 7.93041 |================================================================== b . 7.89634 |================================================================= c . 7.98042 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.20024 |================================================================== b . 2.20040 |================================================================== c . 2.18748 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.50626 |================================================================== b . 2.50853 |================================================================== c . 2.50391 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 7514.62 |================================================================== b . 7500.18 |================================================================== c . 7499.24 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 3896.27 |================================================================== b . 3562.50 |============================================================ c . 3790.40 |================================================================ oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 7519.43 |================================================================= b . 7632.35 |================================================================== c . 7621.22 |================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 47.71 |==================================================================== b . 42.26 |============================================================ c . 39.61 |======================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 55.57 |==================================================================== b . 47.06 |========================================================== c . 47.79 |========================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 38.49 |================================================================== b . 38.54 |================================================================== c . 39.50 |==================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3842.23 |================================================================== b . 3846.70 |================================================================== c . 3837.41 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 7618.20 |================================================================== b . 7634.40 |================================================================== c . 7628.46 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3897.29 |================================================================== b . 3836.99 |================================================================= c . 3844.87 |=================================================================