rt ml lunar lalke Intel Core Ultra 7 256V testing with a ASUS Zenbook S 14 UX5406SA_UX5406SA UX5406SA v1.0 (UX5406SA.300 BIOS) and ASUS Intel LNL 7GB on Ubuntu 24.10 via the Phoronix Test Suite. a: Processor: Intel Core Ultra 7 256V @ 4.70GHz (8 Cores), Motherboard: ASUS Zenbook S 14 UX5406SA_UX5406SA UX5406SA v1.0 (UX5406SA.300 BIOS), Chipset: Intel Device a87f, Memory: 8 x 2GB LPDDR5-8533MT/s Samsung, Disk: 1024GB Western Digital WD PC SN560 SDDPNQE-1T00-1102, Graphics: ASUS Intel LNL 7GB, Audio: Intel Lunar Lake-M HD Audio, Network: Intel Device a840 OS: Ubuntu 24.10, Kernel: 6.11.0-8-generic (x86_64), Desktop: GNOME Shell 47.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 24.3~git2410050600.39e301~oibaf~o (git-39e3015 2024-10-05 oracular-oibaf-pp, OpenCL: OpenCL 3.0, Compiler: GCC 14.2.0, File-System: ext4, Screen Resolution: 2880x1800 b: Processor: Intel Core Ultra 7 256V @ 4.70GHz (8 Cores), Motherboard: ASUS Zenbook S 14 UX5406SA_UX5406SA UX5406SA v1.0 (UX5406SA.300 BIOS), Chipset: Intel Device a87f, Memory: 8 x 2GB LPDDR5-8533MT/s Samsung, Disk: 1024GB Western Digital WD PC SN560 SDDPNQE-1T00-1102, Graphics: ASUS Intel LNL 7GB, Audio: Intel Lunar Lake-M HD Audio, Network: Intel Device a840 OS: Ubuntu 24.10, Kernel: 6.11.0-8-generic (x86_64), Desktop: GNOME Shell 47.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 24.3~git2410050600.39e301~oibaf~o (git-39e3015 2024-10-05 oracular-oibaf-pp, OpenCL: OpenCL 3.0, Compiler: GCC 14.2.0, File-System: ext4, Screen Resolution: 2880x1800 c: Processor: Intel Core Ultra 7 256V @ 4.70GHz (8 Cores), Motherboard: ASUS Zenbook S 14 UX5406SA_UX5406SA UX5406SA v1.0 (UX5406SA.300 BIOS), Chipset: Intel Device a87f, Memory: 8 x 2GB LPDDR5-8533MT/s Samsung, Disk: 1024GB Western Digital WD PC SN560 SDDPNQE-1T00-1102, Graphics: ASUS Intel LNL 7GB, Audio: Intel Lunar Lake-M HD Audio, Network: Intel Device a840 OS: Ubuntu 24.10, Kernel: 6.11.0-8-generic (x86_64), Desktop: GNOME Shell 47.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 24.3~git2410050600.39e301~oibaf~o (git-39e3015 2024-10-05 oracular-oibaf-pp, OpenCL: OpenCL 3.0, Compiler: GCC 14.2.0, File-System: ext4, Screen Resolution: 2880x1800 d: Processor: Intel Core Ultra 7 256V @ 4.70GHz (8 Cores), Motherboard: ASUS Zenbook S 14 UX5406SA_UX5406SA UX5406SA v1.0 (UX5406SA.300 BIOS), Chipset: Intel Device a87f, Memory: 8 x 2GB LPDDR5-8533MT/s Samsung, Disk: 1024GB Western Digital WD PC SN560 SDDPNQE-1T00-1102, Graphics: ASUS Intel LNL 7GB, Audio: Intel Lunar Lake-M HD Audio, Network: Intel Device a840 OS: Ubuntu 24.10, Kernel: 6.11.0-8-generic (x86_64), Desktop: GNOME Shell 47.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 24.3~git2410050600.39e301~oibaf~o (git-39e3015 2024-10-05 oracular-oibaf-pp, OpenCL: OpenCL 3.0, Compiler: GCC 14.2.0, File-System: ext4, Screen Resolution: 2880x1800 oneDNN 3.6 Harness: Recurrent Neural Network Training - Engine: CPU ms < Lower Is Better a . 47469.3 |===================================================== b . 40646.2 |============================================= c . 46000.7 |=================================================== d . 59465.3 |================================================================== oneDNN 3.6 Harness: Recurrent Neural Network Inference - Engine: CPU ms < Lower Is Better a . 38654.1 |================================================================== b . 20543.4 |=================================== c . 24385.1 |========================================== d . 22618.7 |======================================= XNNPACK b7b048 Model: QS8MobileNetV2 us < Lower Is Better a . 1431 |===================================================================== b . 1435 |===================================================================== c . 1417 |==================================================================== d . 1418 |==================================================================== XNNPACK b7b048 Model: FP16MobileNetV3Small us < Lower Is Better a . 891 |===================================================================== b . 899 |====================================================================== c . 892 |===================================================================== d . 888 |===================================================================== XNNPACK b7b048 Model: FP16MobileNetV3Large us < Lower Is Better a . 2303 |===================================================================== b . 2304 |===================================================================== c . 2295 |===================================================================== d . 2285 |==================================================================== XNNPACK b7b048 Model: FP16MobileNetV2 us < Lower Is Better a . 2514 |==================================================================== b . 2554 |===================================================================== c . 2552 |===================================================================== d . 2541 |===================================================================== XNNPACK b7b048 Model: FP16MobileNetV1 us < Lower Is Better a . 3944 |==================================================================== b . 3996 |===================================================================== c . 3981 |===================================================================== d . 3928 |==================================================================== XNNPACK b7b048 Model: FP32MobileNetV3Small us < Lower Is Better a . 953 |===================================================================== b . 946 |===================================================================== c . 944 |===================================================================== d . 963 |====================================================================== XNNPACK b7b048 Model: FP32MobileNetV3Large us < Lower Is Better a . 2710 |===================================================================== b . 2623 |=================================================================== c . 2657 |==================================================================== d . 2565 |================================================================= XNNPACK b7b048 Model: FP32MobileNetV2 us < Lower Is Better a . 2756 |===================================================================== b . 2701 |=================================================================== c . 2747 |===================================================================== d . 2763 |===================================================================== XNNPACK b7b048 Model: FP32MobileNetV1 us < Lower Is Better a . 4568 |==================================================================== b . 4669 |===================================================================== c . 4522 |=================================================================== d . 4547 |=================================================================== LiteRT 2024-10-15 Model: Inception V4 Microseconds < Lower Is Better a . 61928.8 |================================================================== b . 61615.0 |================================================================== c . 61797.7 |================================================================== d . 61788.8 |================================================================== LiteRT 2024-10-15 Model: Inception ResNet V2 Microseconds < Lower Is Better a . 56566.9 |================================================================== b . 56700.7 |================================================================== c . 56712.2 |================================================================== d . 56752.5 |================================================================== LiteRT 2024-10-15 Model: NASNet Mobile Microseconds < Lower Is Better a . 8215.58 |================================================================== b . 8230.73 |================================================================== c . 8157.02 |================================================================= d . 8232.79 |================================================================== LiteRT 2024-10-15 Model: DeepLab V3 Microseconds < Lower Is Better a . 3692.05 |================================================================= b . 3732.92 |================================================================== c . 3723.37 |================================================================== d . 3730.47 |================================================================== LiteRT 2024-10-15 Model: Mobilenet Float Microseconds < Lower Is Better a . 3368.65 |================================================================= b . 3382.83 |================================================================= c . 3418.29 |================================================================== d . 3353.43 |================================================================= LiteRT 2024-10-15 Model: SqueezeNet Microseconds < Lower Is Better a . 4065.69 |================================================================== b . 4071.32 |================================================================== c . 4082.01 |================================================================== d . 4063.38 |================================================================== LiteRT 2024-10-15 Model: Quantized COCO SSD MobileNet v1 Microseconds < Lower Is Better a . 5751.87 |================================================================== b . 5780.23 |================================================================== c . 5767.25 |================================================================== d . 5675.10 |================================================================= LiteRT 2024-10-15 Model: Mobilenet Quant Microseconds < Lower Is Better a . 4311.17 |================================================================= b . 4304.33 |================================================================= c . 4354.91 |================================================================== d . 4327.05 |================================================================== oneDNN 3.6 Harness: Deconvolution Batch shapes_1d - Engine: CPU ms < Lower Is Better a . 7.56465 |================================================================== b . 7.47775 |================================================================= c . 7.50631 |================================================================= d . 7.46605 |================================================================= oneDNN 3.6 Harness: IP Shapes 1D - Engine: CPU ms < Lower Is Better a . 28.64 |============== b . 31.18 |================ c . 27.79 |============== d . 134.53 |=================================================================== oneDNN 3.6 Harness: IP Shapes 3D - Engine: CPU ms < Lower Is Better a . 7.65143 |================================================================== b . 7.62038 |================================================================== c . 7.61504 |================================================================== d . 7.64038 |================================================================== oneDNN 3.6 Harness: Convolution Batch Shapes Auto - Engine: CPU ms < Lower Is Better a . 13.06 |==================================================================== b . 11.20 |========================================================== c . 11.63 |============================================================= d . 11.01 |========================================================= oneDNN 3.6 Harness: Deconvolution Batch shapes_3d - Engine: CPU ms < Lower Is Better a . 81.38 |==================================================================== b . 37.52 |=============================== c . 45.05 |====================================== d . 74.95 |===============================================================