dd AMD Ryzen 7 7840U testing with a PHX Ray_PEU (V1.04 BIOS) and AMD Phoenix1 512MB on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: AMD Ryzen 7 7840U @ 5.29GHz (8 Cores / 16 Threads), Motherboard: PHX Ray_PEU (V1.04 BIOS), Chipset: AMD Device 14e8, Memory: 16GB, Disk: 1024GB Micron_3400_MTFDKBA1T0TFH, Graphics: AMD Phoenix1 512MB (2700/800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: MEDIATEK MT7922 802.11ax PCI OS: Ubuntu 23.10, Kernel: 6.5.0-with-patch2 (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.3~git2309080600.fd297e~oibaf~m (git-fd297ec 2023-09-08 mantic-oibaf-ppa) (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3200x2000 b: Processor: AMD Ryzen 7 7840U @ 5.29GHz (8 Cores / 16 Threads), Motherboard: PHX Ray_PEU (V1.04 BIOS), Chipset: AMD Device 14e8, Memory: 16GB, Disk: 1024GB Micron_3400_MTFDKBA1T0TFH, Graphics: AMD Phoenix1 512MB (2700/800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: MEDIATEK MT7922 802.11ax PCI OS: Ubuntu 23.10, Kernel: 6.5.0-with-patch2 (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.3~git2309080600.fd297e~oibaf~m (git-fd297ec 2023-09-08 mantic-oibaf-ppa) (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3200x2000 c: Processor: AMD Ryzen 7 7840U @ 5.29GHz (8 Cores / 16 Threads), Motherboard: PHX Ray_PEU (V1.04 BIOS), Chipset: AMD Device 14e8, Memory: 16GB, Disk: 1024GB Micron_3400_MTFDKBA1T0TFH, Graphics: AMD Phoenix1 512MB (2700/800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: MEDIATEK MT7922 802.11ax PCI OS: Ubuntu 23.10, Kernel: 6.5.0-with-patch2 (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.3~git2309080600.fd297e~oibaf~m (git-fd297ec 2023-09-08 mantic-oibaf-ppa) (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3200x2000 QuantLib 1.32 Configuration: Multi-Threaded MFLOPS > Higher Is Better a . 28605.0 |================================================================== b . 28768.7 |================================================================== c . 28299.9 |================================================================= QuantLib 1.32 Configuration: Single-Threaded MFLOPS > Higher Is Better a . 4133.0 |================================================================= b . 4229.3 |=================================================================== c . 4074.6 |================================================================= easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 Seconds < Lower Is Better a . 11.98 |==================================================================== b . 11.93 |==================================================================== c . 11.98 |==================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 Seconds < Lower Is Better a . 236.37 |=================================================================== b . 235.94 |=================================================================== c . 236.14 |=================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 Seconds < Lower Is Better a . 584.73 |=================================================================== b . 585.35 |=================================================================== c . 579.99 |================================================================== Embree 4.3 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 7.1781 |================================================================== b . 7.2714 |=================================================================== c . 7.1882 |================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 7.4556 |=================================================================== b . 7.4331 |=================================================================== c . 7.4151 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 8.6173 |================================================================== b . 8.7640 |=================================================================== c . 8.7330 |=================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 7.8348 |=================================================================== b . 7.8132 |=================================================================== c . 7.7511 |================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 9.5152 |=================================================================== b . 9.5178 |=================================================================== c . 9.4660 |=================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 8.1114 |=================================================================== b . 8.0696 |=================================================================== c . 8.0388 |================================================================== Intel Open Image Denoise 2.1 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.22 |===================================================================== b . 0.22 |===================================================================== c . 0.22 |===================================================================== Intel Open Image Denoise 2.1 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.22 |===================================================================== b . 0.22 |===================================================================== c . 0.22 |===================================================================== Intel Open Image Denoise 2.1 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.11 |===================================================================== b . 0.11 |===================================================================== c . 0.11 |===================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU ISPC Items / Sec > Higher Is Better a . 170 |====================================================================== b . 171 |====================================================================== c . 171 |====================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU Scalar Items / Sec > Higher Is Better a . 67 |===================================================================== b . 67 |===================================================================== c . 69 |======================================================================= oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 8.86916 |================================================================= b . 8.99248 |================================================================== c . 8.66246 |================================================================ oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 5.61120 |================================================================== b . 5.57229 |================================================================== c . 5.59833 |================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.28110 |================================================================== b . 1.25823 |================================================================= c . 1.15590 |============================================================ oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.22678 |================================================================== b . 2.22532 |================================================================== c . 2.19780 |================================================================= oneDNN 3.3 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 2.75717 |================================================================== b . 2.75383 |================================================================== c . 2.42519 |========================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3.79236 |================================================================== b . 3.75671 |================================================================= c . 3.62443 |=============================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 15.02 |==================================================================== b . 14.94 |=================================================================== c . 15.09 |==================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 10.8682 |================================================================== b . 10.4152 |=============================================================== c . 9.6233 |========================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 7.60937 |================================================================= b . 7.67500 |================================================================== c . 6.36614 |======================================================= oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 14.25 |================================================================== b . 14.58 |==================================================================== c . 14.27 |=================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.52901 |============================================================ b . 1.67745 |================================================================== c . 1.29785 |=================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.92455 |=============================================================== b . 2.01069 |================================================================== c . 1.55587 |=================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 4898.17 |================================================================= b . 4967.81 |================================================================== c . 3876.53 |==================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 2514.18 |================================================================= b . 2555.43 |================================================================== c . 2127.79 |======================================================= oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 4919.23 |================================================================= b . 4965.28 |================================================================== c . 4376.69 |========================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 6.76831 |================================================================== b . 6.74215 |================================================================== c . 6.72684 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 9.93332 |================================================================== b . 9.73785 |================================================================= c . 8.70755 |========================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 5.17232 |================================================================= b . 5.22381 |================================================================== c . 4.42411 |======================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2506.07 |================================================================= b . 2555.28 |================================================================== c . 2320.01 |============================================================ oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 4956.70 |================================================================== b . 4925.48 |================================================================== c . 4574.04 |============================================================= oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 2520.79 |================================================================== b . 2524.94 |================================================================== c . 2382.55 |==============================================================