one one AMD Ryzen Threadripper 3990X 64-Core testing with a Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 23.04 via the Phoronix Test Suite. a: Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200 OS: Ubuntu 23.04, Kernel: 6.2.0-32-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.3.0, File-System: ext4, Screen Resolution: 3840x2160 b: Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200 OS: Ubuntu 23.04, Kernel: 6.2.0-32-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.3.0, File-System: ext4, Screen Resolution: 3840x2160 c: Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200 OS: Ubuntu 23.04, Kernel: 6.2.0-32-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.3.0, File-System: ext4, Screen Resolution: 3840x2160 d: Processor: AMD Ryzen Threadripper 3990X 64-Core @ 2.90GHz (64 Cores / 128 Threads), Motherboard: Gigabyte TRX40 AORUS PRO WIFI (F6 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: AMD Radeon RX 5700 8GB (1750/875MHz), Audio: AMD Navi 10 HDMI Audio, Monitor: DELL P2415Q, Network: Intel I211 + Intel Wi-Fi 6 AX200 OS: Ubuntu 23.04, Kernel: 6.2.0-32-generic (x86_64), Desktop: GNOME Shell 44.0, Display Server: X Server + Wayland, OpenGL: 4.6 Mesa 23.0.2 (LLVM 15.0.7 DRM 3.49), Compiler: GCC 12.3.0, File-System: ext4, Screen Resolution: 3840x2160 Embree 4.3 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 53.69 |==================================================================== b . 52.70 |=================================================================== c . 51.47 |================================================================= d . 52.17 |================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 48.66 |==================================================================== b . 47.54 |================================================================== c . 46.83 |================================================================= d . 47.18 |================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 41.96 |==================================================================== b . 41.37 |=================================================================== c . 40.18 |================================================================= d . 40.63 |================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 36.08 |==================================================================== b . 35.70 |=================================================================== c . 35.54 |=================================================================== d . 35.15 |================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 41.41 |==================================================================== b . 40.96 |=================================================================== c . 40.57 |=================================================================== d . 40.40 |================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 35.77 |==================================================================== b . 35.40 |=================================================================== c . 34.84 |================================================================== d . 34.90 |================================================================== Intel Open Image Denoise 2.1 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 1.36 |===================================================================== b . 1.36 |===================================================================== c . 1.35 |==================================================================== d . 1.35 |==================================================================== Intel Open Image Denoise 2.1 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 1.36 |===================================================================== b . 1.36 |===================================================================== c . 1.35 |==================================================================== d . 1.35 |==================================================================== Intel Open Image Denoise 2.1 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.67 |===================================================================== b . 0.67 |===================================================================== c . 0.66 |==================================================================== d . 0.66 |==================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 2.50584 |================================================================== b . 2.36677 |============================================================== c . 2.50646 |================================================================== d . 2.13116 |======================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 5.90121 |============================================================= b . 6.01717 |============================================================== c . 6.32392 |================================================================== d . 6.35958 |================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 2.46367 |================================================================ b . 2.28707 |=========================================================== c . 2.41181 |============================================================== d . 2.55858 |================================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.08280 |================================================================== b . 1.08255 |================================================================== c . 1.06728 |================================================================= d . 1.06927 |================================================================= oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 1.013630 |================================================================ b . 1.027350 |================================================================ c . 0.976971 |============================================================= d . 1.037500 |================================================================= oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 9.68878 |================================================================== b . 9.52953 |================================================================ c . 9.75211 |================================================================== d . 9.62871 |================================================================= oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 2.14010 |================================================================== b . 2.12440 |================================================================= c . 2.13061 |================================================================= d . 2.15552 |================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 6.50020 |================================================================= b . 6.50551 |================================================================== c . 6.53647 |================================================================== d . 6.55404 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.62713 |================================================================ b . 1.68374 |================================================================== c . 1.65764 |================================================================= d . 1.67016 |================================================================= oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 0.988933 |================================================================ b . 1.000080 |================================================================= c . 0.988952 |================================================================ d . 0.994753 |================================================================= oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 4010.95 |================================================================== b . 3996.22 |================================================================== c . 4012.80 |================================================================== d . 3998.33 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 848.08 |=================================================================== b . 853.46 |=================================================================== c . 845.92 |================================================================== d . 850.23 |=================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 4014.40 |================================================================== b . 4014.69 |================================================================== c . 4014.72 |================================================================== d . 4003.11 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 857.63 |=================================================================== b . 857.24 |=================================================================== c . 850.83 |================================================================== d . 853.26 |=================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 9669.71 |================================================================== b . 4010.42 |=========================== c . 4008.22 |=========================== d . 4006.87 |=========================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 1007.00 |================================================================== b . 849.77 |======================================================== c . 857.77 |======================================================== d . 848.70 |======================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU ISPC Items / Sec > Higher Is Better a . 744 |====================================================================== b . 731 |===================================================================== c . 741 |====================================================================== d . 743 |====================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU Scalar Items / Sec > Higher Is Better a . 425 |====================================================================== b . 410 |==================================================================== c . 410 |==================================================================== d . 410 |====================================================================