new tests eo nov Intel Core i9-14900K testing with a ASUS PRIME Z790-P WIFI (1402 BIOS) and AMD Radeon 15GB on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: Intel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (1402 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon 15GB (1617/1124MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U OS: Ubuntu 23.10, Kernel: 6.5.0-10-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2311100600.05fb6b~oibaf~m (git-05fb6b9 2023-11-10 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160 b: Processor: Intel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (1402 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon 15GB (1617/1124MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U OS: Ubuntu 23.10, Kernel: 6.5.0-10-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2311100600.05fb6b~oibaf~m (git-05fb6b9 2023-11-10 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160 c: Processor: Intel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (1402 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon 15GB (1617/1124MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U OS: Ubuntu 23.10, Kernel: 6.5.0-10-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2311100600.05fb6b~oibaf~m (git-05fb6b9 2023-11-10 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160 d: Processor: Intel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (1402 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon 15GB (1617/1124MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U OS: Ubuntu 23.10, Kernel: 6.5.0-10-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2311100600.05fb6b~oibaf~m (git-05fb6b9 2023-11-10 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160 e: Processor: Intel Core i9-14900K @ 5.70GHz (24 Cores / 32 Threads), Motherboard: ASUS PRIME Z790-P WIFI (1402 BIOS), Chipset: Intel Device 7a27, Memory: 32GB, Disk: Western Digital WD_BLACK SN850X 1000GB, Graphics: AMD Radeon 15GB (1617/1124MHz), Audio: Realtek ALC897, Monitor: ASUS VP28U OS: Ubuntu 23.10, Kernel: 6.5.0-10-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 24.0~git2311100600.05fb6b~oibaf~m (git-05fb6b9 2023-11-10 mantic-oibaf-ppa) (LLVM 16.0.6 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 3840x2160 WebP2 Image Encode 20220823 Encode Settings: Quality 100, Lossless Compression MP/s > Higher Is Better a . 0.04 |===================================================================== b . 0.04 |===================================================================== c . 0.04 |===================================================================== d . 0.04 |===================================================================== e . 0.04 |===================================================================== PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 8.85 |==================================================== b . 10.51 |============================================================== c . 11.60 |==================================================================== d . 8.92 |==================================================== e . 8.87 |==================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 8.79 |================================================== b . 11.65 |=================================================================== c . 8.88 |=================================================== d . 8.80 |================================================== e . 11.86 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 8.94 |=================================================== b . 11.98 |==================================================================== c . 8.95 |=================================================== d . 11.59 |================================================================== e . 8.78 |================================================== PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 8.90 |==================================================== b . 11.67 |==================================================================== c . 10.50 |============================================================= d . 8.96 |==================================================== e . 11.69 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 10.09 |========================================================= b . 8.82 |================================================== c . 8.89 |================================================== d . 11.72 |================================================================== e . 12.09 |==================================================================== OpenSSL Algorithm: SHA512 byte/s > Higher Is Better a . 10849481210 |============================================================= b . 11062578760 |============================================================== c . 10975727400 |============================================================== d . 10815857230 |============================================================= e . 11006330870 |============================================================== OpenSSL Algorithm: ChaCha20-Poly1305 OpenSSL Algorithm: AES-256-GCM OpenSSL Algorithm: AES-128-GCM OpenSSL Algorithm: ChaCha20 OpenSSL Algorithm: SHA256 byte/s > Higher Is Better a . 35474953010 |============================================================= b . 35998666020 |============================================================== c . 35762336880 |============================================================== d . 35625391340 |============================================================= e . 35567121540 |============================================================= WebP2 Image Encode 20220823 Encode Settings: Quality 95, Compression Effort 7 MP/s > Higher Is Better a . 0.16 |===================================================================== b . 0.16 |===================================================================== c . 0.16 |===================================================================== d . 0.16 |===================================================================== e . 0.16 |===================================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 batches/sec > Higher Is Better a . 17.17 |================================================================ b . 17.63 |================================================================== c . 17.99 |=================================================================== d . 15.14 |========================================================= e . 18.17 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 batches/sec > Higher Is Better a . 14.89 |======================================================= b . 18.42 |==================================================================== c . 14.65 |====================================================== d . 18.08 |=================================================================== e . 18.09 |=================================================================== PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 batches/sec > Higher Is Better a . 18.08 |=================================================================== b . 17.71 |================================================================== c . 18.04 |=================================================================== d . 14.88 |======================================================= e . 18.30 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-152 batches/sec > Higher Is Better a . 17.13 |================================================================ b . 18.15 |==================================================================== c . 17.97 |=================================================================== d . 18.08 |==================================================================== e . 18.07 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 batches/sec > Higher Is Better a . 18.04 |=================================================================== b . 17.12 |================================================================ c . 16.90 |=============================================================== d . 18.14 |==================================================================== e . 18.24 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l batches/sec > Higher Is Better a . 13.50 |==================================================================== b . 13.42 |==================================================================== c . 13.43 |==================================================================== d . 13.48 |==================================================================== e . 13.48 |==================================================================== OpenSSL Algorithm: RSA4096 verify/s > Higher Is Better a . 347145.5 |=============================================================== b . 355954.3 |================================================================ c . 359762.4 |================================================================= d . 351474.2 |================================================================ e . 352828.9 |================================================================ OpenSSL Algorithm: RSA4096 sign/s > Higher Is Better a . 5360.0 |================================================================= b . 5476.0 |================================================================== c . 5536.0 |=================================================================== d . 5410.1 |================================================================= e . 5429.5 |================================================================== WebP2 Image Encode 20220823 Encode Settings: Quality 75, Compression Effort 7 MP/s > Higher Is Better a . 0.35 |===================================================================== b . 0.33 |================================================================= d . 0.34 |=================================================================== e . 0.34 |=================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 batches/sec > Higher Is Better a . 28.71 |=================================================================== b . 28.97 |==================================================================== c . 22.35 |==================================================== d . 22.73 |===================================================== e . 22.45 |===================================================== PyTorch 2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 batches/sec > Higher Is Better a . 39.05 |======================================================== b . 39.34 |======================================================== c . 47.00 |=================================================================== d . 47.83 |==================================================================== e . 39.29 |======================================================== PyTorch 2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 batches/sec > Higher Is Better a . 46.32 |==================================================================== b . 44.47 |================================================================= c . 46.47 |==================================================================== d . 44.14 |================================================================= e . 38.68 |========================================================= PyTorch 2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 batches/sec > Higher Is Better a . 46.82 |==================================================================== b . 38.93 |======================================================== c . 46.95 |==================================================================== d . 44.52 |================================================================ e . 46.67 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 batches/sec > Higher Is Better a . 46.88 |==================================================================== b . 46.76 |==================================================================== c . 46.32 |=================================================================== d . 46.40 |=================================================================== e . 46.58 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 batches/sec > Higher Is Better a . 46.48 |==================================================================== b . 46.73 |==================================================================== c . 46.76 |==================================================================== d . 46.30 |=================================================================== e . 46.49 |==================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 31.15 |==================================================================== b . 31.12 |==================================================================== c . 31.09 |==================================================================== d . 31.27 |==================================================================== e . 31.13 |==================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 31.86 |==================================================================== b . 31.75 |==================================================================== c . 31.72 |==================================================================== d . 31.65 |==================================================================== e . 31.88 |==================================================================== Java SciMark 2.2 Computational Test: Composite Mflops > Higher Is Better a . 4716.01 |================================================================= b . 4785.17 |================================================================== c . 4773.58 |================================================================== d . 4772.90 |================================================================== e . 4779.52 |================================================================== Embree 4.3 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 30.07 |=================================================================== b . 30.06 |=================================================================== c . 30.31 |==================================================================== d . 29.99 |=================================================================== e . 30.10 |==================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 30.48 |==================================================================== b . 30.25 |=================================================================== c . 30.20 |=================================================================== d . 30.19 |=================================================================== e . 30.27 |==================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 34.45 |==================================================================== b . 34.44 |==================================================================== c . 34.48 |==================================================================== d . 34.38 |==================================================================== e . 34.50 |==================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 36.21 |==================================================================== b . 36.41 |==================================================================== c . 36.25 |==================================================================== d . 36.42 |==================================================================== e . 36.22 |==================================================================== PyTorch 2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 batches/sec > Higher Is Better a . 58.84 |===================================================== b . 60.11 |====================================================== c . 74.54 |=================================================================== d . 75.67 |==================================================================== e . 74.03 |=================================================================== WebP2 Image Encode 20220823 Encode Settings: Quality 100, Compression Effort 5 MP/s > Higher Is Better a . 8.83 |============================================================= b . 8.96 |============================================================== c . 9.93 |===================================================================== d . 7.65 |===================================================== e . 9.98 |===================================================================== WebP2 Image Encode 20220823 Encode Settings: Default MP/s > Higher Is Better a . 15.78 |================================================================== b . 15.89 |=================================================================== c . 15.40 |================================================================ d . 16.24 |==================================================================== e . 15.65 |================================================================== Java SciMark 2.2 Computational Test: Jacobi Successive Over-Relaxation Mflops > Higher Is Better a . 2940.87 |================================================================== b . 2947.94 |================================================================== c . 2947.94 |================================================================== d . 2947.94 |================================================================== e . 2949.36 |================================================================== Java SciMark 2.2 Computational Test: Dense LU Matrix Factorization Mflops > Higher Is Better a . 13059.89 |=============================================================== b . 13387.72 |================================================================= c . 13341.67 |================================================================= d . 13337.50 |================================================================= e . 13354.20 |================================================================= Java SciMark 2.2 Computational Test: Sparse Matrix Multiply Mflops > Higher Is Better a . 4792.04 |================================================================== b . 4790.64 |================================================================== c . 4789.24 |================================================================== d . 4780.86 |================================================================== e . 4794.85 |================================================================== Java SciMark 2.2 Computational Test: Fast Fourier Transform Mflops > Higher Is Better a . 1219.73 |================================================================= b . 1232.02 |================================================================== c . 1232.91 |================================================================== d . 1230.69 |================================================================== e . 1231.13 |================================================================== Java SciMark 2.2 Computational Test: Monte Carlo Mflops > Higher Is Better a . 1567.51 |================================================================== b . 1567.51 |================================================================== c . 1556.15 |================================================================= d . 1567.51 |================================================================== e . 1568.08 |==================================================================