new sun 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: 6.2.0-20-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 12.2.0, 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: 6.2.0-20-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 12.2.0, 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: 6.2.0-20-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 12.2.0, File-System: ext4, Screen Resolution: 3840x2160 CP2K Molecular Dynamics 2023.1 Input: H20-64 Seconds < Lower Is Better a . 40.67 |================================================================== b . 41.51 |=================================================================== c . 41.82 |==================================================================== CP2K Molecular Dynamics 2023.1 Input: H2O-DFT-LS Seconds < Lower Is Better CP2K Molecular Dynamics 2023.1 Input: Fayalite-FIST Seconds < Lower Is Better a . 151.86 |================================================================= b . 153.86 |================================================================== c . 156.12 |=================================================================== GPAW 23.6 Input: Carbon Nanotube Seconds < Lower Is Better a . 106.14 |=================================================================== b . 106.63 |=================================================================== c . 106.68 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 62.04 |================================================================== b . 61.89 |================================================================== c . 63.90 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 34.67 |==================================================================== b . 34.37 |=================================================================== c . 34.22 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 112.30 |================================================================== b . 113.57 |=================================================================== c . 112.33 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 86.06 |=================================================================== b . 87.46 |==================================================================== c . 87.20 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 33.08 |=================================================================== b . 33.73 |==================================================================== c . 33.25 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 12.53 |==================================================================== b . 12.61 |==================================================================== c . 12.60 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 59.19 |================================================================== b . 59.60 |================================================================== c . 61.23 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 37.43 |==================================================================== b . 37.47 |==================================================================== c . 37.54 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 60.70 |==================================================================== b . 60.37 |==================================================================== c . 60.34 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 29.83 |==================================================================== b . 29.82 |==================================================================== c . 29.80 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 103.58 |================================================================== b . 104.37 |================================================================== c . 105.45 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 98.69 |================================================================= b . 101.59 |=================================================================== c . 100.27 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 32.05 |==================================================================== b . 31.58 |=================================================================== c . 32.15 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 12.83 |==================================================================== b . 12.84 |==================================================================== c . 12.78 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 58.59 |==================================================================== b . 58.42 |==================================================================== c . 58.24 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 34.22 |==================================================================== b . 34.37 |==================================================================== c . 34.40 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 61.28 |=================================================================== b . 61.78 |==================================================================== c . 61.29 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 34.70 |==================================================================== b . 34.31 |=================================================================== c . 34.13 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 113.16 |=================================================================== b . 110.95 |================================================================== c . 110.74 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 87.46 |==================================================================== b . 87.11 |==================================================================== c . 86.48 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 33.42 |==================================================================== b . 33.57 |==================================================================== c . 32.80 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 12.62 |==================================================================== b . 12.59 |==================================================================== c . 12.62 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 59.69 |==================================================================== b . 60.00 |==================================================================== c . 60.10 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 37.35 |=================================================================== b . 37.32 |=================================================================== c . 37.84 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 60.56 |==================================================================== b . 60.11 |=================================================================== c . 60.55 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 29.70 |==================================================================== b . 29.87 |==================================================================== c . 29.88 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 105.45 |=================================================================== b . 103.17 |================================================================== c . 103.77 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 101.92 |=================================================================== b . 101.27 |=================================================================== c . 100.40 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 31.63 |=================================================================== b . 31.62 |=================================================================== c . 31.95 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 12.76 |==================================================================== b . 12.76 |==================================================================== c . 12.75 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 58.82 |==================================================================== b . 58.51 |==================================================================== c . 58.92 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 34.30 |==================================================================== b . 34.36 |==================================================================== c . 34.51 |==================================================================== Kripke 1.2.6 Throughput FoM > Higher Is Better a . 132875000 |=============================================================== b . 134555700 |================================================================ c . 132703600 |=============================================================== Monte Carlo Simulations of Ionised Nebulae 2.02.73.3 Input: Gas HII40 Seconds < Lower Is Better a . 16.91 |=================================================================== b . 17.14 |==================================================================== c . 17.03 |==================================================================== Monte Carlo Simulations of Ionised Nebulae 2.02.73.3 Input: Dust 2D tau100.0 Seconds < Lower Is Better a . 141.94 |=================================================================== b . 136.99 |================================================================= c . 136.20 |================================================================ Palabos 2.3 Grid Size: 100 Mega Site Updates Per Second > Higher Is Better a . 154.43 |=================================================================== b . 154.67 |=================================================================== c . 154.35 |=================================================================== Palabos 2.3 Grid Size: 400 Mega Site Updates Per Second > Higher Is Better a . 110.66 |=================================================================== b . 110.76 |=================================================================== c . 110.74 |=================================================================== Palabos 2.3 Grid Size: 500 Mega Site Updates Per Second > Higher Is Better a . 114.30 |=================================================================== b . 114.36 |=================================================================== c . 114.31 |===================================================================