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.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2310248-NE-DD557351896
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 |==============================================================