one phoenix AMD Ryzen 7 PRO 7840U testing with a LENOVO 21K5001JUS (R2FET33W_0921_3 1.13 BIOS) and AMD Phoenix1 4GB on Ubuntu 23.10 via the Phoronix Test Suite. a: Processor: AMD Ryzen 7 PRO 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: LENOVO 21K5001JUS (R2FET33W_0921_3 1.13 BIOS), Chipset: AMD Device 14e8, Memory: 60GB, Disk: 1024GB Kioxia KXG8AZNV1T02 LA, Graphics: AMD Phoenix1 4GB (2700/800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: Realtek RTL8111/8168/8411 + Qualcomm QCNFA765 OS: Ubuntu 23.10, Kernel: 6.6.0-060600rc3daily20230925-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 23.1.7-1ubuntu1 (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2880x1800 b: Processor: AMD Ryzen 7 PRO 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: LENOVO 21K5001JUS (R2FET33W_0921_3 1.13 BIOS), Chipset: AMD Device 14e8, Memory: 60GB, Disk: 1024GB Kioxia KXG8AZNV1T02 LA, Graphics: AMD Phoenix1 4GB (2700/800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: Realtek RTL8111/8168/8411 + Qualcomm QCNFA765 OS: Ubuntu 23.10, Kernel: 6.6.0-060600rc3daily20230925-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 23.1.7-1ubuntu1 (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2880x1800 c: Processor: AMD Ryzen 7 PRO 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: LENOVO 21K5001JUS (R2FET33W_0921_3 1.13 BIOS), Chipset: AMD Device 14e8, Memory: 60GB, Disk: 1024GB Kioxia KXG8AZNV1T02 LA, Graphics: AMD Phoenix1 4GB (2700/800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: Realtek RTL8111/8168/8411 + Qualcomm QCNFA765 OS: Ubuntu 23.10, Kernel: 6.6.0-060600rc3daily20230925-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 23.1.7-1ubuntu1 (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2880x1800 d: Processor: AMD Ryzen 7 PRO 7840U @ 5.13GHz (8 Cores / 16 Threads), Motherboard: LENOVO 21K5001JUS (R2FET33W_0921_3 1.13 BIOS), Chipset: AMD Device 14e8, Memory: 60GB, Disk: 1024GB Kioxia KXG8AZNV1T02 LA, Graphics: AMD Phoenix1 4GB (2700/800MHz), Audio: AMD Rembrandt Radeon HD Audio, Network: Realtek RTL8111/8168/8411 + Qualcomm QCNFA765 OS: Ubuntu 23.10, Kernel: 6.6.0-060600rc3daily20230925-generic (x86_64), Desktop: GNOME Shell 45.0, Display Server: X Server 1.21.1.7 + Wayland, OpenGL: 4.6 Mesa 23.1.7-1ubuntu1 (LLVM 15.0.7 DRM 3.54), Compiler: GCC 13.2.0, File-System: ext4, Screen Resolution: 2880x1800 Intel Open Image Denoise 2.1 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.34 |=================================================================== b . 0.35 |===================================================================== c . 0.35 |===================================================================== d . 0.35 |===================================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.94324 |================================================================ b . 1.99665 |================================================================== c . 1.95464 |================================================================= d . 1.98576 |================================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3.18072 |================================================================== b . 3.19218 |================================================================== c . 3.13402 |================================================================= d . 3.14058 |================================================================= oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 4.29743 |================================================================== b . 4.23611 |================================================================= c . 4.24044 |================================================================= d . 4.25029 |================================================================= oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 6.75565 |================================================================== b . 6.67639 |================================================================= c . 6.69421 |================================================================= d . 6.71290 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 8.51349 |================================================================= b . 8.56322 |================================================================== c . 8.55323 |================================================================== d . 8.61362 |================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 0.818099 |================================================================= b . 0.819625 |================================================================= c . 0.811225 |================================================================ d . 0.817453 |================================================================= oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3160.74 |================================================================== b . 3134.44 |================================================================= c . 3134.53 |================================================================= d . 3133.00 |================================================================= oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.07987 |================================================================== b . 1.07388 |================================================================== c . 1.07059 |================================================================= d . 1.07257 |================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 1.92435 |================================================================== b . 1.90959 |================================================================= c . 1.91197 |================================================================== d . 1.91816 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 3.43721 |================================================================== b . 3.44409 |================================================================== c . 3.42447 |================================================================== d . 3.44967 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 6.58725 |================================================================== b . 6.56318 |================================================================== c . 6.57380 |================================================================== d . 6.54052 |================================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 5.35016 |================================================================== b . 5.34274 |================================================================== c . 5.38079 |================================================================== d . 5.35442 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better a . 1627.94 |================================================================== b . 1636.80 |================================================================== c . 1626.44 |================================================================== d . 1628.76 |================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 9.52730 |================================================================== b . 9.54947 |================================================================== c . 9.51419 |================================================================== d . 9.49507 |================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 8.77897 |================================================================== b . 8.77743 |================================================================== c . 8.81113 |================================================================== d . 8.80582 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 5.34613 |================================================================== b . 5.35883 |================================================================== c . 5.34031 |================================================================== d . 5.35025 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 3138.66 |================================================================== b . 3129.39 |================================================================== c . 3127.87 |================================================================== d . 3136.41 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1.33215 |================================================================== b . 1.32836 |================================================================== c . 1.32943 |================================================================== d . 1.33136 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better a . 1627.61 |================================================================== b . 1624.01 |================================================================== c . 1623.47 |================================================================== d . 1623.59 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 3122.44 |================================================================== b . 3124.59 |================================================================== c . 3124.45 |================================================================== d . 3130.28 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better a . 1627.65 |================================================================== b . 1625.04 |================================================================== c . 1625.11 |================================================================== d . 1626.41 |================================================================== Intel Open Image Denoise 2.1 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.16 |===================================================================== b . 0.16 |===================================================================== c . 0.16 |===================================================================== d . 0.16 |===================================================================== Intel Open Image Denoise 2.1 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.34 |===================================================================== b . 0.34 |===================================================================== c . 0.34 |===================================================================== d . 0.34 |=====================================================================