Xeon Silver March Intel Xeon Silver 4216 testing with a TYAN S7100AG2NR (V4.02 BIOS) and ASPEED on Debian 10 via the Phoronix Test Suite. 1: Processor: Intel Xeon Silver 4216 @ 3.20GHz (16 Cores / 32 Threads), Motherboard: TYAN S7100AG2NR (V4.02 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 24GB, Disk: 240GB Corsair Force MP500, Graphics: ASPEED, Audio: Realtek ALC892, Network: 2 x Intel I350 OS: Debian 10, Kernel: 4.19.0-9-amd64 (x86_64), Desktop: GNOME Shell 3.30.2, Display Server: X Server, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 1024x768 2: Processor: Intel Xeon Silver 4216 @ 3.20GHz (16 Cores / 32 Threads), Motherboard: TYAN S7100AG2NR (V4.02 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 24GB, Disk: 240GB Corsair Force MP500, Graphics: ASPEED, Audio: Realtek ALC892, Network: 2 x Intel I350 OS: Debian 10, Kernel: 4.19.0-9-amd64 (x86_64), Desktop: GNOME Shell 3.30.2, Display Server: X Server, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 1024x768 3: Processor: Intel Xeon Silver 4216 @ 3.20GHz (16 Cores / 32 Threads), Motherboard: TYAN S7100AG2NR (V4.02 BIOS), Chipset: Intel Sky Lake-E DMI3 Registers, Memory: 24GB, Disk: 240GB Corsair Force MP500, Graphics: ASPEED, Audio: Realtek ALC892, Network: 2 x Intel I350 OS: Debian 10, Kernel: 4.19.0-9-amd64 (x86_64), Desktop: GNOME Shell 3.30.2, Display Server: X Server, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 1024x768 Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 129 Cells Per Direction Seconds < Lower Is Better 1 . 16.70 |=================================================================== 2 . 16.85 |==================================================================== 3 . 16.86 |==================================================================== Xcompact3d Incompact3d 2021-03-11 Input: input.i3d 193 Cells Per Direction Seconds < Lower Is Better 1 . 66.45 |==================================================================== 2 . 66.67 |==================================================================== 3 . 66.16 |=================================================================== simdjson 0.8.2 Throughput Test: Kostya GB/s > Higher Is Better 1 . 1.13 |===================================================================== 2 . 1.12 |==================================================================== 3 . 1.13 |===================================================================== simdjson 0.8.2 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 0.38 |===================================================================== 2 . 0.38 |===================================================================== 3 . 0.38 |===================================================================== simdjson 0.8.2 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 1.37 |===================================================================== 2 . 1.37 |===================================================================== 3 . 1.36 |==================================================================== simdjson 0.8.2 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 1.48 |===================================================================== 2 . 1.48 |===================================================================== 3 . 1.48 |===================================================================== LuaRadio 0.9.1 Test: Five Back to Back FIR Filters MiB/s > Higher Is Better 1 . 808.6 |==================================================================== 2 . 807.8 |==================================================================== 3 . 810.2 |==================================================================== LuaRadio 0.9.1 Test: FM Deemphasis Filter MiB/s > Higher Is Better 1 . 254.2 |==================================================================== 2 . 254.0 |==================================================================== 3 . 253.3 |==================================================================== LuaRadio 0.9.1 Test: Hilbert Transform MiB/s > Higher Is Better 1 . 55.4 |===================================================================== 2 . 55.4 |===================================================================== 3 . 55.4 |===================================================================== LuaRadio 0.9.1 Test: Complex Phase MiB/s > Higher Is Better 1 . 434.1 |=================================================================== 2 . 438.2 |==================================================================== 3 . 439.2 |==================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 0 Two-Pass Frames Per Second > Higher Is Better 1 . 0.21 |===================================================================== 2 . 0.20 |================================================================== 3 . 0.21 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 4 Two-Pass Frames Per Second > Higher Is Better 1 . 3.77 |===================================================================== 2 . 3.77 |===================================================================== 3 . 3.76 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Realtime Frames Per Second > Higher Is Better 1 . 11.76 |==================================================================== 2 . 11.68 |==================================================================== 3 . 11.70 |==================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 6 Two-Pass Frames Per Second > Higher Is Better 1 . 9.29 |===================================================================== 2 . 9.31 |===================================================================== 3 . 9.31 |===================================================================== AOM AV1 2.1-rc Encoder Mode: Speed 8 Realtime Frames Per Second > Higher Is Better 1 . 30.06 |==================================================================== 2 . 30.00 |==================================================================== 3 . 29.64 |=================================================================== SVT-HEVC 1.5.0 Tuning: 1 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 7.88 |===================================================================== 2 . 7.86 |===================================================================== 3 . 7.89 |===================================================================== SVT-HEVC 1.5.0 Tuning: 7 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 120.65 |=================================================================== 2 . 121.08 |=================================================================== 3 . 120.93 |=================================================================== SVT-HEVC 1.5.0 Tuning: 10 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 258.29 |=================================================================== 2 . 257.29 |=================================================================== 3 . 255.87 |================================================================== SVT-VP9 0.3 Tuning: VMAF Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 216.44 |================================================================== 2 . 218.37 |=================================================================== 3 . 219.08 |=================================================================== SVT-VP9 0.3 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 221.50 |=================================================================== 2 . 221.91 |=================================================================== 3 . 222.05 |=================================================================== SVT-VP9 0.3 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p Frames Per Second > Higher Is Better 1 . 169.62 |=================================================================== 2 . 169.81 |=================================================================== 3 . 170.48 |=================================================================== Stockfish 13 Total Time Nodes Per Second > Higher Is Better 1 . 31665033 |================================================================= 2 . 31089824 |================================================================ 3 . 31357896 |================================================================ oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 4.75486 |================================================================== 2 . 4.74640 |================================================================== 3 . 4.74045 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3.93294 |================================================================== 2 . 3.85096 |================================================================= 3 . 3.91852 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1.05123 |================================================================== 2 . 1.04921 |================================================================== 3 . 1.04890 |================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1.45952 |================================================================== 2 . 1.42021 |================================================================ 3 . 1.44027 |================================================================= oneDNN 2.1.2 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 10.60 |==================================================================== 2 . 10.59 |==================================================================== 3 . 10.59 |==================================================================== oneDNN 2.1.2 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 3.12486 |================================================================== 2 . 3.12458 |================================================================== 3 . 3.13052 |================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 6.57468 |================================================================== 2 . 6.51645 |================================================================= 3 . 6.55537 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 11.76 |==================================================================== 2 . 11.75 |==================================================================== 3 . 11.78 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 7.65076 |================================================================== 2 . 7.64752 |================================================================== 3 . 7.63646 |================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 6.39957 |================================================================== 2 . 6.21612 |================================================================ 3 . 6.16607 |================================================================ oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1.26827 |================================================================== 2 . 1.27125 |================================================================== 3 . 1.27234 |================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1.88615 |================================================================== 2 . 1.88395 |================================================================== 3 . 1.88619 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3586.70 |================================================================== 2 . 3588.58 |================================================================== 3 . 3592.55 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 1859.12 |================================================================== 2 . 1856.49 |================================================================== 3 . 1854.28 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3589.87 |================================================================== 2 . 3589.97 |================================================================== 3 . 3592.30 |================================================================== oneDNN 2.1.2 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 16.28 |==================================================================== 2 . 16.29 |==================================================================== 3 . 16.28 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 18.43 |==================================================================== 2 . 18.43 |==================================================================== 3 . 18.44 |==================================================================== oneDNN 2.1.2 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 21.77 |==================================================================== 2 . 21.77 |==================================================================== 3 . 21.78 |==================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1852.81 |================================================================== 2 . 1853.80 |================================================================== 3 . 1852.34 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 1.61069 |================================================================== 2 . 1.61866 |================================================================== 3 . 1.60482 |================================================================= oneDNN 2.1.2 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 3589.54 |================================================================== 2 . 3593.32 |================================================================== 3 . 3588.05 |================================================================== oneDNN 2.1.2 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 1853.05 |================================================================== 2 . 1853.25 |================================================================== 3 . 1855.59 |================================================================== oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 0.833192 |================================================================= 2 . 0.834428 |================================================================= 3 . 0.830736 |================================================================= oneDNN 2.1.2 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 3.56301 |================================================================== 2 . 3.56246 |================================================================== 3 . 3.56446 |================================================================== Basis Universal 1.13 Settings: ETC1S Seconds < Lower Is Better 1 . 32.71 |==================================================================== 2 . 32.66 |==================================================================== 3 . 32.61 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 0 Seconds < Lower Is Better 1 . 10.08 |==================================================================== 2 . 10.07 |==================================================================== 3 . 10.07 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 2 Seconds < Lower Is Better 1 . 31.89 |==================================================================== 2 . 31.87 |==================================================================== 3 . 31.87 |==================================================================== Basis Universal 1.13 Settings: UASTC Level 3 Seconds < Lower Is Better 1 . 57.17 |==================================================================== 2 . 57.19 |==================================================================== 3 . 57.06 |==================================================================== Mobile Neural Network 1.1.3 Model: SqueezeNetV1.0 ms < Lower Is Better 1 . 8.133 |=================================================================== 2 . 8.130 |=================================================================== 3 . 8.236 |==================================================================== Mobile Neural Network 1.1.3 Model: resnet-v2-50 ms < Lower Is Better 1 . 43.66 |=================================================================== 2 . 43.99 |==================================================================== 3 . 44.23 |==================================================================== Mobile Neural Network 1.1.3 Model: MobileNetV2_224 ms < Lower Is Better 1 . 5.038 |=================================================================== 2 . 5.095 |==================================================================== 3 . 5.099 |==================================================================== Mobile Neural Network 1.1.3 Model: mobilenet-v1-1.0 ms < Lower Is Better 1 . 3.265 |=================================================================== 2 . 3.227 |=================================================================== 3 . 3.292 |==================================================================== Mobile Neural Network 1.1.3 Model: inception-v3 ms < Lower Is Better 1 . 55.10 |==================================================================== 2 . 54.55 |=================================================================== 3 . 54.09 |=================================================================== Sysbench 1.0.20 Test: RAM / Memory MiB/sec > Higher Is Better 1 . 15699.71 |================================================================= 2 . 15632.40 |================================================================= 3 . 15678.47 |================================================================= Sysbench 1.0.20 Test: CPU Events Per Second > Higher Is Better 1 . 22943.61 |================================================================= 2 . 22942.83 |================================================================= 3 . 22943.20 |=================================================================