Ryzen 3 3300X Xmas AMD Ryzen 3 3300X 4-Core testing with a MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS) and AMD FirePro V3800 512MB on Ubuntu 20.04 via the Phoronix Test Suite. 1: Processor: AMD Ryzen 3 3300X 4-Core @ 3.80GHz (4 Cores / 8 Threads), Motherboard: MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 256GB INTEL SSDPEKKW256G7, Graphics: AMD FirePro V3800 512MB, Audio: AMD Redwood HDMI Audio, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.9.0-rc5-14sep-patch (x86_64) 20200914, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 3.3 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 2: Processor: AMD Ryzen 3 3300X 4-Core @ 3.80GHz (4 Cores / 8 Threads), Motherboard: MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 256GB INTEL SSDPEKKW256G7, Graphics: AMD FirePro V3800 512MB, Audio: AMD Redwood HDMI Audio, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.9.0-rc5-14sep-patch (x86_64) 20200914, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 3.3 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: AMD Ryzen 3 3300X 4-Core @ 3.80GHz (4 Cores / 8 Threads), Motherboard: MSI B350M GAMING PRO (MS-7A39) v1.0 (2.NR BIOS), Chipset: AMD Starship/Matisse, Memory: 8GB, Disk: 256GB INTEL SSDPEKKW256G7, Graphics: AMD FirePro V3800 512MB, Audio: AMD Redwood HDMI Audio, Monitor: VA2431, Network: Realtek RTL8111/8168/8411 OS: Ubuntu 20.04, Kernel: 5.9.0-rc5-14sep-patch (x86_64) 20200914, Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 3.3 Mesa 20.0.8 (LLVM 10.0.0), Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 Unpacking The Linux Kernel linux-4.15.tar.xz Seconds < Lower Is Better 1 . 4.944 |==================================================================== 2 . 4.931 |==================================================================== 3 . 4.937 |==================================================================== CLOMP 1.2 Static OMP Speedup Speedup > Higher Is Better 1 . 3.2 |====================================================================== 2 . 3.0 |================================================================== 3 . 3.1 |==================================================================== Timed HMMer Search 3.3.1 Pfam Database Search Seconds < Lower Is Better 1 . 103.42 |=================================================================== 2 . 103.28 |=================================================================== 3 . 103.10 |=================================================================== simdjson 0.7.1 Throughput Test: Kostya GB/s > Higher Is Better 1 . 0.60 |===================================================================== 2 . 0.60 |===================================================================== 3 . 0.59 |==================================================================== simdjson 0.7.1 Throughput Test: LargeRandom GB/s > Higher Is Better 1 . 0.43 |===================================================================== 2 . 0.43 |===================================================================== 3 . 0.43 |===================================================================== simdjson 0.7.1 Throughput Test: PartialTweets GB/s > Higher Is Better 1 . 0.68 |==================================================================== 2 . 0.69 |===================================================================== 3 . 0.68 |==================================================================== simdjson 0.7.1 Throughput Test: DistinctUserID GB/s > Higher Is Better 1 . 0.70 |===================================================================== 2 . 0.69 |==================================================================== 3 . 0.70 |===================================================================== oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 6.84371 |================================================================== 2 . 6.86396 |================================================================== 3 . 6.76855 |================================================================= oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 8.52111 |========================================================= 2 . 9.81054 |================================================================== 3 . 7.80639 |===================================================== oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.92904 |================================================================== 2 . 4.96126 |================================================================== 3 . 4.89977 |================================================================= oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.50766 |=============================================================== 2 . 2.64117 |================================================================== 3 . 2.40369 |============================================================ oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 21.25 |=================================================================== 2 . 21.60 |==================================================================== 3 . 20.95 |================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 9.12080 |================================================================== 2 . 9.16172 |================================================================== 3 . 9.09468 |================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 11.41 |==================================================================== 2 . 11.43 |==================================================================== 3 . 11.35 |==================================================================== oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 21.88 |================================================================== 2 . 22.65 |==================================================================== 3 . 22.00 |================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 11.38 |=================================================================== 2 . 11.51 |==================================================================== 3 . 11.36 |=================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 9.98594 |================================================================= 2 . 10.02125 |================================================================= 3 . 9.96837 |================================================================= oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 5947.85 |================================================================= 2 . 5999.78 |================================================================== 3 . 5934.31 |================================================================= oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3081.19 |================================================================= 2 . 3106.43 |================================================================== 3 . 3058.79 |================================================================= oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 5994.08 |================================================================== 2 . 6027.19 |================================================================== 3 . 5977.34 |================================================================= oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 3080.42 |========================== 2 . 3114.00 |========================== 3 . 7762.44 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 4.75671 |=============================================================== 2 . 4.90760 |================================================================ 3 . 5.02241 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 5991.49 |================================================================== 2 . 6018.26 |================================================================== 3 . 6010.57 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 3093.57 |================================================================== 2 . 3114.62 |================================================================== 3 . 3101.65 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 5.72711 |================================================================= 2 . 5.76708 |================================================================== 3 . 5.79035 |================================================================== rav1e 0.4 Alpha Speed: 1 Frames Per Second > Higher Is Better 1 . 0.387 |=================================================================== 2 . 0.390 |=================================================================== 3 . 0.394 |==================================================================== rav1e 0.4 Alpha Speed: 5 Frames Per Second > Higher Is Better 1 . 1.163 |==================================================================== 2 . 1.146 |=================================================================== 3 . 1.156 |==================================================================== rav1e 0.4 Alpha Speed: 6 Frames Per Second > Higher Is Better 1 . 1.542 |==================================================================== 2 . 1.553 |==================================================================== 3 . 1.551 |==================================================================== rav1e 0.4 Alpha Speed: 10 Frames Per Second > Higher Is Better 1 . 3.469 |==================================================================== 2 . 3.483 |==================================================================== 3 . 3.486 |==================================================================== Coremark 1.0 CoreMark Size 666 - Iterations Per Second Iterations/Sec > Higher Is Better 1 . 182448.28 |================================================================ 2 . 180553.02 |=============================================================== 3 . 181403.67 |================================================================ Stockfish 12 Total Time Nodes Per Second > Higher Is Better 1 . 10378430 |================================================================= 2 . 10313214 |================================================================= 3 . 10202806 |================================================================ asmFish 2018-07-23 1024 Hash Memory, 26 Depth Nodes/second > Higher Is Better 1 . 14970912 |================================================================= 2 . 15051454 |================================================================= 3 . 15000176 |================================================================= Timed Clash Compilation Time To Compile Seconds < Lower Is Better 1 . 242.93 |=================================================================== 2 . 241.83 |=================================================================== 3 . 242.57 |=================================================================== Timed FFmpeg Compilation 4.2.2 Time To Compile Seconds < Lower Is Better 1 . 94.31 |==================================================================== 2 . 94.69 |==================================================================== 3 . 94.43 |==================================================================== Build2 0.13 Time To Compile Seconds < Lower Is Better 1 . 211.75 |=================================================================== 2 . 205.35 |================================================================= 3 . 206.09 |================================================================= Timed Eigen Compilation 3.3.9 Time To Compile Seconds < Lower Is Better 1 . 72.83 |==================================================================== 2 . 73.10 |==================================================================== 3 . 73.18 |==================================================================== Monkey Audio Encoding 3.99.6 WAV To APE Seconds < Lower Is Better 1 . 11.55 |==================================================================== 2 . 11.53 |==================================================================== 3 . 11.54 |==================================================================== Opus Codec Encoding 1.3.1 WAV To Opus Encode Seconds < Lower Is Better 1 . 7.180 |==================================================================== 2 . 7.160 |==================================================================== 3 . 7.157 |==================================================================== Node.js V8 Web Tooling Benchmark runs/s > Higher Is Better 1 . 12.57 |==================================================================== 2 . 12.23 |================================================================== 3 . 12.50 |==================================================================== ASTC Encoder 2.0 Preset: Fast Seconds < Lower Is Better 1 . 7.47 |===================================================================== 2 . 7.50 |===================================================================== 3 . 7.46 |===================================================================== ASTC Encoder 2.0 Preset: Medium Seconds < Lower Is Better 1 . 8.32 |===================================================================== 2 . 8.32 |===================================================================== 3 . 8.32 |===================================================================== ASTC Encoder 2.0 Preset: Thorough Seconds < Lower Is Better 1 . 50.94 |==================================================================== 2 . 50.96 |==================================================================== 3 . 50.93 |==================================================================== ASTC Encoder 2.0 Preset: Exhaustive Seconds < Lower Is Better 1 . 410.74 |=================================================================== 2 . 411.15 |=================================================================== 3 . 410.20 |=================================================================== SQLite Speedtest 3.30 Timed Time - Size 1,000 Seconds < Lower Is Better 1 . 57.69 |==================================================================== 2 . 58.04 |==================================================================== 3 . 57.87 |==================================================================== NCNN 20201218 Target: CPU - Model: mobilenet ms < Lower Is Better 1 . 20.84 |=================================================================== 2 . 20.74 |=================================================================== 3 . 21.06 |==================================================================== NCNN 20201218 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 5.35 |==================================================================== 2 . 5.41 |===================================================================== 3 . 5.21 |================================================================== NCNN 20201218 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 4.53 |=================================================================== 2 . 4.69 |===================================================================== 3 . 4.60 |==================================================================== NCNN 20201218 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 8.05 |=================================================================== 2 . 8.25 |===================================================================== 3 . 8.03 |=================================================================== NCNN 20201218 Target: CPU - Model: mnasnet ms < Lower Is Better 1 . 4.89 |===================================================================== 2 . 4.89 |===================================================================== 3 . 4.91 |===================================================================== NCNN 20201218 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 7.62 |==================================================================== 2 . 7.77 |===================================================================== 3 . 7.54 |=================================================================== NCNN 20201218 Target: CPU - Model: blazeface ms < Lower Is Better 1 . 2.27 |===================================================================== 2 . 2.15 |================================================================= 3 . 2.20 |=================================================================== NCNN 20201218 Target: CPU - Model: googlenet ms < Lower Is Better 1 . 15.30 |================================================================= 2 . 15.94 |==================================================================== 3 . 15.78 |=================================================================== NCNN 20201218 Target: CPU - Model: vgg16 ms < Lower Is Better 1 . 65.70 |==================================================================== 2 . 66.06 |==================================================================== 3 . 66.12 |==================================================================== NCNN 20201218 Target: CPU - Model: resnet18 ms < Lower Is Better 1 . 15.82 |==================================================================== 2 . 15.70 |=================================================================== 3 . 15.86 |==================================================================== NCNN 20201218 Target: CPU - Model: alexnet ms < Lower Is Better 1 . 14.45 |=================================================================== 2 . 14.58 |==================================================================== 3 . 14.46 |=================================================================== NCNN 20201218 Target: CPU - Model: resnet50 ms < Lower Is Better 1 . 33.67 |==================================================================== 2 . 33.77 |==================================================================== 3 . 33.77 |==================================================================== NCNN 20201218 Target: CPU - Model: yolov4-tiny ms < Lower Is Better 1 . 28.30 |=================================================================== 2 . 28.59 |==================================================================== 3 . 28.46 |==================================================================== NCNN 20201218 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better 1 . 27.10 |==================================================================== 2 . 27.13 |==================================================================== 3 . 27.01 |==================================================================== NCNN 20201218 Target: CPU - Model: regnety_400m ms < Lower Is Better 1 . 10.85 |=================================================================== 2 . 10.98 |==================================================================== 3 . 11.02 |==================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU FPS > Higher Is Better 1 . 1.27 |===================================================================== 2 . 1.27 |===================================================================== 3 . 1.27 |===================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP16 - Device: CPU ms < Lower Is Better 1 . 3131.88 |================================================================= 2 . 3165.51 |================================================================== 3 . 3149.60 |================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU FPS > Higher Is Better 1 . 1.26 |==================================================================== 2 . 1.26 |==================================================================== 3 . 1.28 |===================================================================== OpenVINO 2021.1 Model: Face Detection 0106 FP32 - Device: CPU ms < Lower Is Better 1 . 3187.96 |================================================================== 2 . 3178.77 |================================================================== 3 . 3167.39 |================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU FPS > Higher Is Better 1 . 0.88 |===================================================================== 2 . 0.88 |===================================================================== 3 . 0.88 |===================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP16 - Device: CPU ms < Lower Is Better 1 . 4532.98 |================================================================== 2 . 4536.61 |================================================================== 3 . 4506.69 |================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU FPS > Higher Is Better 1 . 0.87 |===================================================================== 2 . 0.87 |===================================================================== 3 . 0.87 |===================================================================== OpenVINO 2021.1 Model: Person Detection 0106 FP32 - Device: CPU ms < Lower Is Better 1 . 4567.40 |================================================================== 2 . 4557.65 |================================================================== 3 . 4562.87 |================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better 1 . 3955.38 |================================================================= 2 . 3992.29 |================================================================== 3 . 3937.05 |================================================================= OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better 1 . 1.00 |==================================================================== 2 . 0.99 |==================================================================== 3 . 1.01 |===================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU FPS > Higher Is Better 1 . 3893.18 |================================================================= 2 . 3962.81 |================================================================== 3 . 3973.20 |================================================================== OpenVINO 2021.1 Model: Age Gender Recognition Retail 0013 FP32 - Device: CPU ms < Lower Is Better 1 . 1.02 |===================================================================== 2 . 1.00 |==================================================================== 3 . 0.99 |=================================================================== PHPBench 0.8.1 PHP Benchmark Suite Score > Higher Is Better 1 . 671321 |================================================================== 2 . 678566 |=================================================================== 3 . 678009 |=================================================================== WavPack Audio Encoding 5.3 WAV To WavPack Seconds < Lower Is Better 1 . 12.38 |==================================================================== 2 . 12.41 |==================================================================== 3 . 12.39 |==================================================================== Unpacking Firefox 84.0 Extracting: firefox-84.0.source.tar.xz Seconds < Lower Is Better 1 . 17.50 |==================================================================== 2 . 17.46 |==================================================================== 3 . 17.42 |==================================================================== BRL-CAD 7.30.8 VGR Performance Metric VGR Performance Metric > Higher Is Better 1 . 66712 |==================================================================== 2 . 66332 |=================================================================== 3 . 66953 |====================================================================