3300X New 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 LeelaChessZero 0.26 Backend: BLAS Nodes Per Second > Higher Is Better 1 . 688 |============================================================= 2 . 666 |=========================================================== 3 . 791 |====================================================================== LeelaChessZero 0.26 Backend: Eigen Nodes Per Second > Higher Is Better 1 . 665 |=============================================================== 2 . 712 |==================================================================== 3 . 734 |====================================================================== LeelaChessZero 0.26 Backend: Random Nodes Per Second > Higher Is Better 1 . 227920 |=================================================================== 2 . 227389 |=================================================================== 3 . 227721 |=================================================================== NAMD 2.14 ATPase Simulation - 327,506 Atoms days/ns < Lower Is Better 1 . 4.31075 |================================================================== 2 . 4.30607 |================================================================== 3 . 4.31865 |================================================================== Dolfyn 0.527 Computational Fluid Dynamics Seconds < Lower Is Better 1 . 16.33 |==================================================================== 2 . 16.34 |==================================================================== 3 . 16.37 |==================================================================== FFTE 7.0 N=256, 3D Complex FFT Routine MFLOPS > Higher Is Better 1 . 25965.40 |================================================================= 2 . 25833.14 |================================================================= 3 . 25987.24 |================================================================= Timed HMMer Search 3.3.1 Pfam Database Search Seconds < Lower Is Better 1 . 103.71 |=================================================================== 2 . 103.50 |=================================================================== 3 . 104.01 |=================================================================== WebP Image Encode 1.1 Encode Settings: Default Encode Time - Seconds < Lower Is Better 1 . 1.472 |==================================================================== 2 . 1.469 |==================================================================== 3 . 1.475 |==================================================================== WebP Image Encode 1.1 Encode Settings: Quality 100 Encode Time - Seconds < Lower Is Better 1 . 2.243 |==================================================================== 2 . 2.248 |==================================================================== 3 . 2.244 |==================================================================== WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless Encode Time - Seconds < Lower Is Better 1 . 16.05 |==================================================================== 2 . 15.94 |=================================================================== 3 . 16.07 |==================================================================== WebP Image Encode 1.1 Encode Settings: Quality 100, Highest Compression Encode Time - Seconds < Lower Is Better 1 . 6.967 |==================================================================== 2 . 6.980 |==================================================================== 3 . 6.955 |==================================================================== WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless, Highest Compression Encode Time - Seconds < Lower Is Better 1 . 34.09 |=================================================================== 2 . 33.93 |=================================================================== 3 . 34.37 |==================================================================== BYTE Unix Benchmark 3.6 Computational Test: Dhrystone 2 LPS > Higher Is Better 1 . 46642879.6 |=============================================================== 2 . 46044154.4 |============================================================== 3 . 45708214.7 |============================================================== LibRaw 0.20 Post-Processing Benchmark Mpix/sec > Higher Is Better 1 . 30.74 |==================================================================== 2 . 30.88 |==================================================================== 3 . 30.69 |==================================================================== eSpeak-NG Speech Engine 20200907 Text-To-Speech Synthesis Seconds < Lower Is Better 1 . 28.14 |=================================================================== 2 . 28.46 |==================================================================== 3 . 28.62 |==================================================================== MPV Video Input: Big Buck Bunny Sunflower 4K - Decode: Software Only FPS > Higher Is Better 1 . 175.59 |=================================================================== 2 . 175.95 |=================================================================== 3 . 175.75 |=================================================================== MPV Video Input: Big Buck Bunny Sunflower 1080p - Decode: Software Only FPS > Higher Is Better 1 . 319.43 |=================================================================== 2 . 319.12 |=================================================================== 3 . 319.18 |=================================================================== Apache CouchDB 3.1.1 Bulk Size: 100 - Inserts: 1000 - Rounds: 24 Seconds < Lower Is Better 1 . 112.67 |================================================================== 2 . 112.81 |================================================================== 3 . 113.84 |=================================================================== GROMACS 2020.3 Water Benchmark Ns Per Day > Higher Is Better 1 . 0.559 |==================================================================== 2 . 0.555 |=================================================================== 3 . 0.560 |==================================================================== Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 100 Milli-Seconds < Lower Is Better 1 . 37854 |==================================================================== 2 . 38104 |==================================================================== 3 . 37907 |==================================================================== Caffe 2020-02-13 Model: AlexNet - Acceleration: CPU - Iterations: 200 Milli-Seconds < Lower Is Better 1 . 75727 |=================================================================== 2 . 76423 |==================================================================== 3 . 75699 |=================================================================== Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 100 Milli-Seconds < Lower Is Better 1 . 98610 |==================================================================== 2 . 98759 |==================================================================== 3 . 98742 |==================================================================== Caffe 2020-02-13 Model: GoogleNet - Acceleration: CPU - Iterations: 200 Milli-Seconds < Lower Is Better 1 . 197252 |=================================================================== 2 . 198462 |=================================================================== 3 . 197955 |=================================================================== NCNN 20200916 Target: CPU - Model: squeezenet ms < Lower Is Better 1 . 19.81 |==================================================================== 2 . 19.89 |==================================================================== 3 . 19.72 |=================================================================== NCNN 20200916 Target: CPU - Model: mobilenet ms < Lower Is Better 1 . 20.89 |=================================================================== 2 . 21.13 |==================================================================== 3 . 20.94 |=================================================================== NCNN 20200916 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 5.39 |=================================================================== 2 . 5.51 |===================================================================== 3 . 5.43 |==================================================================== NCNN 20200916 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 4.86 |===================================================================== 2 . 4.76 |==================================================================== 3 . 4.74 |=================================================================== NCNN 20200916 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 3.20 |===================================================================== 2 . 3.18 |===================================================================== 3 . 3.18 |===================================================================== NCNN 20200916 Target: CPU - Model: mnasnet ms < Lower Is Better 1 . 5.05 |===================================================================== 2 . 5.04 |===================================================================== 3 . 4.90 |=================================================================== NCNN 20200916 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 7.66 |==================================================================== 2 . 7.66 |==================================================================== 3 . 7.81 |===================================================================== NCNN 20200916 Target: CPU - Model: blazeface ms < Lower Is Better 1 . 1.47 |=================================================================== 2 . 1.52 |===================================================================== 3 . 1.52 |===================================================================== NCNN 20200916 Target: CPU - Model: googlenet ms < Lower Is Better 1 . 16.91 |==================================================================== 2 . 16.84 |=================================================================== 3 . 17.02 |==================================================================== NCNN 20200916 Target: CPU - Model: vgg16 ms < Lower Is Better 1 . 70.04 |==================================================================== 2 . 70.33 |==================================================================== 3 . 70.27 |==================================================================== NCNN 20200916 Target: CPU - Model: resnet18 ms < Lower Is Better 1 . 16.57 |==================================================================== 2 . 16.54 |==================================================================== 3 . 16.57 |==================================================================== NCNN 20200916 Target: CPU - Model: alexnet ms < Lower Is Better 1 . 17.92 |================================================================== 2 . 18.36 |==================================================================== 3 . 18.08 |=================================================================== NCNN 20200916 Target: CPU - Model: resnet50 ms < Lower Is Better 1 . 33.84 |==================================================================== 2 . 34.08 |==================================================================== 3 . 33.85 |==================================================================== NCNN 20200916 Target: CPU - Model: yolov4-tiny ms < Lower Is Better 1 . 29.70 |=================================================================== 2 . 29.87 |==================================================================== 3 . 29.97 |==================================================================== TNN 0.2.3 Target: CPU - Model: MobileNet v2 ms < Lower Is Better 1 . 250.39 |=================================================================== 2 . 249.96 |=================================================================== 3 . 250.39 |=================================================================== TNN 0.2.3 Target: CPU - Model: SqueezeNet v1.1 ms < Lower Is Better 1 . 240.73 |=================================================================== 2 . 238.71 |================================================================== 3 . 239.06 |=================================================================== Hierarchical INTegration 1.0 Test: FLOAT QUIPs > Higher Is Better 1 . 379856539.78 |============================================================= 2 . 379820315.57 |============================================================= 3 . 380134502.20 |============================================================= Mlpack Benchmark Benchmark: scikit_ica Seconds < Lower Is Better 1 . 53.35 |=================================================================== 2 . 53.23 |=================================================================== 3 . 53.99 |==================================================================== Mlpack Benchmark Benchmark: scikit_qda Seconds < Lower Is Better 1 . 66.42 |==================================================================== 2 . 66.75 |==================================================================== 3 . 65.90 |=================================================================== Mlpack Benchmark Benchmark: scikit_svm Seconds < Lower Is Better 1 . 19.40 |==================================================================== 2 . 19.49 |==================================================================== 3 . 19.44 |==================================================================== Mlpack Benchmark Benchmark: scikit_linearridgeregression Seconds < Lower Is Better 1 . 3.04 |===================================================================== 2 . 3.02 |===================================================================== 3 . 3.03 |===================================================================== OpenCV 4.4 Test: DNN - Deep Neural Network ms < Lower Is Better 1 . 4079 |================================================================== 2 . 4287 |===================================================================== 3 . 4287 |===================================================================== InfluxDB 1.8.2 Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 val/sec > Higher Is Better 1 . 1148083.7 |================================================================ 2 . 1154741.0 |================================================================ 3 . 1135241.1 |=============================================================== InfluxDB 1.8.2 Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 val/sec > Higher Is Better 1 . 1215926.1 |================================================================ 2 . 1214667.8 |================================================================ 3 . 1213725.5 |================================================================ InfluxDB 1.8.2 Concurrent Streams: 1024 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 val/sec > Higher Is Better 1 . 1235812.2 |================================================================ 2 . 1234016.6 |================================================================ 3 . 1231834.8 |================================================================