Xeon E3 v6 Intel Xeon E3-1275 v6 testing with a ASUS P10S-M WS (4401 BIOS) and Intel HD P630 3GB on Ubuntu 20.04 via the Phoronix Test Suite. 1: Processor: Intel Xeon E3-1275 v6 @ 4.20GHz (4 Cores / 8 Threads), Motherboard: ASUS P10S-M WS (4401 BIOS), Chipset: Intel Xeon E3-1200 v6/7th, Memory: 16GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: Intel HD P630 3GB (1150MHz), Audio: Realtek ALC1150, Monitor: DELL S2409W, Network: 2 x Intel I210 OS: Ubuntu 20.04, Kernel: 5.4.0-47-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.4, OpenCL: OpenCL 2.1, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 2: Processor: Intel Xeon E3-1275 v6 @ 4.20GHz (4 Cores / 8 Threads), Motherboard: ASUS P10S-M WS (4401 BIOS), Chipset: Intel Xeon E3-1200 v6/7th, Memory: 16GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: Intel HD P630 3GB (1150MHz), Audio: Realtek ALC1150, Monitor: DELL S2409W, Network: 2 x Intel I210 OS: Ubuntu 20.04, Kernel: 5.4.0-47-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.4, OpenCL: OpenCL 2.1, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: Intel Xeon E3-1275 v6 @ 4.20GHz (4 Cores / 8 Threads), Motherboard: ASUS P10S-M WS (4401 BIOS), Chipset: Intel Xeon E3-1200 v6/7th, Memory: 16GB, Disk: Samsung SSD 970 EVO Plus 500GB, Graphics: Intel HD P630 3GB (1150MHz), Audio: Realtek ALC1150, Monitor: DELL S2409W, Network: 2 x Intel I210 OS: Ubuntu 20.04, Kernel: 5.4.0-47-generic (x86_64), Desktop: GNOME Shell 3.36.4, Display Server: X Server 1.20.8, Display Driver: modesetting 1.20.8, OpenGL: 4.6 Mesa 20.0.4, OpenCL: OpenCL 2.1, Compiler: GCC 9.3.0, File-System: ext4, Screen Resolution: 1920x1080 RealSR-NCNN 20200818 Scale: 4x - TAA: No Seconds < Lower Is Better 1 . 26.67 |============================================================ 2 . 30.18 |==================================================================== 3 . 29.74 |=================================================================== WebP Image Encode 1.1 Encode Settings: Default Encode Time - Seconds < Lower Is Better 1 . 1.618 |==================================================================== 2 . 1.622 |==================================================================== 3 . 1.615 |==================================================================== WebP Image Encode 1.1 Encode Settings: Quality 100 Encode Time - Seconds < Lower Is Better 1 . 2.536 |==================================================================== 2 . 2.539 |==================================================================== 3 . 2.530 |==================================================================== WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless Encode Time - Seconds < Lower Is Better 1 . 18.19 |==================================================================== 2 . 17.97 |=================================================================== 3 . 18.07 |==================================================================== WebP Image Encode 1.1 Encode Settings: Quality 100, Highest Compression Encode Time - Seconds < Lower Is Better 1 . 7.549 |==================================================================== 2 . 7.553 |==================================================================== 3 . 7.552 |==================================================================== WebP Image Encode 1.1 Encode Settings: Quality 100, Lossless, Highest Compression Encode Time - Seconds < Lower Is Better 1 . 44.00 |==================================================================== 2 . 44.05 |==================================================================== 3 . 44.15 |==================================================================== LibRaw 0.20 Post-Processing Benchmark Mpix/sec > Higher Is Better 1 . 30.31 |==================================================================== 2 . 30.30 |==================================================================== 3 . 30.22 |==================================================================== dcraw RAW To PPM Image Conversion Seconds < Lower Is Better 1 . 39.80 |==================================================================== 2 . 39.73 |==================================================================== 3 . 39.75 |==================================================================== eSpeak-NG Speech Engine 20200907 Text-To-Speech Synthesis Seconds < Lower Is Better 1 . 28.64 |==================================================================== 2 . 28.77 |==================================================================== 3 . 28.65 |==================================================================== MPV Video Input: Big Buck Bunny Sunflower 4K - Decode: Software Only FPS > Higher Is Better 1 . 86.40 |==================================================================== 2 . 86.19 |==================================================================== 3 . 86.53 |==================================================================== MPV Video Input: Big Buck Bunny Sunflower 1080p - Decode: Software Only FPS > Higher Is Better 1 . 243.18 |=================================================================== 2 . 241.47 |=================================================================== 3 . 242.87 |=================================================================== NCNN 20200916 Target: CPU - Model: squeezenet ms < Lower Is Better 1 . 22.43 |=================================================================== 2 . 22.55 |==================================================================== 3 . 22.65 |==================================================================== NCNN 20200916 Target: CPU - Model: mobilenet ms < Lower Is Better 1 . 26.11 |==================================================================== 2 . 26.18 |==================================================================== 3 . 26.19 |==================================================================== NCNN 20200916 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 7.03 |===================================================================== 2 . 7.03 |===================================================================== 3 . 7.06 |===================================================================== NCNN 20200916 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 5.82 |===================================================================== 2 . 5.81 |===================================================================== 3 . 5.82 |===================================================================== NCNN 20200916 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 4.13 |===================================================================== 2 . 4.13 |===================================================================== 3 . 4.16 |===================================================================== NCNN 20200916 Target: CPU - Model: mnasnet ms < Lower Is Better 1 . 5.94 |===================================================================== 2 . 5.94 |===================================================================== 3 . 5.95 |===================================================================== NCNN 20200916 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 9.44 |==================================================================== 2 . 9.48 |===================================================================== 3 . 9.53 |===================================================================== NCNN 20200916 Target: CPU - Model: blazeface ms < Lower Is Better 1 . 1.93 |==================================================================== 2 . 1.95 |===================================================================== 3 . 1.96 |===================================================================== NCNN 20200916 Target: CPU - Model: googlenet ms < Lower Is Better 1 . 20.80 |==================================================================== 2 . 20.83 |==================================================================== 3 . 20.89 |==================================================================== NCNN 20200916 Target: CPU - Model: vgg16 ms < Lower Is Better 1 . 82.96 |==================================================================== 2 . 81.63 |=================================================================== 3 . 81.87 |=================================================================== NCNN 20200916 Target: CPU - Model: resnet18 ms < Lower Is Better 1 . 21.23 |==================================================================== 2 . 21.01 |=================================================================== 3 . 21.04 |=================================================================== NCNN 20200916 Target: CPU - Model: alexnet ms < Lower Is Better 1 . 20.41 |=================================================================== 2 . 20.58 |=================================================================== 3 . 20.81 |==================================================================== NCNN 20200916 Target: CPU - Model: resnet50 ms < Lower Is Better 1 . 42.31 |==================================================================== 2 . 42.08 |==================================================================== 3 . 42.07 |==================================================================== NCNN 20200916 Target: CPU - Model: yolov4-tiny ms < Lower Is Better 1 . 35.85 |==================================================================== 2 . 35.94 |==================================================================== 3 . 36.07 |==================================================================== NCNN 20200916 Target: Vulkan GPU - Model: squeezenet ms < Lower Is Better 1 . 107.16 |=================================================================== 2 . 107.21 |=================================================================== 3 . 107.07 |=================================================================== NCNN 20200916 Target: Vulkan GPU - Model: mobilenet ms < Lower Is Better 1 . 97.01 |==================================================================== 2 . 97.20 |==================================================================== 3 . 97.21 |==================================================================== NCNN 20200916 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better 1 . 33.96 |==================================================================== 2 . 33.97 |==================================================================== 3 . 33.94 |==================================================================== NCNN 20200916 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better 1 . 36.85 |==================================================================== 2 . 36.92 |==================================================================== 3 . 36.83 |==================================================================== NCNN 20200916 Target: Vulkan GPU - Model: shufflenet-v2 ms < Lower Is Better 1 . 22.57 |==================================================================== 2 . 22.57 |==================================================================== 3 . 22.54 |==================================================================== NCNN 20200916 Target: Vulkan GPU - Model: mnasnet ms < Lower Is Better 1 . 35.07 |==================================================================== 2 . 35.10 |==================================================================== 3 . 35.08 |==================================================================== NCNN 20200916 Target: Vulkan GPU - Model: efficientnet-b0 ms < Lower Is Better 1 . 70.06 |==================================================================== 2 . 68.91 |=================================================================== 3 . 69.76 |==================================================================== NCNN 20200916 Target: Vulkan GPU - Model: blazeface ms < Lower Is Better 1 . 6.25 |===================================================================== 2 . 6.27 |===================================================================== 3 . 6.26 |===================================================================== NCNN 20200916 Target: Vulkan GPU - Model: googlenet ms < Lower Is Better 1 . 91.29 |=================================================================== 2 . 92.17 |==================================================================== 3 . 91.32 |=================================================================== NCNN 20200916 Target: Vulkan GPU - Model: vgg16 ms < Lower Is Better 1 . 252.30 |=================================================================== 2 . 252.41 |=================================================================== 3 . 252.99 |=================================================================== NCNN 20200916 Target: Vulkan GPU - Model: resnet18 ms < Lower Is Better 1 . 80.18 |==================================================================== 2 . 80.18 |==================================================================== 3 . 80.21 |==================================================================== NCNN 20200916 Target: Vulkan GPU - Model: alexnet ms < Lower Is Better 1 . 110.76 |=================================================================== 2 . 110.73 |=================================================================== 3 . 110.76 |=================================================================== NCNN 20200916 Target: Vulkan GPU - Model: resnet50 ms < Lower Is Better 1 . 136.16 |=================================================================== 2 . 135.99 |=================================================================== 3 . 132.15 |================================================================= NCNN 20200916 Target: Vulkan GPU - Model: yolov4-tiny ms < Lower Is Better 1 . 137.12 |=================================================================== 2 . 137.32 |=================================================================== 3 . 137.31 |=================================================================== TNN 0.2.3 Target: CPU - Model: MobileNet v2 ms < Lower Is Better 1 . 336.74 |=================================================================== 2 . 335.70 |=================================================================== 3 . 335.82 |=================================================================== TNN 0.2.3 Target: CPU - Model: SqueezeNet v1.1 ms < Lower Is Better 1 . 319.88 |=================================================================== 2 . 319.82 |=================================================================== 3 . 320.04 |=================================================================== OpenCV 4.4 Test: DNN - Deep Neural Network ms < Lower Is Better 1 . 29816 |==================================================================== 2 . 22836 |==================================================== 3 . 20943 |================================================ InfluxDB 1.8.2 Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 val/sec > Higher Is Better 1 . 1081853.5 |================================================================ 2 . 1089126.9 |================================================================ 3 . 1085107.7 |================================================================ InfluxDB 1.8.2 Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 val/sec > Higher Is Better 1 . 1095315.6 |================================================================ 2 . 1095260.6 |================================================================ 3 . 1097357.3 |================================================================ InfluxDB 1.8.2 Concurrent Streams: 1024 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 val/sec > Higher Is Better 1 . 1107162.1 |================================================================ 2 . 1106460.8 |================================================================ 3 . 1105632.5 |================================================================ Apache CouchDB 3.1.1 Bulk Size: 100 - Inserts: 1000 - Rounds: 24 Seconds < Lower Is Better 1 . 149.90 |=================================================================== 2 . 148.42 |================================================================== 3 . 147.33 |==================================================================