gpu riser card

A lot of friends in addition to viewing the graphics card parameters or viewing the graphics card ladder, you can also use professional gpu-z tools to view the video card good or bad. With the help of gpu-z mainly need to learn to see the graphics

Graphics performance depends on the display core, so to distinguish the graphics performance, you must know some of the graphics card parameters! To facilitate the viewing of parameters, a tool designed to view the parameters of the graphics card is gpu-z. Through gpu-z, we can compare the graphics

View graphics card and GPU information in CentOS Lspci | grep-I vga This will display the graphics card information on the machine, such [Root @ localhost conf] # lspci | grep-I vga. 0 VGA compatible controller: nVidia Corporation Device 1081 (rev a1). 0 VGA compatible controller: nVidia Corporation GT215 [GeForce GT 240] (rev a2)08:05. 0 VGA compatible controlle

bc00 [size = 128][Virtual] Expansion ROM at f8f80000 [disabled] [size = 512 K]Capabilities: [60] Power Management version 3Capabilities: [68] MSI: Enable-Count = 1/1 Maskable-64bit +Capabilities: [78] Express Endpoint, MSI 00Capabilities: [b4] Vendor Specific Information: Len = 14 Capabilities: [100] Virtual ChannelCapabilities: [128] Power Budgeting Capabilities: [600] Vendor Specific Information: ID = 0001 Rev = 1 Len = 024 Kernel driver in use: nvidiaKernel modules: nvidiafb, nvidia We ca

Ubuntu16.04 ultra-low graphics card GTX730 configuration pytorch-gpu + cuda9.0 + cudnn tutorial, gtx730cudnnI. Preface Today, I have nothing to do with the configuration of the ultra-low-configuration graphics card GTX730. I think it may be possible to use cuda + cudnn for all the graphics cards. As a result, I checked it on the nvidia official website. It's a pi

First, the preface Today there is nothing to configure a bit of ultra-low-matching graphics card GTX730, I think the graphics card may also be able to use CUDA+CUDNN, the results of the NVIDIA official website, sure enough, I GTX730 ^_^, then my 730 can also use Cuda. introduction of the online installation of Cuda+cudnn+pytorch/tensorflow/caffe blog, I wrote this is not to say how good my method, just wan