Installing CUDA 9 on Ubuntu 17.10: A Guide

To avoid boot issues caused by the Nvidia Persistent Daemon when using Wayland, one possible solution is to install Nvidia drivers through the Ubuntu preinstalled program known as Additional Drivers. Solution 1: Setting up the 384 version of the NVIDIA driver. To set up the computer with an NVIDIA GPU, we can either install a […]

Implementing Atomic Writes in CUDA: A Guide

The execution order of these operations is not guaranteed, and the order in which other threads observe these events may not be as expected. The flag write can occur before the guarded data is written. To address this, combining multiple operations using an operation can prevent any intervening operations from other threads. Question: Initially, I […]

Tips for identifying the CUDA version of Nvidia

Feedback Solution: How can one determine if a particular Nvidia GPU is supported by a given CUDA version, particularly a recently launched version? GPUs having a compute capability of 2.0 or higher are supported by all CUDA versions ranging from CUDA 7.0 to CUDA 8.0, which includes both of your GPUs. Details of supporting some […]

Specifying the GPU for PyCUDA: A Guide

Generally, the primary GPU is assigned as the target display with the string “0.0”. If you intend to launch the display on the secondary GPU, you can perform the following action. Is it possible that you are using an outdated version of the CUDA toolkit that PyCUDA is utilizing? Solution 1: The specific GPUs you […]

Unusable printf within a CUDA kernel function

Feedback Question: The printf function is not functional when executed within the Kernel of a cuda code . #include “Common.h” #include #include __device__ __global__ void Kernel(float *a_d , float *b_d ,int size) { int idx = threadIdx.x ; int idy = threadIdx.y ; //Allocating memory in the share memory of the device __shared__ float temp[16][16]; […]