TILED Matrix Multiplication Using Shared Memory in CUDA

Tiled Matrix Multiplication in CUDA

 Today, I am going to discuss Matrix Multiplication in CUDA. In CUDA, number of memories are present. As we have already discussed about the same in previous post "What is CUDA". Matrix Multiplication is very basic but a crucial algorithm in the field of Engineering & Computer Science. I assumed that one who is reading this post knows how to perform Matrix Multiplication in at least one programming language. (C, C++, Python, etc).

How To install CUDA on Ubuntu 14.04 Trusty Tahr

          Today, I am going to discuss about the installation of CUDA 6.5 Toolkit & Drivers on Ubuntu 14.04 (Trusty Tahr). From last few days a number of query regarding this problems are being asked. And Yes, Installation of CUDA Toolkit on Ubuntu 14.04 (Trusty Tahr) release is really a tough and challenging task. There are number of problems encountered during the installation of CUDA Toolkit. The installation on Ubuntu & Fedora systems have a lot of similarities. As both operating systems are based on different packages, so one need to understand the structuring & requirements of those packages to get task successfully done. I have already shared one post regarding installation of CUDA on Ubuntu 14.04 (Trusty Tahr). So lets check the Ubuntu installation process today.

How To Install CUDA on Fedora 20

          Today, I am going to discuss about the installation of CUDA 6.5 Toolkit & Drivers on Fedora 20. From last few days a number of query regarding this problems are being asked. And Yes, Installation of CUDA Toolkit on Fedora 20 (Heisenbug) release is really a tough and challenging task. There are number of problems encountered during the installation of CUDA Toolkit.

Vector Arithmetic Operations in CUDA

After learning how to perform addition of two numbers, the next step is to learn how to perform addition and subtraction of two Vectors. The only difference between these two programs is the memory required to store the two Vectors. Also the kernel functions to perform the task.

Addition of two numbers in CUDA: A Simple Approach

Addition is the very Basic & one of the arithmetic operation. To perform it in C language is also a very easy and simple task. In this post, we will convert the C language code into a CUDA code. The steps to remember for writing a CUDA code for any program are as follows:

What is CUDA?

CUDA (Compute Unified Device Architecture) is invented by NVIDIA Corporation Pvt. Ltd. First release of CUDA was in the year mid 2007.
CUDA is a Parallel Computing Platform one of its first kind which enables General Purpose Computing (widely known as GPGPU) in a very efficient and easy way. CUDA enables user to exploit the computing power of Graphics Processing Unit (GPU) present in underlying hardware. Before the inception of CUDA, one had to use DirectX or OpenGL

One Dimensional (1D) Image Convolution in CUDA

          First let me tell you that if you are reading this page then you are already looking for some advance stuff in today's technology as both CUDA & Image Processing are highly demanding as well as advanced technologies. On this blog we will be mainly focusing on use of CUDA(Compute Unified Device Architecture) technology to improve Image Processing Algorithms.The improvement is mainly with respective to Time & Space required to Image Processing Algorithm. You may refer to concern links provided to get more information about both the fields.