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.
A Technical Blog addressing the Computer Science Issues. Focus is mainly on Tools and Technologies Techniques required to Develop different Applications by using Technologies like CUDA, Image Processing, MATLAB, OpenCV, C, C++ and Web Development.
Friday 17 July 2015
Sunday 12 July 2015
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:
Sunday 5 July 2015
Two Dimensional (2D) Image Convolution in CUDA by Shared & Constant Memory: An Optimized way
After learning the concept of two dimension (2D) Convolution and its implementation in C language; the next step is to learn to optimize it. As Convolution is one of the most Compute Intensive task in Image Processing, it is always better to save time required for it. So, today I am going to share a technique to optimize the Convolution process by using CUDA. Here we will use Shared Memory and Constant Memory resources available in CUDA to get fastest implementation of Convolution.
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