GPU Programming using NVIDIA CUDA

Performing DCT8x8 Computation on GPU Using NVIDIA CUDA Technology

In this paper, we have proposed sequential and parallel Discrete Cosine Transform (DCT) in compute unified device architecture (CUDA) libraries. The introduction of programmable pipeline in the graphics processing units (GPU) has enabled configurability. GPU which is available in every computer has a tremendous feat of highly parallel SIMD processing, but its capability is often under-utilized....

GPU acceleration of object classification algorithms using NVIDIA CUDA

Data access optimized applications on the GPU using NVIDIA CUDA

This work is an attempt to address the problem of bandwidth limited performance of data intensive GPGPU applications. Performance limited by memory bandwidth is common issue faced by general data intensive HPC applications. In case of the GPU, this problem is more pronounced owing to the unique architecture. This problem has been tackled by optimizing basic data rearrangement operations on the ...

GPU-Accelerated SART Reconstruction Using the CUDA Programming Environment

The Common Unified Device Architecture (CUDA) introduced in 2007 by NVIDIA is a recent programming model making use of the unified shader design of the most recent graphics processing units (GPUs). The programming interface allows algorithm implementation using standard C language along with a few extensions without any knowledge about graphics programming using OpenGL, DirectX, and shading lan...

Efficient Data Compression using CUDA programming in GPU

The aim of this project is to explore and test the new potential performance improvement that can be achieved by the use of GPU processing architecture for several different types of compression algorithms. The compression algorithms are the choice of focus on the data parallelism on the GPU device. The specific algorithms ported to the CUDA architecture included lossless data compression techn...