08-01-2014, 04:19 PM
CUDA Technology
Abstract:
Today’s supercomputers are computers of tomorrow and GPU processors are bridge between them today. A Graphics Processing Unit or GPU is a specialized processor offloads 3D or 2D graphics rendering from the microprocessor. GPU computing is the use of a GPUto do general purpose scientific and engineering computing. The model of GPU computing is to use a CPU and GPU together in a heterogeneous computing model. The sequential part of the application runs on the CPU and the computationally-intensive part runs on the GPU. From the user’s perspective, the application just runs faster because it is using high performance of the GPU to boost performance. Computing is evolving from central processing on the CPU to co-processing on the CPU and GPU. TO enable this new computing paradigm, NVIDIA invented the CUDA parallel computing architecture.
The specific algorithms ported to the CUDA architecture included JPEG, Vorbis audio encoding and lossless data compression. Lossless data compression was chosen as being distinctly unique from libjpeg and Vorbis in that both of these are lossy compression techniques. JPEG compression was considered distinct from audio in that the encoding concepts and transforms used differed significantly enough to contain divergent opportunities for exploitation of data level parallelism and vector processing