Heterogeneous Parallel Computing Using Cuda for Chemical Process

Abstract

CUDA (Compute Unified Device Architecture) is a parallel computing platform and programming model created by NVIDIA and implemented by the graphics processing units (GPUs) that they produce. Using CUDA, the GPUs can be used for general purpose processing which involves parallel computation. CUDA has been used to accelerate non-graphical applications in computational biology, cryptography and other fields by an order of magnitude or more. Chemical processes need validation of their experimental data. It was found that Chemical process could become one such application where CUDA can be efficiently used. These validations of Chemical processes normally involve calculation of many coefficients. The chemical process that has been chosen for parallelizing is Heat Transfer process. This process involves calculation of coefficients for multiple iterations. As each of these iterations is independent of one another, CUDA was used to parallelize the calculation process. The execution time analysis shows that though CPU outperforms GPU when the numbers of iterations are less, when the number of iterations increase the GPU outperforms CPU greatly.