high performance computing on graphics processing units: hgpu.org

In this dissertation we examine the efficiency of GPUs with a limited number of stream processors (up to 32), located in desktops and laptops, in the execution of algorithms such as hashing (MD5, SHA1), encryption (Salsa20) and compression (LZ78). For the implementation part, the OpenCL framework was used under OS X. The graphic cards tested were NVIDIA GeForce 9400m and GeForce 9600m GT. We found an efficient block size for each algorithm that results in optimal GPU performance. The results show that encryption and hashing algorithms can be executed on these GPUs very efficiently and replace or assist CPU computations. We achieved a throughput of 159 MB/s for Salsa20, 107.5 MB/s for MD5 and 123.5 MB/s for SHA1. Compression results showed a reduced compression ratio due to GPU memory limitations and reduced speed due to divergent code paths. The combined execution of encryption and compression on the GPU can improve execution times by reducing the latency caused by data transfers between CPU and GPU. In general, a GPU device with 32 stream processors can provide us with enough computation power to replace CPU in the execution of data-parallel computation-intensive algorithms.