No.031 Many-cores and On-chip Interconnects

Graphics processing units (GPUs) are increasingly important for general-purpose parallel processing performance. GPU hardware is composed of many streaming multiprocessors, each of which employs the single-instruction multiple-data (SIMD) execution style. This massively parallel architecture allows GPUs to execute tens of thousands of threads in parallel. Thus, GPU architectures efficiently execute heavily data-parallel applications.
However, the performance of GPU applications critically depends on the compiler optimization. If it is not done right, it will seriously hurt the performance. In this talk, I will first present a case study of accelerating 3D sound localization using GPUs. Then, I will present the modeling and optimization techniques we have developed including control flow divergence modeling, register and thread structure optimization, and cache passing optimization.