An Efficient Vectorization Approach to Nested Thread-level Parallelism for CUDA GPUs

Abstract

Nested thread-level parallelism (TLP) is pervasive in real applications. For example, 75% (14 out of 19) of the applications in the Rodinia benchmark for heterogeneous accelerators contain kernels with nested thread-level parallelism. Efficiently mapping the enclosed nested parallelism to the GPU threads in the C-to-CUDA compilation (OpenACC in this paper) is becoming more and more important. This mapping problem is two folds: suitable execution models and efficient mapping strategies of the nested parallelism.