Real-time enhanced efficient thread level parallelism scheme for performance improvement in heterogeneous edge computing

Abstract

In the era of technology, there is a need to rely on new high performance Heterogeneous embedded computing device to process a huge amount of data for various smart applications. Packing different architecture processor into a system on chip provides a substantial potential improvement in computing horsepower, but the maximum processing power of this heterogeneous edge computing processor can only be harnessed if the target software is actually configured to utilize all the processing elements. The proposed Enhanced Efficient thread level parallelism (EETLP) is implemented using CUDA in CPU-GPU based heterogeneous edge computing platform and analyzed with different size of matrix multiplication. From the experiment results, it was clearly observed that for the matrix size 1024x1024, Efficient Thread Level Parallelism (ETLP) using quad core CPU processor reduces 71% execution time and EETLP reduces 99% execution time compared to Basic Sequential Execution (BSE). In terms of Speedup, EETLP has achieved 5.5Kx speedup compare with ETLP and 19Kx speedup against BSE on CPU.