Unrolling-based loop mapping and scheduling

This paper presents an loop unrolling based mapping and scheduling strategy to maximum the parallelism of an application described as task graph targeting on a heterogeneous computing systems. Loops are statically unrolled using compile-time parameters and dynamic tasks are generated to handle run-time conditions, such that the closer the match of run-time conditions and compile-time parameters, the higher the performance. Experimental results obtained using a speech recognition system show the proposed method outperforms an approach without unrolling by 2.1 times, and using the processing time of a 2.6 GHz microprocessor as a reference, a speed up of 10 times can be achieved when compile-time and run-time parameters are matched, while the performance drops gradually when they are different.