Multithreaded Pipeline Synthesis for Data-Parallel Kernels

Pipelining is an important technique in high-level synthesis, which overlaps the execution of successive loop iterations or threads to achieve high throughput for loop/function kernels. Since existing pipelining techniques typically enforce in-order thread execution, a variable-latency operation in one thread would block all subsequent threads, resulting in considerable performance degradation. In this paper, we propose a multithreaded pipelining approach that enables context switching to allow out-of-order thread execution for data-parallel kernels. To ensure that the synthesized pipeline is complex-ity effective, we further propose efficient scheduling algorithms for minimizing the hardware overhead associated with context man-agement. Experimental results show that our proposed techniques can significantly improve the effective pipeline throughput over conventional approaches while conserving hardware resources. 1