A Transformation-Based Approach for Storage Optimization

Abstract

High-level synthesis (HLS) has been successfully targeted towards the digital signal processing (DSP) domain. Both application-specific integrated circuits (ASICs) and application-specific instruction-set processor (ASIPs) have been frequently designed using the HLS approach. Since most ASIP and DSP processors provide multiple addressing modes, and, in addition to classical constraint on the number of function units, registers, and buses, there are many resource usage rules, special considerations need to be paid to the optimizing code generation problem. In this paper we propose three transformation techniques, data management, data ordering, and transformational retiming, for storage optimization during code generation. With these transformations, some scheduling bottlenecks are eliminated, redundant instructions removed, and multiple operations mapped onto a single one. The proposed transformations have been implemented in a software system called Theda:MS. A set of benchmark programs has been used to evaluate the effectiveness of Theda:MS. Measurement on the synthesized codes targeted towards the TI-TMS320C40 DSP processor shows that the proposed approach is indeed very effective.