Time-constrained code compaction for DSPs

Abstract

This paper addresses instruction-level parallelism in code generation for digital signal processors (DSPs). In the presence of potential parallelism, the task of code generation includes code compaction, which parallelizes primitive processor operations under given dependency and resource constraints. Furthermore, DSP algorithms in most cases are required to guarantee real-time response. Since the exact execution speed of a DSP program is only known after compaction, real-time constraints should be taken into account during the compaction phase. While previous DSP code generators rely on rigid heuristics for compaction, we propose a novel approach to exact local code compaction based on an integer programming (IP) model, which handles time constraints. Due to a general problem formulation, the IP model also captures encoding restrictions and handles instructions having alternative encodings and side effects and therefore applies to a large class of instruction formats. Capabilities and limitations of our approach are discussed for different DSPs.