This paper deals with address assignment in code generation for digital signal processors (DSPs) with SIMD (single instruction multiple data) memory accesses. In these processors data are organized in groups (or partitions), whose elements share one common memory address. In order to optimize program performance for processors with such memory architectures it is important to have a suitable memory layout of the variables. We propose a two-step address assignment technique for scalar variables using a genetic algorithm based partitioning method and a graph based heuristic which makes use of available DSP address generation hardware. We show that our address assignment techniques lead to a significant code quality improvement compared to heuristics.

Code selection is an important task in code generation for programmable processors, where the goal is to find an efficient mapping of machine-independent intermediate code to processor-specific machine instructions. Traditional approaches to code selection are based on tree parsing which enables fast and optimal code selection for intermediate code given as a set of data-flow trees. While this approach is generally useful in compilers for general-purpose processors, it may lead to poor code quality in the case of embedded processors. The reason is that the special architectural features of embedded processors require performing code selection on data-flow graphs, which are a more general representation of intermediate code. In this paper, we present data-flow graph-based code selection techniques for two architectural families of embedded processors: media processors with support for SIMD instructions and fixed-point DSPs with irregular data paths. Both techniques exploit the fact that, in the area of embedded systems, high code quality is a much more important goal than high compilation speed. We demonstrate that certain architectural features can only be utilized by graph-based code selection, while in other cases this approach leads to a significant increase in code quality as compared to tree-based code selection.

Abstract – Fixed-point DSPs are a class of embedded processors with highly irregular architectures. This irregularity makes it difficult to generate high-quality machine code from programming languages such as C. In this paper we present a novel constraint driven approach to code selection for irregular processor architectures, which provides a twofold improvement of earlier work. First, it handles complete data flow graphs instead of trees and thereby generates better code in presence of common subexpressions. Second, the presented technique is not restricted to computation of a single solution, but it generates alternative solutions. This feature enables the tight coupling of different code generation phases, resulting in better exploitation of instruction-level parallelism. Experimental results indicate that our technique is capable of generating machine code that competes well with handwritten assembly code. 1