Storage optimization through code size reduction for digital signal processors

Hassan A. Salamy, J. Ramanujam
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引用次数: 1

Abstract

Most modern digital signal processors (DSPs) provide multiple address registers and a dedicated address generation unit (AGU) which performs address generation in parallel to instruction execution. There is no address computation overhead if the next address is within the auto-modify range. A careful placement of variables in memory is utilized to decrease the number of address arithmetic instructions and thus to generate compact and efficient code. The simple offset assignment (SOA) problem concerns the layout of variables for machines with one address register and the general offset assignment (GOA) deals with multiple address registers. Both these problems assume that each variable needs to be allocated for the entire duration of a program. Both SOA and GOA are NP-complete. In this paper, we present an effective heuristic for the general offset assignment problem with variable coalescing (CGOA) where two or more non-interfering variables can be mapped into the same memory location. Results on several benchmarks show the significant improvement of our solution compared to other heuristics. Results were further improved using a simulated annealing (SA).
通过减少数字信号处理器的代码大小来优化存储
大多数现代数字信号处理器(dsp)提供多个地址寄存器和一个专用地址生成单元(AGU),该单元在并行执行指令时执行地址生成。如果下一个地址在自动修改范围内,则没有地址计算开销。通过在内存中小心地放置变量,可以减少地址算术指令的数量,从而生成紧凑而高效的代码。简单偏移分配(SOA)问题涉及具有一个地址寄存器的机器的变量布局,而一般偏移分配(GOA)处理多个地址寄存器。这两个问题都假设每个变量都需要在程序的整个持续时间内分配。SOA和GOA都是np完备的。在本文中,我们提出了一种有效的启发式方法,用于具有变量合并(CGOA)的一般偏移分配问题,其中两个或多个非干扰变量可以映射到相同的内存位置。几个基准测试的结果表明,与其他启发式方法相比,我们的解决方案有了显著的改进。使用模拟退火(SA)进一步改善了结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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