An experimental evaluation of scalar replacement on scientific benchmarks

This paper describes our experiments comparing multiple scalar replacement algorithms to evaluate their effectiveness on entire scientific application benchmarks within the context of a production‐level compiler. We investigate at what point aggressive scalar replacement becomes detrimental and which dependence tests are necessary to give scalar replacement enough information to be effective. As many commercial optimizing compilers may include some version of scalar replacement as an optimization, it is important to determine how aggressive these algorithms need to be. Previously, no study has examined ‘how much’ scalar replacement is sufficient and effective within the context of an existing highly optimizing compiler. Our experiments show that, on whole programs, simple algorithms and simple dependence analysis capture nearly all opportunities for scalar replacement found in scientific application benchmarks. While additional aggressiveness may lead to some performance gain in some individual loops, it also leads to performance degradation too often to be worth the risk when considering entire applications. Algorithms restricted to value reuse over at most one loop iteration and to fully redundant array references give the best results. Our experiment further shows that scalar replacement is not only an effective optimization, but also a feasible one for commercial optimizers since the simple algorithms are not computationally expensive. Based upon our findings, we conclude that scalar replacement ought to be a part of any highly optimizing compiler because of its low cost and significant potential gain. Copyright © 2003 John Wiley & Sons, Ltd.     

3种提高软件流水有效性的算法:比较和结合

软件流水是开发循环程序指令级并行性的技术,它通过并行执行连续的多个循环体来加快循环的执行速度.在软件流水中,循环体的重叠增加了寄存器需求,导致寄存器压力增大,当目标处理机所提供的寄存器不足时,软件流水可能失败.在Itanium处理机上评估了NAS和SPEC2000基准程序中的软件流水循环的寄存器需求,发现静态寄存器不足是造成软件流水失败的主要原因,提出了3种增加软件流水个数、提高软件流水有效性的算法:限制循环展开因子的算法(register sensitive unrolling,简称RSU)、堆栈寄存器分配算法(stacked registerallocation,简称SRA)以及变量类型转换的算法(variabletype conversion,简称VTC).RSU根据静态寄存器需求确定一个合理的展开因子,增加了软件流水的成功率;SRA和VTC分别使用空闲的堆栈寄存器和旋转寄存器来充当静态寄存器,提高了寄存器的利用率.在面向Itanium处理器的开放源码编译器ORC(open research compiler)上实现了这3种算法,通过NAS程序的测试比较了这3种算法的有效性,同时对它们的结合应用进行了研究和实验.