Optimization Strategies Oriented to Loop Characteristics in Software Thread Level Speculation Systems  

作　　者：Li Shen 

机构地区：[1]State Key Laboratory of High Performance Computing, Changsha 410073, China [2]School of Computer, National University of Defense Technology, Changsha 410073, China

出　　处：《Journal of Computer Science & Technology》2016年第1期60-76,共17页计算机科学技术学报（英文版）

基　　金：This work was supported by the National High Technology Research and Development 863 Program of China under Grant No. 2012AA010905 and the National Natural Science Foundation of China under Grant Nos. 61272143 and 61472431.

摘　　要：Thread level speculation provides not only a simple parallel programming model, but also an effective mech- anism for thread-level parallelism exploitation. The performance of software speculative parallel models is limited by high global overheads caused by different types of loops. These loops usually have different characteristics of dependencies and different requirements of optimization strategies. In this paper, we propose three comprehensive optimization techniques to reduce different factors of global overheads, aiming at requirements from different types of loops. Inter-thread fetching can reduce the high mis-speculation rate of the loops with frequent dependencies and out-of-order committing can reduce the control overhead of the loops with infrequent dependencies, while enhanced dynamic task granularity resizing can reduce the control overhead and optimize the global overhead of the loops with changing characteristics of dependencies. All these three optimization techniques have been implemented in HEUSPEC~ a software TLS system. Experimental results indicate that they can satisfy tile demands from different groups of benchmarks. The combination of these techniques can improve the performance of all benchmarks and reach a higher average speedup.Thread level speculation provides not only a simple parallel programming model, but also an effective mech- anism for thread-level parallelism exploitation. The performance of software speculative parallel models is limited by high global overheads caused by different types of loops. These loops usually have different characteristics of dependencies and different requirements of optimization strategies. In this paper, we propose three comprehensive optimization techniques to reduce different factors of global overheads, aiming at requirements from different types of loops. Inter-thread fetching can reduce the high mis-speculation rate of the loops with frequent dependencies and out-of-order committing can reduce the control overhead of the loops with infrequent dependencies, while enhanced dynamic task granularity resizing can reduce the control overhead and optimize the global overhead of the loops with changing characteristics of dependencies. All these three optimization techniques have been implemented in HEUSPEC~ a software TLS system. Experimental results indicate that they can satisfy tile demands from different groups of benchmarks. The combination of these techniques can improve the performance of all benchmarks and reach a higher average speedup.

关 键 词：parallel programming model OPTIMIZATION thread level speculation HEUSPEC performance 

分 类 号：TP316[自动化与计算机技术—计算机软件与理论] U464[自动化与计算机技术—计算机科学与技术]