Optimizations and Designs for Practical Improvements to Program Performance on Multicore Systems

点击翻译按钮获取中文摘要

This research aims at improving the utilization of modern, multicore computers. Although these are now commonplace, the techniques required to develop software for such systems are still very complex, and achieving both correctness and efficiency are continuing concerns. Two approaches are used to address this issue. The first furthers work on a specific form of automatic parallelization: "speculative multithreading". This technique is applied internally by the runtime system to make use of multiple processors without programmer or user intervention. The result is a program that executes faster by using any available multiple cores. This has the advantage that the result applies to existing, legacy single-threaded programs, and does not require sophisticated parallel programming skills, although performance is not always the best possible. The second approach aims at improving support for newer programming languages and programming concepts that reduce some of the more subtle complexity found in existing, popular parallel programming languages. It is possible to achieve good efficiency with programming languages that provide access to low-level parallel programming constructs, but this also introduces correctness problems in the potential for "data-races." These kinds of bugs can be prevented through the use of new language designs and idioms, but the best approach is still unclear, and current implementation designs tend to result in trade-offs with program performance. The research work thus focuses on optimizing specific implementation designs, and developing new programming language paradigms that further reduce the complexity encountered by the programmer. Both of our main approaches target improvements in feasible and efficient use of parallel systems, and by addressing the core problem from two fundamental directions we expect to make significant improvements to current practice.