ITR: Opportunistic Parallel Computation

该项目提出了运行时和编译器支持，使程序能够收集空闲的SMP和/或单处理器工作站来执行并行计算。该系统的独特功能是能够使并行程序适应处理器的动态可用性，同时利用SMP中的局部性。该项目集成了几个目标，即：1)扩展分布式共享内存Strings以支持线程迁移，结合对运行时可用处理器数量变化的适应，并提出在运行时处理器数量变化时平衡数据局部性和并行性的技术。2)研究驱逐时间对重新映射策略和约束的影响。3)开发对并行程序的编译时支持，这些并行程序可以在处理器数量和可用性变化的环境中执行。4)开发分析模型，并使用几个真正的程序对上述编译器和运行时技术进行广泛的评估。5)将SMP工作站机群上并行计算的空闲周期的利用集成到现有的并行化环境中。

This project proposes runtime and compiler support that will enable programs to harvest idle SMPs and/or single processor workstations to perform parallel computations. The unique feature of this system is the ability to adapt parallel programs to the dynamic availability of processors while exploiting the locality within an SMP. The project integrates several goals, namely:1) Extend the Distributed Shared Memory, Strings, to support thread migration, incorporate adaptation to the changing number of available processors at runtime and propose techniques to balance data locality and the parallelism used when the number of processors changes at runtime. 2) Study the impact of eviction time on remapping strategies and constraints. 3) Develop compile-time support for parallel programs which can be executed in an environment where the number and the availability of the processors can change.4) Develop analytic models and extensively evaluate the above compiler and runtime techniques using several "real programs".5) Integrate the utilization of idle cycles for parallel computing on cluster of SMP workstations into the existing parallelization environment.