CISE Research Instrumentation: Design and Evaluation of Architectures, Programming Environments, and Applications for Shared-Memory Systems

Adve，Sarita V. Aazhang，Behnaam Rice大学 CISE研究仪器：共享内存系统的体系结构、编程环境和应用的设计与评估 这项研究仪器补助金有助于获得共享内存多处理器，以支持以下研究项目：-基于ILP的共享内存多处理器的设计和评估-共享内存系统的并行化处理器-调整共享内存并行程序性能的交互式和自适应技术-通信系统的并行算法-信号和图像处理。 因此，以下研究是启用：-架构技术，以利用共享内存多处理器的并行级并行：快速模拟方法是这项研究的关键使能技术。 建议的多处理器，使高性能并行模拟器的开发和使用。- 高性能Fortran（HPF）的编译技术：所提出的多处理器是HPF编译器开发的一个具有成本效益的平台，也是评估编译器生成的并行代码的一个重要目标。- 识别和补救共享内存程序中的性能瓶颈的并行技术：多处理器是开发和评估这些技术的理想平台。- 用于无线和网络通信系统的算法：大多数此类算法必须满足严格的实时约束。多处理器使并行算法的开发能够满足这些约束。用于信号和图像处理的算法，应用包括物理学、雷达和医学成像诊断：需要多处理器在真实的数据集上测试和开发并行和资源密集型顺序算法。总的来说，所提出的系统，使上述研究在三个关键的方式：使并行化的应用程序，不能按顺序运行，提供了一个测试平台的编译器和工具的研究，并提供具有成本效益的资源，顺序，但资源密集型任务。

Adve, Sarita V. Aazhang, Behnaam Rice University CISE Research Instrumentation: Design and Evaluation of Architectures, Programming Environments, and Applications for Shared-Memory Systems This research instrumentation grant facilitates acquiring a shared-memory multiprocessor to support the following research projects: -Design and Evaluation of ILP-Based Shared-Memory Multiprocessors -Parallelizing Compilers for Shared-Memory Systems- Interactive and Adaptive Techniques for Tuning the Performance of Shared-Memory Parallel Programs -Parallel Algorithms for Communications Systems -Signal and Image Processing. The following research is thus enabled:- Architectural techniques to exploit instruction-level-parallelism in shared-memory multiprocessors: Fast simulation methods are the key enabling technology for this research. The proposed multiprocessor enables the development and use of high-performance parallel simulators. - Compilation techniques for High Performance Fortran (HPF): The proposed multiprocessor is a cost-effective platform for HPF compiler development and an important target for evaluating the compiler-generated parallel code. - Runtime techniques to identify and remedy performance bottlenecks in shared-memory programs: The multiprocessor is the desired platform to develop and evaluate the techniques. - Algorithms for wireless and network communication systems: Most such algorithms must meet stringent real-time constraints. The multiprocessor enables the development of parallel algorithms to meet these constraints.- Algorithms for signal and image processing for applications including geophysics, radar, and medical imaging diagnostics: The multiprocessor is needed to test and develop parallel and resource-intensive sequential algorithms on real data sets. Overall, the proposed system enables the above research in three critical ways: enables parallelization of applications that cannot be run sequentially, provides a testbed for compiler and tools research, and provides cost-effective resources for sequential but resource-intensive tasks.