Exploring the Role of Grid-Enabled OpenMP in Adaptive Mesh Calculations

计算机和网络技术的进步将很快使利用分布式超级计算机系统的集体计算能力成为可能，从而形成计算电网（或简称网格）。网格计算将需要处理异常高的延迟和低带宽。为了有效地将网格用作科学计算的平台，将需要新的算法和编程方法，以及编译器和运行时支持，以简化程序开发过程。这个问题的范围是如此广泛，以至于我们认为，通过关注具体的应用领域，可以最好地开发有效的技术。本提案将进行探索性研究，探索编译器和运行时技术的发展，以及支持网格计算流体动力学（CID）中大规模、并行、结构化自适应网格细化（AMR）计算的算法技术。该项目将是一项跨学科研究，由NCSA的应用科学家和莱斯大学和休斯顿大学的计算机科学家组成。因此，该提案将进行一项研究，看看这种高度复杂的AMR应用程序是否可以有效地在网格上运行。本课程将探讨几种不同的算法策略来支持网格上的AMR。这还需要开发创新的编译器技术和OpenMP标准的语言扩展，使其能够为此类AMR应用程序提供基于网格的支持。最后，网格计算环境中的资源（节点、网络连接）经常是争用的。因此，支持网格的应用程序必须能够预测地适应不断变化的网格资源。该提案将建立监控应用程序在网格上的性能以及可用网格资源的工具。来自这些工具的信息将通过OpenMP API中的标准接口提供给AMR应用程序，以便AMR应用程序可以推测地适应不断变化的网格资源。

Advances in computer and network technologies will soon make it possible to harness the collective computing power of distributed supercomputer systems as a Computational Power Grid (or Grid for short). Grid computing will entail coping with unusually high latencies and low bandwidths. To use such a Grid effectively as a platform for scientific computing will require new algorithms and programming methodologies along with compiler and run-time support to simplify the program development process.The scope of this problem is so broad that we believe that effective technologies can best be developed through focusing on concrete application domains. This proposal will perform an exploratory study to explore the development of compiler and runtime technology as well as algorithmic techniques for supporting largescale, parallel, structured adaptive mesh refinement (AMR) calculations in Computational Fluid Dynamics (CID) on the Grid. The project will be an interdisciplinary study consisting of applications scientists from NCSA and computer scientists from Rice and University of Houston.This proposal, therefore, will carry out a study to see whether such highly complex AMR applications can be efficiently run on the Grid. The course of this work will be exploring several different algorithmic strategies for supporting AMR on Grids. This will also entail developing innovative compiler technology and language extensions to the OpenMP standard that allow it to provide Grid-based support for such AMR applications. Lastly, resources (nodes, network connections) in the Grid computational environment are often contended. Therefore a Grid-enabled application has to be able to speculatively adapt to changing Grid resources. The proposal will build up tools that monitor the application's performance on the Grid as well as the available Grid resources. Information from these tools will be made available to the AMR application through standard interfaces in our OpenMP API so that the AMR application can speculatively adapt to changing Grid resources.