Scientific Applications in a Distributed Computing Environment

本研究计划的重点是开发一套相当大的真正的科学应用程序，用于在高性能工作站网络上或在有限的分布式计算环境中使用相对较快的网络（例如，32处理器的Thinking Machines CM-5）执行。这套用于分布式仪器和SADIE执行的科学应用程序可以被计算科学家用作真实科学应用程序的测试平台，以评估和基准测试各种分布式计算环境的软件工具或环境。SADIE将促进性能预测模型的发展，这些模型可以评估给定环境对特定应用程序或应用程序子集的适用性。执行科学应用程序所需的实际内存、CPU速度和网络延迟将使用几个分布式计算软件系统进行量化，SADIE的候选支持软件系统包括PVM、P4、CONDOR和Linda。通过构建应用程序的测试平台，可以评估以前在大规模并行平台上表现良好的流行（底层）算法的有效性。可以比较分布式环境的备选策略/算法，以便根据某些网络条件对算法进行排序（适用性）的分类。SADIE包含多种科学应用：高温超级计算机建模、压电晶体建模、材料特性第一性原理模拟、大规模信息检索、计算生态学和非结构化网格有限元计算。SADIE中使用的相应的主要算法集包括：线性系统的求解，SVD和广义对称特征问题，自适应网格细化，有限元网格的矩阵组装以及聚类/补丁识别几何。

9411394 Berry This research proposal focuses on the development of a reasonably large suite of real scientific application programs for execution on networks of high-performance workstations or within a limited distributed computing environment with a relatively fast network (e.g., 32-processor Thinking Machines CM-5). This suite of Scientific Applications for Distributed Instrumentation and Execution of SADIE can be used a testbed of real scientific applications by computational scientists to evaluate and benchmark software tools or environments for various distributed computing environments. SADIE will facilitate the development of performance prediction models which can assess the suitability of a given environment for a particular application or subset of applications. Realistic memory, CPU speeds, and network latencies needed to execute scientific applications will be quantified using several distributed computing software systems, Candidate support software systems for SADIE include PVM, P4, CONDOR, and Linda. By constructing a testbed of applications, the effectiveness of popular (underlying) algorithms which previously performs well on massively-parallel platforms can be assessed. Alternative strategies/algorithms for distributed environments can be compared so that a classification in which algorithms are ranked (in suitability) according to certain network conditions is produced. SADIE comprises a diverse set of scientific applications: modeling high-temperature supercomputers, modeling piezoelectric crystals, first principles simulation of material properties, large-scale information retrieval, computational ecology, and finite element computations on unstructured meshes. The corresponding set of dominant algorithms used within SADIE includes: the solution of linear systems, SVD and generalized symmetric eigenproblems, adaptive mesh refinement, matrix assembly from finite element meshes, and cluster/patch identification geometry.