Scientific Applications in a Distributed Computing Environment

9411394 Berry本研究计划的重点是开发一套相当大的真实的科学应用程序，用于在高性能工作站网络上或在具有相对快速网络的有限分布式计算环境中执行（例如，32-处理器Thinking Machines CM-5）。 这套科学应用程序的分布式仪器和执行SADIE可以使用一个测试床的真实的科学应用程序的计算科学家评估和基准测试软件工具或环境的各种分布式计算环境。 SADIE将促进性能预测模型的开发，这些模型可以评估特定环境对特定应用或应用子集的适用性。 将使用几个分布式计算软件系统来量化执行科学应用所需的实际内存、CPU速度和网络延迟。SADIE的候选支持软件系统包括PVM、P4、CONDOR和琳达。 通过构建一个应用程序的测试床，可以评估以前在并行平台上表现良好的流行（底层）算法的有效性。 可以比较用于分布式环境的替代策略/算法，以便产生其中根据某些网络条件对算法进行排名（在适用性方面）的分类。 SADIE包括各种科学应用：高温超级计算机建模，压电晶体建模，材料特性的第一原理模拟，大规模信息检索，计算生态学和非结构化网格上的有限元计算。 SADIE中使用的主要算法包括：线性系统的解决方案，奇异值分解和广义对称特征值问题，自适应网格细化，有限元网格的矩阵组装，和集群/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.