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Design and Development of Grid Enabled, G2PU Accelerated Java Application (Protein Sequence Study) for Grid Performance Analysis

机译:支持网格的G2PU加速Java应用程序的设计和开发(蛋白质序列研究),用于网格性能分析

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Recent advancement in the field of structural biology has generated huge volume of data and analyzing such data is vital to know the hidden truths of life but such analysis is compute intensive in nature and requires huge computational power resulting in extensive use of high performance computing (Multi Core Computing, G2PU Computing, CPU-GPU Hybrid computing, Cluster, Grid) models. Grid is one of the widely used HPC model which is commonly used in computational biology and to execute a compute intensive tasks on grid, the applications must also be grid enabled. Performance of grid depends on appropriate selection of load balancing strategy (at server and node level) and maximum utilization of computational resources of nodes (multiple cores of CPU and execution units of GPU) by the grid enabled applications. In this paper an attempt has been made to establish an experimental grid, develop a grid enabled application and to operate the grid with its highest possible performance by the grid enabled applications.
机译:结构生物学领域的最新进展已产生了大量数据,对此类数据进行分析对于了解生活中的隐藏真相至关重要,但这种分析本质上是计算密集型的,需要巨大的计算能力,因此导致高性能计算的广泛使用(多核心计算,G2PU计算,CPU-GPU混合计算,集群,网格)模型。网格是广泛用于计算生物学的HPC模型之一,要在网格上执行计算密集型任务,应用程序还必须启用网格。网格的性能通过对电网依赖于负载均衡策略(在服务器和节点级)和节点的计算资源(GPU的CPU的执行部件多核心)的最大利用率的适当选择功能的应用。在本文中,已经尝试建立实验性网格,开发具有网格功能的应用程序并通过具有网格功能的应用程序以最高性能运行网格。

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