Exploiting Reconfigurable FPGA for Parallel Query Processing in Computation Intensive Data Mining Applications
Exploiting Reconfigurable FPGA for Parallel Query Processing in Computation Intensive Data Mining Applications
复制标题
利用可重构 FPGA 在计算密集型数据挖掘应用中进行并行查询处理
DOI：
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发表时间：
1999
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影响因子：
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通讯作者：
R. Muntz
中科院分区：
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作者：
Kelvin T. Leung;Professor Milos Ercegovac;R. Muntz
这项工作集中于利用基于SRAM的FPGA处理器的可重新配置的可编程可编程门阵列（FPGA），用于查询计算密集型数据挖掘应用程序中的查询处理。地球科学和医学信息系统环境中的复杂计算密集型数据挖掘应用程序通常需要支持可扩展性和并行处理，以赋予必要的功能和HI GH性能。新兴的FPGA技术代表了一种有希望的混合硬件/软件（HW/SW）共同设计方法[20,21]，可通过有效利用可重新配置的特定于任务的硬件内核和主机处理器来增强传统查询处理技术。在这项工作中，我们研究了FPGA协调员系统VCCEVC的属性和特性，该系统使用Xilinx 4020e零件和从奴隶接地进行数据采集。我们为并行查询处理提供了一个简单的HW/SW成本模型。而且，我们通过研究NASA旋风跟踪数据挖掘应用来研究HW/SW分配问题。我们确定了该应用程序中最多的计算密集型例程，该应用程序在我们可扩展的平行地球科学查询过程中运行。 Finall y，我们根据我们的结果讨论了混合方法在给定应用程序中的适用性。
This work concentrates on exploiting re-configurable Field Programmable Gate Arrays (FPGAs), an SRAM-based FPGA coprocessor, for query processing in computation-intensive data mining appli cations. Complex computation-intensive data mining applications in geoscientific and medical information systems environments often require support for extensibility and parallel processing to deli ver the necessary functionality and hi gh performance. Emerging FPGA technology represents a promising hybrid hardware/software (HW/SW) co-design approach [20,21] to augment traditional query processing techniques by efficient use of reconfigurable task-specific hardware kernels and host processor(s). In this work, we study the properties and characteristics of a FPGA co-processor system, VCCEVC, which uses a Xilinx 4020E part and a slaveinterface for data acquisition. We present a simple HW/SW cost model for parallel query processing. And also, we study a HW/SW partitioning problem by looking into the NASA Cyclone-Tracking Data Mining appli cation. We identify the most computation intensive routines in this application that runs on our extensible parallel geoscientific query-processing environment, Conquest. Finall y, we discuss the applicability of the hybrid approach for the given application based on our results.