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Titlebook: High-Performance Computing Using FPGAs; Wim Vanderbauwhede,Khaled Benkrid Book 2013 Springer Science+Business Media, LLC 2013 FPGA computi

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楼主: mountebank
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FPGA-Accelerated Molecular Dynamicsre exists a many order-of-magnitude gap between the demand and the performance currently achieved. Acceleration of MD has therefore received much attention. In this chapter, we discuss the progress made in accelerating MD using Field-Programmable Gate Arrays (FPGAs). We first introduce the algorithm
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FPGA-Based HPRC for Bioinformatics Applicationss, which are intrinsically suited to FPGA implementations. Others can be expressed as numerical computations which can parallelize through pipelining, instruction-level and data-level parallelism. This chapter covers two sample applications encountered in bioinformatics, namely homology searches and
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High-Performance Computing for Neuroinformatics Using FPGA non-linear, dynamical and often time-varying. Hardware systems, such as the FPGA-based platforms, are very efficient in doing such studies given their intrinsic parallelism, reconfigurability and real-time processing capability. We have successfully used the Xilinx Virtex-6 FPGA devices to prototyp
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High Performance Implementation of RTM Seismic Modeling on FPGAs: Architecture, Arithmetic and Poweralgorithm. These devices have been largely used as accelerators in scientific computing applications that require massive data processing, large parallel machines, huge memory bandwidth and power. The RTM algorithm enables you to directly solve the acoustic and elastic waves problems with precision
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FPGA-Based HPRC Systems for Scientific Applicationslications. In this chapter, we show two case studies of applying FPGA-based systems for this application domain. First, implementation of ocean model simulation is discussed, especially focusing on how use of a high-level design tool and data transfer optimization techniques affect the execution per
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Accelerating the SPICE Circuit Simulator Using an FPGA: A Case Studynd energy-savings over a conventional microprocessor for the simulation program with integrated circuit emphasis (SPICE) circuit simulator. We develop a parallel, FPGA-based, heterogeneous architecture customized for accelerating the SPICE simulator to deliver this speedup. To properly parallelize t
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