By Wim Vanderbauwhede, Khaled Benkrid
High-Performance Computing utilizing FPGA covers the realm of excessive functionality reconfigurable computing (HPRC). This e-book presents an outline of architectures, instruments and functions for High-Performance Reconfigurable Computing (HPRC). FPGAs provide very excessive I/O bandwidth and fine-grained, customized and versatile parallelism and with the ever-increasing computational wishes coupled with the frequency/power wall, the expanding adulthood and features of FPGAs, and the arrival of multicore processors which has brought on the popularity of parallel computational versions. The half on architectures will introduce various FPGA-based HPC systems: hooked up co-processor HPRC architectures reminiscent of the CHREC’s Novo-G and EPCC’s Maxwell structures; tightly coupled HRPC architectures, e.g. the exhibit hybrid-core machine; reconfigurably networked HPRC architectures, e.g. the QPACE process, and standalone HPRC architectures akin to EPFL’s CONFETTI method. The half on instruments will concentrate on high-level programming ways for HPRC, with chapters on C-to-Gate instruments (such as Impulse-C, AutoESL, Handel-C, MORA-C++); Graphical instruments (MATLAB-Simulink, NI LabVIEW); Domain-specific languages, languages for heterogeneous computing(for instance OpenCL, Microsoft’s Kiwi and Alchemy projects). The half on functions will current case from numerous software domain names the place HPRC has been used effectively, comparable to Bioinformatics and Computational Biology; monetary Computing; Stencil computations; info retrieval; Lattice QCD; Astrophysics simulations; climate and weather modeling.
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Extra info for High-Performance Computing Using FPGAs
A comparison of different FPGA implementations of the European option3 benchmark against other implementations using GPUs, Cell BE, and a traditional software implementation was presented in . In this work, the FPGA implementation was produced using “HyperStreams,” which is a high level abstraction for designing arithmetic pipelines built on the Handel-C programming language. An acceleration of 146x compared to a reference software implantation can be obtained using FPGAs. 4 GHz Intel Xeon processor, for one-factor and the multi-factor models, respectively.
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