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Journal Article Application-Adaptive Reconfiguration of Memory Address Shuffler for FPGA-Embedded Instruction-Set Processor
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Authors
Young-Su Kwon, Nak-Woong Eum
Issue Date
2010-11
Citation
Journal of Circuits, Systems and Computers, v.19, no.7, pp.1435-1447
ISSN
0218-1266
Publisher
World Scientific Publishing
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1142/S0218126610006748
Abstract
Programmability requirement in reconfigurable systems necessitates the integration of soft processors in FPGAs. The extensive memory bandwidth sets a major performance bottleneck in soft processors for media applications. While the parallel memory system is a viable solution to account for a large amount of memory transactions in media processors, memory access conflicts caused by multiple memory buses limit the overall performance. We propose and evaluate the configurable memory address shuffler integrated in memory access arbiter for the parallel memory system in a soft processor. The novel address shuffling algorithm profiles memory access pattern of the application, produces the access conflict graph, relocates decomposed memory sub-pages based on the access conflict graph, and finally generates a synthesizable code of the address shuffler. The address shuffler efficiently translates the requested memory addresses into the shuffled addresses such that the amount of simultaneous accesses to the identical physical memory block diminishes. The reconfigurability of the address shuffler enables the adaptive address shuffling depending on the memory access pattern of an application running on the soft processor. The configurable address shuffler removes 80% of access conflicts on average for benchmarks where the hardware overhead of the shuffler is 1592 LUTs which is 14% of LUT size of the processor core. © 2010 World Scientific Publishing Company.
KSP Keywords
Access Conflict, Configurable memory, Instruction sets, Media applications, Memory System, Memory access pattern, Memory address, Memory bandwidth, Overall performance, Parallel memory, Physical Memory