Moore's Law has helped Field Programmable Gate Arrays (FPGAs) scale continuously in speed, capacity and energy efficiency, allowing the integration of ever-larger systems into a single FPGA chip. This brings challenges to the productivity of developers in leveraging the sea of FPGA resources. Higher level of design abstractions and programming models are needed to improve the design productivity, which in turn require memory architectural supports on FPGAs. While previous efforts focus on computation-centric applications, we take a bandwidth-centric approach in designing memory systems. In particular, we investigate the scheduling, buffered switching and searching problems, which are common to a wide range of FPGA applications. Despite that the bandwidth problem has been extensively studied for general-purpose computing and application specific integrated circuit (ASIC) designs, the proposed techniques are often not applicable to FPGAs. In order to achieve optimized design implementations, designers need to take into consideration both the underlying FPGA physical characteristics as well as the requirements from applications. We therefore extract design requirements from four driving applications for the selected problems, and address them by exploiting the physical architectures and available resources of FPGAs. Towards solving the selected problems, we manage to advance state-of-the-art with a scheduling algorithm,
a switch organization and a cache analytical model. These lead to performance improvements, resource savings and feasibilities of new approaches for well-known problems.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/43538 |
| Date | 08 January 2014 |
| Creators | Dai, Zefu |
| Contributors | Zhu, Jianwen |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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