<p>Computation-intensive algorithms require a high level of parallelism and programmability, which </p><p>make them good candidate for hardware acceleration using fine-grained processor arrays. Using </p><p>Hardware Description Language (HDL), it is very difficult to design and manage fine-grained </p><p>processing units and therefore High-Level Language (HLL) is a preferred alternative. </p><p> </p><p>This thesis analyzes HLL programming of fine-grained architecture in terms of achieved </p><p>performance and resource consumption. In a case study, highly computation-intensive algorithms </p><p>(interpolation kernels) are implemented on fine-grained architecture (FPGA) using a high-level </p><p>language (Mitrion-C). Mitrion Virtual Processor (MVP) is extracted as an application-specific </p><p>fine-grain processor array, and the Mitrion development environment translates high-level design </p><p>to hardware description (HDL). </p><p> </p><p>Performance requirements, parallelism possibilities/limitations and resource requirement for </p><p>parallelism vary from algorithm to algorithm as well as by hardware platform. By considering </p><p>parallelism at different levels, we can adjust the parallelism according to available hardware </p><p>resources and can achieve better adjustment of different tradeoffs like gates-performance and </p><p>memory-performance tradeoffs. This thesis proposes different design approaches to adjust </p><p>parallelism at different design levels. For interpolation kernels, different parallelism levels and </p><p>design variants are proposed, which can be mixed to get a well-tuned application and resource </p><p>specific design.</p>
Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:hh-2620 |
Date | January 2009 |
Creators | Cheema, Fahad Islam |
Publisher | Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Högskolan i Halmstad/Sektionen för Informationsvetenskap, Data- och Elektroteknik (IDE) |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, text |
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