Soft processors simplify hardware design by being able to implement complex control strategies using software. However, they are not fast enough for many intensive data-processing tasks, such as highly data-parallel embedded applications. This thesis suggests adding a vector processing core to the soft processor as a general-purpose accelerator for these types of applications. The approach has the benefits of a purely software-oriented development model, a fixed ISA allowing parallel software and hardware development, a single accelerator that can accelerate multiple functions in an application, and scalable performance with a single source code. With no hardware design experience needed, a software programmer can make area-versus-performance tradeoffs by scaling the number of functional units and register file bandwidth with a single parameter. The soft vector processor can be further customized by a number of secondary parameters to add and remove features for the specific application to optimize resource utilization. This thesis shows that a vector processing architecture maps efficiently into an FPGA and provides a scalable amount of performance for a reasonable amount of area. Configurations of the soft vector processor with different performance levels are estimated to achieve speedups of 2-24x for 5-26x the area of a Nios II/s processor on three benchmark kernels.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:BVAU.2429/2394 |
| Date | 11 1900 |
| Creators | Yu, Jason Kwok Kwun |
| Publisher | University of British Columbia |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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