Off-campus UMass Amherst users: To download campus access dissterations, please use the following link to log into our proxy server with your UMass Amherst user name and password.

Non-UMass Amherst users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Dissertations that have an embargo placed on them will not be available to anyone until the embargo expires.

Document Type

Open Access

Degree Program

Electrical & Computer Engineering

Degree Type

Master of Science in Electrical and Computer Engineering (M.S.E.C.E.)

Year Degree Awarded

2009

Month Degree Awarded

May

Keywords

soft processor, FPGA, multi core, automatic synthesis, application specific customization, scalability

Abstract

Soft multiprocessor systems exploit the plentiful computational resources available in field programmable devices. By virtue of their adaptability and ability to support coarse grained parallelism, they serve as excellent platforms for rapid prototyping and design space exploration of embedded multiprocessor applications. As complex applications emerge, careful mapping, processor and interconnect customization are critical to the overall performance of the multiprocessor system. In this thesis, we have developed an automated scalable framework to efficiently map applications written in a high-level programmer-friendly language to customizable soft-cores. The framework allows the user to specify the application in a high-level language called Streamit. After an initial analysis of the application, a soft multiprocessor system is generated automatically using a set of customizable SPREE processors which communicate with each other over point-to-point FIFO connections. Several micro-architectural features of the processors are then automatically customized on a per-application basis to improve system area, performance and power consumption. The efficiency and scalability of this approach has been validated using a diverse set of eight audio, video and signal processing benchmarks on soft multiprocessor systems consisting of one to sixteen processors. Results show that generated soft multiprocessor systems consisting of sixteen processors can offer up to 6x speedup over a conventional single processor system. Our experiments with soft multiprocessor interconnection networks show that point-to-point topologies perform approximately 2x better than mesh topologies. Finally, we demonstrate that application-specific customizations on the instruction set, memory size, and inter-processor buffer size can improve the area and performance of the generated soft multiprocessor systems. The developed framework facilitates rapid design space exploration of soft multiprocessors.

Share

COinS
 

Advisor(s) or Committee Chair

Tessier, Russell G