Michael Monkang Chu

EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-01-1134
2001

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2001/CSD-01-1134.pdf

Reconfigurable computing devices offer substantial improvements in functional density and yield versus traditional microprocessors, yet remain out of general-purpose use due in part to their difficulty of programming and lack of cross-device compatibility. In a stream-based compute model called SCORE (Stream Computations Organized for Reconfigurable Execution) was introduced with a goal to provide a programming model for easily exploiting the computational density of reconfigurable devices. SCORE virtualizes reconfigurable resources (compute, storage, and communication) by dividing a computation up into fixed-size "pages" and time-multiplexing the virtual pages on available physical hardware. Consequently, SCORE applications can scale up or down automatically to efficiently run on a wide range of hardware. In this project we implemented project implements a dynamic runtime scheduler for SCORE that virtualizes the reconfigurable computation fabric and automatically manages the execution of SCORE applications in hardware. Initial performance scaling experiments show that a dynamic scheduler is able to automatically scale applications on reduced hardware and exploit hardware under-utilization to achieve reasonable area-time curves. In this paper, we present the basic scheduler details and runtime system flow along with key implementation highlights, such as scheduling heuristics, memory management, and deadlock detection.

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BibTeX citation:

@techreport{Chu:CSD-01-1134,
    Author = {Chu, Michael Monkang},
    Title = {Dynamic Runtime Scheduler Support for SCORE},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {2001},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2001/6433.html},
    Number = {UCB/CSD-01-1134},
    Abstract = {Reconfigurable computing devices offer substantial improvements in functional density and yield versus traditional microprocessors, yet remain out of general-purpose use due in part to their difficulty of programming and lack of cross-device compatibility. In a stream-based compute model called SCORE (Stream Computations Organized for Reconfigurable Execution) was introduced with a goal to provide a programming model for easily exploiting the computational density of reconfigurable devices. SCORE virtualizes reconfigurable resources (compute, storage, and communication) by dividing a computation up into fixed-size "pages" and time-multiplexing the virtual pages on available physical hardware. Consequently, SCORE applications can scale up or down automatically to efficiently run on a wide range of hardware. In this project we implemented project implements a dynamic runtime scheduler for SCORE that virtualizes the reconfigurable computation fabric and automatically manages the execution of SCORE applications in hardware. Initial performance scaling experiments show that a dynamic scheduler is able to automatically scale applications on reduced hardware and exploit hardware under-utilization to achieve reasonable area-time curves. In this paper, we present the basic scheduler details and runtime system flow along with key implementation highlights, such as scheduling heuristics, memory management, and deadlock detection.}
}

EndNote citation:

%0 Report
%A Chu, Michael Monkang
%T Dynamic Runtime Scheduler Support for SCORE
%I EECS Department, University of California, Berkeley
%D 2001
%@ UCB/CSD-01-1134
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2001/6433.html
%F Chu:CSD-01-1134