Tile size selection for low-power tile-based architectures

Authors:
John Oliver;Ravishankar Rao;Michael Brown;Jennifer Mankin;Diana Franklin;Frederic T. Chong;Venkatesh Akella
Affiliations:
University of California, Davis, CA;University of California, Davis, CA;Cal Poly State University, San Luis Obispo, CA;Cal Poly State University, San Luis Obispo, CA;Cal Poly State University, San Luis Obispo, CA;University of California, Santa Barbara, CA;University of California, Davis, CA
Venue:
Proceedings of the 3rd conference on Computing frontiers
Year:
2006

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Abstract

In this paper, we investigate the power implications of tile size selection for tile-based processors. We refer to this investigation as a tile granularity study. This is accomplished by distilling the architectural cost of tiles with different computational widths into a system metric we call the Granularity Indicator (GI). The GI is then compared against the communications exposed when algorithms are partitioned across multiple tiles. Through this comparison, the tile granularity that best fits a given set of algorithms can be determined, reducing the system power for that set of algorithms. When the GI analysis is applied to the Synchroscalar tile architecture[1], we find that Synchroscalar's already low power consumption can be further reduced by 14% when customized for execution of the 802.11a reciever. In addition, the GI can also be a used to evaluate tile size when considering multiple applications simultaneously, providing a convenient platform for hardware-software co-design.