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2014 23rd International Conference on Parallel Architecture and Compilation (PACT) (2014)
Edmonton, Canada
Aug. 23, 2014 to Aug. 27, 2014
ISBN: 978-1-5090-6607-0
pp: 475-476
Snehasish Kumar , School of Computing Science, Simon Fraser University
Arrvindh Shriraman , School of Computing Science, Simon Fraser University
Dan Lin , School of Computing Science, Simon Fraser University
Jordon Phillips , School of Computing Science, Simon Fraser University
ABSTRACT
Software data structures are a critical aspect of emerging data-centric applications which makes it imperative to improve the energy efficiency of data delivery. We propose SQRL, a hardware accelerator that integrates with the last-level-cache (LLC) and enables energy-efficient iterative computation on data structures. SQRL integrates a data structure-specific LLC refill engine (Collector) with a compute array of lightweight processing elements (PEs). The collector exploits knowledge of the compute kernel to i) run ahead of the PEs in a decoupled fashion to gather data objects and ii) throttle fetch rate and adaptively tile the dataset based on the locality characteristics. The collector exploits data structure knowledge to find the memory level parallelism and eliminate data structure instructions.
INDEX TERMS
Data structures, Kernel, Out of order, Hardware, Open area test sites
CITATION
Snehasish Kumar, Arrvindh Shriraman, Vijayalakshmi Srinivasan, Dan Lin, Jordon Phillips, "SQRL: Hardware accelerator for collecting software data structures", 2014 23rd International Conference on Parallel Architecture and Compilation (PACT), vol. 00, no. , pp. 475-476, 2014, doi:10.1145/2628071.2628118
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