7921

A Yoke of Oxen and a Thousand Chickens for Heavy Lifting Graph Processing

Abdullah Gharaibeh, Lauro Beltrao Costa, Elizeu Santos-Neto, Matei Ripeanu
Department of Electrical and Computer Engineering, The University of British Columbia
IEEE/ACM International Conference on Parallel Architectures and Compilation Techniques (PACT 2012), 2012

@article{gharaibeh2012totem,

   title={TOTEM: Graph Processing on Heterogeneous CPU and GPU Platforms},

   author={Gharaibeh, A. and Santos-Neto, E. and Costa, L.B. and Ripeanu, M.},

   year={2012}

}

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Large, real-world graphs are famously difficult to process efficiently. Not only they have a large memory footprint but most graph processing algorithms entail memory access patterns with poor locality, data-dependent parallelism, and a low compute-to-memory access ratio. Additionally, most real-world graphs have a low diameter and a highly heterogeneous node degree distribution. Partitioning these graphs and simultaneously achieve access locality and load-balancing is difficult if not impossible. This paper demonstrates the feasibility of graph processing on heterogeneous (i.e., including both CPUs and GPUs) platforms as a cost-effective approach towards addressing the graph processing challenges above. To this end, this work (i) presents and evaluates a performance model that estimates the achievable performance on heterogeneous platforms; (ii) introduces TOTEM – a processing engine based on the Bulk Synchronous Parallel (BSP) model that offers a convenient environment to simplify the implementation of graph algorithms on heterogeneous platforms; and, (iii) demonstrates TOTEM’S efficiency by implementing and evaluating two graph algorithms (PageRank and breadth-first search). TOTEM achieves speedups close to the model’s prediction, and applies a number of optimizations that enable linear speedups with respect to the share of the graph offloaded for processing to accelerators.
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