Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/87968
Title: A case for energy-efficient acceleration of graph problems using embedded FPGA-based SoCs
Authors: Moorthy, Pradeep
Kapre, Nachiket
Keywords: Energy Efficiency
Sparse Graphs
DRNTU::Engineering::Computer science and engineering
Issue Date: 2015
Source: Moorthy, P., & Kapre, N. (2015). A case for energy-efficient acceleration of graph problems using embedded FPGA-based SoCs. Supercomputing Frontiers and Innovations, 2(3), 76-86.
Series/Report no.: Supercomputing Frontiers and Innovations
Abstract: Sparse graph problems are notoriously hard to accelerate on conventional platforms due to irregular memory access patterns resulting in underutilization of memory bandwidth. These bottlenecks on traditional x86-based systems mean that sparse graph problems scale very poorly, both in terms of performance and power efficiency. A cluster of embedded SoCs (systems-on-chip) with closely-coupled FPGA accelerators can support distributed memory accesses with better matched low-power processing. We first conduct preliminary experiments across a range of COTS (commercial off-the-shelf) embedded SoCs to establish promise for energy-efficiency acceleration of sparse problems. We select the Xilinx Zynq SoC with FPGA accelerators to construct a prototype 32-node Beowulf cluster. We develop specialized MPI routines and memory DMA offload engines to support irregular communication efficiently. In this setup, we use the ARM processor as a data marshaller for local DMA traffic as well as remote MPI traffic while the FPGA may be used as a programmable accelerator. Across a set of benchmark graphs, we show that 32-node embedded SoC cluster can exceed the energy efficiency of an Intel E5-2407 by as much as 1.7× at a total graph processing capacity of 91–95 MTEPS for graphs as large as 32 million nodes and edges.
URI: https://hdl.handle.net/10356/87968
http://hdl.handle.net/10220/45595
ISSN: 2409-6008
DOI: http://dx.doi.org/10.14529/jsfi150307
Rights: © 2015 The Author(s). This paper is distributed under the terms of the Creative Commons Attribution-Non Commercial 3.0 License which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is properly cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Journal Articles

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