Gluon: A Communication-Optimizing Substrate for Distributed Heterogeneous Graph Analytics
This paper introduces a new approach to building distributed-memory graph analytics systems that exploits heterogeneity in processor types (CPU and GPU), partitioning policies, and programming models. The key to this approach is Gluon, a communication-optimizing substrate.
Programmers write applications in a shared-memory programming system of their choice and interface these applications with Gluon using a lightweight API. Gluon enables these programs to run on heterogeneous clusters and optimizes communication in a novel way by exploiting structural and temporal invariants of graph partitioning policies.
To demonstrate Gluon's ability to support different programming models, we interfaced Gluon with the Galois and Ligra shared-memory graph analytics systems to produce distributed-memory versions of these systems named D-Galois and D-Ligra, respectively. To demonstrate Gluon's ability to support heterogeneous processors, we interfaced Gluon with IrGL, a state-of-the-art single-GPU system for graph analytics, to produce D-IrGL, the first multi-GPU distributed-memory graph analytics system.
Our experiments were done on CPU clusters with up to 256 hosts and roughly 70,000 threads and on multi-GPU clusters with up to 64 GPUs. The communication optimizations in Gluon improve end-to-end application execution time by ~2.6$x on the average. D-Galois and D-IrGL scale well and are faster than Gemini, the state-of-the-art distributed CPU graph analytics system, by factors of ~3.9x and ~4.9x, respectively, on the average.
Fri 22 Jun (GMT-04:00) Eastern Time (US & Canada) change
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Changwan Hong, Aravind Sukumaran-RajamOhio State University, USA, Jinsung KimOhio State University, USA, Prashant Singh Rawat, Sriram KrishnamoorthyPacific Northwest National Laboratories, Louis-Noël PouchetColorado State University, Fabrice RastelloINRIA, P. SadayappanOhio State UniversityMedia Attached
|16:35 - 17:00|
Roshan DathathriUniversity of Texas at Austin, USA, Gurbinder GillUniversity of Texas at Austin, USA, Loc HoangUniversity of Texas at Austin, USA, Hoang-Vu DangUniversity of Illinois at Urbana-Champaign, USA, Alex BrooksUniversity of Illinois at Urbana-Champaign, USA, Nikoli DrydenUniversity of Illinois at Urbana-Champaign, USA, Marc SnirUIUC, Keshav PingaliUniversity of Texas at Austin, USAMedia Attached
|17:00 - 17:25|
Umut A. AcarCarnegie Mellon University, Arthur CharguéraudInria, Adrien Guatto, Mike Rainey, Filip SieczkowskiUniversity of WrocławMedia Attached