SC12 Home > SC12 Schedule > SC12 Presentation - Large-Scale Energy-Efficient Graph Traversal - A Path to Efficient Data-Intensive Supercomputing

SCHEDULE: NOV 10-16, 2012

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Large-Scale Energy-Efficient Graph Traversal - A Path to Efficient Data-Intensive Supercomputing

SESSION: Breadth First Search

EVENT TYPE: Papers

TIME: 11:30AM - 12:00PM

SESSION CHAIR: Umit Catalyurek

AUTHOR(S):Nadathur Satish, Changkyu Kim, Jatin Chhugani, Pradeep Dubey

ROOM:255-EF

ABSTRACT:
Graph-traversal is used in many fields including social-networks, bioinformatics and HPC. The push for HPC machines to be rated in ``GigaTEPS" (billions-of-traversed-edges-per-second) has led to the Graph500 benchmark. Graph-traversal is well-optimized for single-node CPUs. However, current cluster implementations suffer from high-latency and large-volume inter-node communication, with low performance and energy-efficiency. In this work, we use novel low-overhead data-compression techniques to reduce communication-volumes along with new latency-hiding techniques. Keeping the same optimized single-node algorithm, we obtain 6.6X performance improvement and order-of-magnitude energy savings over state-of-the-art techniques. Our Graph500 implementation achieves 115 GigaTEPS on 320-node Intel-Endeavor cluster with E5-2700 Sandybridge nodes, matching the second-ranked result in the November-2011 Graph500 list with 5.6X fewer nodes. Our per-node performance only drops 1.8X over optimized single-node implementations, and is highest in the top 10 of the list. We obtain near-linear scaling with node count. On 1024 Westmere-nodes of the NASA-Pleiadas system, we obtain 195 GigaTEPS.

Chair/Author Details:

Umit Catalyurek (Chair) - Ohio State University

Nadathur Satish - Intel Corporation

Changkyu Kim - Intel Corporation

Jatin Chhugani - Intel Corporation

Pradeep Dubey - Intel Corporation

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Large-Scale Energy-Efficient Graph Traversal - A Path to Efficient Data-Intensive Supercomputing

SESSION: Breadth First Search

EVENT TYPE:

TIME: 11:30AM - 12:00PM

SESSION CHAIR: Umit Catalyurek

AUTHOR(S):Nadathur Satish, Changkyu Kim, Jatin Chhugani, Pradeep Dubey

ROOM:255-EF

ABSTRACT:
Graph-traversal is used in many fields including social-networks, bioinformatics and HPC. The push for HPC machines to be rated in ``GigaTEPS" (billions-of-traversed-edges-per-second) has led to the Graph500 benchmark. Graph-traversal is well-optimized for single-node CPUs. However, current cluster implementations suffer from high-latency and large-volume inter-node communication, with low performance and energy-efficiency. In this work, we use novel low-overhead data-compression techniques to reduce communication-volumes along with new latency-hiding techniques. Keeping the same optimized single-node algorithm, we obtain 6.6X performance improvement and order-of-magnitude energy savings over state-of-the-art techniques. Our Graph500 implementation achieves 115 GigaTEPS on 320-node Intel-Endeavor cluster with E5-2700 Sandybridge nodes, matching the second-ranked result in the November-2011 Graph500 list with 5.6X fewer nodes. Our per-node performance only drops 1.8X over optimized single-node implementations, and is highest in the top 10 of the list. We obtain near-linear scaling with node count. On 1024 Westmere-nodes of the NASA-Pleiadas system, we obtain 195 GigaTEPS.

Chair/Author Details:

Umit Catalyurek (Chair) - Ohio State University

Nadathur Satish - Intel Corporation

Changkyu Kim - Intel Corporation

Jatin Chhugani - Intel Corporation

Pradeep Dubey - Intel Corporation

Add to iCal  Click here to download .ics calendar file

Add to Outlook  Click here to download .vcs calendar file

Add to Google Calendarss  Click here to add event to your Google Calendar