[Nets-seminars] Seminar Friday 9th May GS/102 66-72 Gower street 16:00

[Richard G. Clegg]

Don't forget this week's seminar, Friday 9th May GS/102 66-72 Gower 
street 16:00.  If you're coming from outside UCL, then email me to be be 
sure you can get in the building.  Our speaker is Eiko Yoneki from 
Cambridge.

Title: Scale-up Graph Processing in Single Computer: A Storage-centric View

The determinant of performance in scale-up graph processing on single computers is the speed at which graphs can be fetched from storage: either from disk into memory or from memory into CPU-cache. Executing algorithms that follow edges inevitably results in random access to the storage medium for the graph, which can often be the determinant of performance, regardless of the algorithmic complexity or runtime efficiency of the actual algorithm in use. A storage-centric viewpoint would suggest a solution to this problem in recognising that graphs represent a unique workload, and therefore should be treated as such by adopting novel ways to access graph structured data. Two approaches have emerged: using indexed random access or streaming sequential access. Streaming sequential access takes advantage of the fact that sequential access bandwidth is much larger than random access bandwidth, but it requires all edges to be read from secondary storage, whereas indexed access only requires access to the edges that will be needed. I will compare two contrasting approaches and demonstrate the benefit of each; then introduce a new hybrid approach that dynamically chooses, for each iteration of a graph algorithm, between indexed and streaming access. I will also briefly introduce our ongoing work on hybrid graph computation task scheduling using Accelerated Processing Units (APUs), where GPU cores are integrated into CPU chip design. This approach gives significant performance improvement on skewed graph computation workload.
  
Bio: Eiko Yoneki is an EPSRC Research Fellow in the Systems Research Group of the University of Cambridge Computer Laboratory. Her current research focuses on the exploration of new abstractions for supporting the design and implementation of robust and heterogeneous large-scale graph data processing, ranging from cluster computing to single computer environments. More information can be found athttp://www.cl.cam.ac.uk/~ey204/.


-- 
Richard G. Clegg,
Dept of Elec. Eng.,
University College London
http://www.richardclegg.org/



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