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The goal of this project is to understand the challenges in supporting graph algorithms on commodity, hybrid platforms; platforms that consist of processors optimized for sequential processing and accelerators optimized for massively-parallel processing.

This will fill the gap between current graph processing platforms that are either expensive (e.g., supercomputers) or inefficient (e.g., commodity clusters). Our hypothesis is that hybrid platforms (e.g., GPU-supported large-memory nodes and GPU supported clusters) can bridge the performance-cost chasm, and offer an attractive graph-processing solution for many graph-based applications such as social networks and web analysis.


Scott Sallinen
Matei Ripeanu


[2] Graph Colouring as a Challenge Problem for Dynamic Graph Processing on Distributed Systems, Scott Salinnen, Keita Iwabuchi, Suraj Poudel, Roger Pearce, Matei Ripeanu, IEEE/ACM International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2016), Salt Lake City, UT November 2016 (acceptance rate: 82/446=18.3%) pdf slides
[1] Systems for Near Real-Time Analysis of Large-Scale Dynamic Graphs, Luis M. Vaquero, Felix Cuadrado, Matei Ripeanu, Technical Report arXiv:1410.1903, October 2014.

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