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TERATEC 2016 Forum
Workshop 3 - Wednesday, June 29 from 9:00 to 12:30
Tools and algorithms for Big Data applications

Analyse de graphes sur GPU
Alex FENDER, Software Engineer, NVIDIA

Abstract: Some of the largest problems in data analytics can be best described as graphs.  To handle these problems with GPUs requires specialized algorithms and deep knowledge of the GPU architecture. Nvidia will provide a new library for graph analytics as part of the CUDA 8.0 toolkit, to enable more users to take advantage of the bandwidth and parallel processing capabilities of GPUs.  NvGraph provides graph primitives such as graph construction, subgraph extraction, along with pre-tuned algorithms for analytics: https://developer.nvidia.com/nvgraph .  The NVIDIA Graph Analytics library features an advanced Pagerank calculator, single source shortest path (SSSP), widest path, and a semi-ring based SpMV operator which automatically load balances any sparsity pattern.
We introduce nvGraph, present performance benchmark and describe the future path forward.

Bio: Alex Fender is a Software Engineer at NVIDIA where he has been working for 2 years on emerging applications in graph analytics and sparse iterative methods. He is involved in the development of CUDA libraries such as nvGraph and AmgX. Alex is also a PhD candidate at the University of Paris-Saclay with research interests in spectral graph analysis. Previously, he worked at Silkan and Dailymotion, he attended University Of Versailles and Ecole Central Paris for his M.Sc. See latest updates on Alex’s bio at https://linkedin.com/in/alexandrefender

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