Enabling Graph Analytics at Scale: The Opportunity for GPU-Acceleration of Data-Parallel Graph Analytics (Application to Bioinformatics) – Brad Bebee ODSC Boston 2015
ConferencesToolsTools & LanguagesODSC East 2015|Speaker Slidesposted by Open Data Science June 3, 2015 Open Data Science
From social networks to protein networks to financial transactions,
graphs are everywhere. Graph Analytics represent a key tool for
data science to take advance of this type of network information.
Many “Bigdata” and NoSQL techniques for analysis and data science
that work well for relational and structured data, do not scale effectively
when applied to challenges in graph analytics and traversal algorithms.
The data locality and graph access patterns challenge existing
HW architectures and place a premium on bandwidth to main memory.
GPUs currently have 10X advantage over CPUs in this area.
The advantage is projected to grow to 100X by 2016. This talk will
discuss why GPUs are game-changer by dramatically improving
the price-performance ratio for very large graph analytics over
existing technologies. It will present results for work in GPU
Acceleration of graph analytics within both research and industry applications.
Throughout his career, Brad Bebee has helped customers navigate complex technology and business challenges to deliver products and solutions that solve them quickly and effectively. Brad is currently leading SYSTAP’s efforts to deliver it’s game changing technology to use GPU Acceleration for data parallel graph analytics. This will enable new classes of applications for graph analytics in Data Science and large scale data analytics by dramatically improving the price-performance ratio for very high speed graphs.