Abstract:
We live in an age where enormous amount of data is being collected constantly because of smart phones, ubiquitous presence of sensors and the wide-spread use of social media. Useful and cost-effective analysis of this data is the biggest economic driver for the IT industry. Such analyses are often done in data centers or on cluster of machines because they involve applying sophisticated algorithms to terabyte-size graphs, which are extremely irregular and sparse. We will show how low-power appliances for such analyses can be built using flash storage and hardware accelerators. Such appliances are likely to be 10X cheaper than 16-32 node server clusters and will come in the form factor of an SSD to be plugged into your laptop.
Bio:
Arvind is the Head of Computer Science Faculty and the Charles and Jennifer Johnson Professor of Computer Science and Engineering at MIT. Arvind’s group, in collaboration with Motorola, built the Monsoon dataflow machines and its associated software in the late eighties. In 2000, Arvind started Sandburst which was sold to Broadcom in 2006. In 2003, Arvind co-founded Bluespec Inc., an EDA company to produce a set of tools for high-level synthesis. Arvind's current research focus is to enable rapid development of embedded systems and designing complex digital chips with associated correctness proofs. Arvind is a Fellow of IEEE and ACM, and a member of the National Academy of Engineering and the American Academy of Arts and Sciences.
http://csg.csail.mit.edu/Users/arvind/
