CSE LECTURE SERIES
Colloquium and Distinguished
Jignesh Patel
University of Wisconsin
Wednesday, November 25, 2013
11:00AM - 12:00PM
CSE 1202
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Data @ Bare Metal Speed
Big data platforms today largely employ data processing kernels that were developed for a now
bygone hardware era. Modern hardware has made a fundamental shift in recent years, driven by
two dominating factors: power consumption limits for hardware components, and the transformation of the traditional memory hierarchy because of large main memory configurations and flashbased storage. Because of this shift, we are now building a “deficit” between the pace at which the
hardware is evolving and the pace that is demanded by data processing kernels to keep up with the
growth of big data. This deficit is unsustainable in the long run as it requires building exponentially
larger data centers to keep up with the anticipated growth in data volumes. One way to “pay off” this
deficit is to have hardware and software co-evolve to exploit the full potential of the hardware.
Luckily, even on current hardware, there is potential for an order-of-magnitude (or more) in
improvement if one uses this perspective to redesign data processing kernels. I will provide some
examples of recent work from our Quickstep project that demonstrates the merit of this line of
thinking. I will then speculate on other data processing mechanisms that will likely be needed in the
future to continue to keep this hardware deficit under control.
Biography
”
Jignesh Patel is a Professor in Computer Sciences at the University of Wisconsin-Madison, which is where he also got his PhD. He has worked
in the area of databases (now called “big data”) for over two decades. He is the recipient of an NSF Career Award, and multiple Google, IBM,
Microsoft, and Oracle faculty awards. His papers have been selected as the “best papers in the conference” at VLDB (2012), SIGMOD (2011),
and ICDE (2010, 2011). He also has a strong interest in seeing research ideas transition to actual products. His thesis work was commercialized
via an acquisition by NCR/Teradata. He also co-founded Locomatix, a startup that built a platform to power real-time data-driven mobile
services. Locomatix became part of Twitter in 2013. Jignesh is also an ACM Distinguished Scientist. He blogs at bigfastdata.blogspot.com.
For more information, please contact the Chair’s Office at (858) 822-5198 or [email protected]