[Crib-list] SPEAKER: Hang Liu (UMass, Lowell) | Computational Research in Boston and Beyond Seminar (CRIBB) | Friday, April 5, 2019 | TIME: 12:00 PM - 1:00 PM in Building 32, Room 141 (STATA)

[Shirley Entzminger]

 	              Computational Research in Boston and Beyond Seminar
 				          (CRIBB)



DATE:		Friday, April 5, 2019

TIME:		12:00 PM to 1:00 PM

LOCATION:	Building 32, Room 141  (STATA)
 		       32 Vassar Street
 		       Cambridge, MA

 		     (Pizza/beverages will be provided at 11:45 AM outside
 		      Room 32-141)


TITLE:		Software-Hardware Co-Optimized Data Analytics


SPEAKER:	Hang Liu  (University of Massachusetts, Lowell)


ABSTRACT:


We are increasingly awash in data, both connected and disconnected, as a 
growing array of “sensors”, which is integrated in our daily life, continues to 
generate an explosive amount of data. Notably, IBM recently suggests that we 
are creating ~2.5 quintillion bytes of data per day. Buried in such a rapidly 
growing flood of data are the key insights to resolve the critical issues 
surrounding our society, for improving productivity, enlisting new economic 
opportunities, and uncovering novel discoveries in science and engineering. 
While accommodating traditional queries, such as, word count, is 
straightforward, the emerging data analytical applications (e.g., graph 
analytics) tend to be more complex, thus will place server tax on conventional 
hardware systems. This talk unveils the enormous potentials of the emerging 
hardware, such as, Graphics Processing Unit (GPU), Field-Programmable Gate 
Array (FPGA) and Non-Volatile Memory express (NVMe). At meantime, Dr. Liu 
demonstrates how his work (i.e., USENIX FAST ‘17, DAC ‘19 and a recent 
submission to SIGMOD ‘20) leverages the new hardware to accelerate complex 
analytical applications on both connected and disconnected data. As the future 
work, this talk further outlines the mounting challenges as well as the 
potential solutions for deploying the popular graph learning framework on 
hardware accelerators.


Bio:

Dr. Hang Liu is currently an assistant professor in the Department of 
Electrical and Computer Engineering at University of Massachusetts Lowell. He 
receives the Ph.D. degree from the George Washington University in 2017, and 
B.E. from Huazhong University of Science and Technology in 2011. His research 
interests include exploiting emerging hardware to build high-performance 
systems for graph computing, machine learning, data compression, numerical 
simulation, cloud computing and software debugging. His publications appear in 
top tier conferences, such as, SC, SIGMOD, USENIX FAST and DAC. Particularly, 
he is the recipient of the NSF CRII award and the Champion of 2018 
DARPA/MIT/AMAZON Graph Challenge. He is also the winner of the Best 
Dissertation Award from the Department of Electrical and Computer Engineering 
at the George Washington University. Notably, his graph traversal systems are 
ranked highly in both Graph500 and Green Graph500 benchmarks, which measure the 
performance and energy efficiency of the most powerful supercomputers in the 
world.


===================================================================

Massachusetts Institute of Technology
Cambridge, MA


For information about the Computational Research in Boston and Beyond Seminar 
(CRIBB), please visit....

 			http://math.mit.edu/crib/



===

Shirley A. Entzminger
Administrative Assistant II
Department of Mathematics
Massachusetts Institute of Technology
77 Massachusetts Avenue
Building 2, Room 350A
Cambridge, MA 02139
PHONE:	(617) 253-4347
FAX:	(617) 253-4358
E-mail:	daisymae at math.mit.edu
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