Date : 13-09-01
[Seminar] Prof. Xian-He Sun of IIT
Author : Admin
Views : 3,025
Title: Rethinking System Design for Big Data Processing

Speaker: Prof. Xian-He Sun, Illinois Institute of Technology

Date: Sep 6th, (Fri) 15:30

Location: 우정관 (Woojung Building), 205 lecture room, Korea University

Computing becomes more and more data-intensive. The lasting memory-wall
problem of system design compounded with the newly emerged big-data problem
of application practice has changed the landscape of computing. CPU speed is
no longer the performance bottleneck of a high-end computing system, the data
access speed is, whereas the data access speed is limited by the performance
of memory and file systems. Concurrency exists in memory and file systems.
Historically, this concurrency is designed and utilized around computing, not
sustained data accessing. A paradigm shift is needed to support data-centric
computing. In this talk we introduce the memory parallelism concept.
First, we review the concurrency available in modern memory systems,
and propose the C-AMAT formulation for system design analysis of concurrent
data accesses. Next, we illustrate the difference between memory-concurrency
from a computing-centric view and memory-parallelism from a data-centric view,
and discuss the considerations of utilizing parallel data access for big data
applications. Finally, we present some of our recent results which quantize
and utilize parallel I/O following the memory-parallelism concept.

Dr. Xian-He Sun is the chairman and a professor of the Department of
Computer Science, the director of the Scalable Computing Software laboratory
at the Illinois Institute of Technology (IIT) and a guest faculty in the Mathematics
and Computer Science Division at the Argonne National Laboratory.
Before joining IIT, he worked at DoE Ames National Laboratory, at ICASE,
NASA Langley Research Center, at Louisiana State University, Baton Rouge,
and was an ASEE fellow at Navy Research Laboratories. Dr. Sun is an IEEE
fellow and is known for his memory-bounded speedup model, also called
Sun-Ni’s Law, for scalable computing. His research interests include parallel
and distributed processing, high-end computing, memory and I/O systems,
and performance evaluation. He has close to 200 publications and 4 patents
in these areas. He is a vice chair of the IEEE Technical Committee on Scalable
Computing, a member of the IEEE fellow evaluation committee, serving and
served on the editorial board of most of the leading professional journals in
the field of parallel processing, and is a named overseas expert of Chinese
Academy of Sciences. More information about Dr. Sun can be found at his
web site