Galois Tech Talk: Requirements and Performance of Data Intensive, Irregular Applications
Iavor Diatchki
open to the interested public. Please join us!
Please note the unusual day for this talk: it is on *Friday*, 9 July 2010
title:
Requirements and Performance of Data Intensive, Irregular Applications
presenter:
Dr. John Feo
time:
10:30am, *Friday*, 9 July 2010
location:
Galois Inc.
421 SW 6th Ave. Suite 300, Portland, OR, USA
(3rd floor of the Commonwealth building)
abstract:
Many fundamental science, national security, and business applications
need to process large volumes of irregular, unstructured data. Data
collection and analysis is rapidly changing the way the scientific,
national security, and economic communities operate. There are
worldwide operational deployments of instruments to detect the
proliferation of weapons of mass destruction, monitor terrorist cells,
and track the movement of illicit goods and services. In the next 15
years 30% of battle-space defense forces will be autonomous with each
advanced robotic device carrying dozens of sophisticated sensors
collecting, processing, analyzing and transmitting large amounts of
data. American economic competitiveness will depend increasingly on
the timely analysis of many Petabytes of data collected in diverse
computing clouds charting the social and economic behavior of
consumers.
Unlike traditional scientific applications based on linear algebra
routines, data analytic applications comprise large, integer-based
graph computations with irregular data access patterns, low
computation to memory access ratios, and high levels of fine grain
parallelism that pass data and synchronize frequently. Traditional
architectures optimized to run large-scale floating point intensive
simulations are inadequate, and more suitable high-end architectures
such as the Cray XMT are needed. In this talk I will discuss the
programming language, tools, and system requirements for data analytic
applications. I will survey the research at PNNL’s Center for Adaptive
Supercomputer Software as regards graph analytics. In particular, I
will present several key graph algorithms we have developed with an
emphasis on structure, use of special hardware features, performance,
and scalability.
bio:
Dr. John Feo is the director of the Center for Adaptive Supercomputer
Software at the Pacific Northwest Laboratory. Dr. Feo received his
Ph.D. in Computer Science from The University of Texas at Austin. He
began his career at Lawrence Livermore National Laboratory where he
managed the Computer Science Group and was the principal investigator
of the Sisal Language Project. Dr. Feo then joined Tera Computer
Company (now Cray Inc) where he was a principal engineer and product
manager for the MTA-1 and MTA-2, the first two generations of the
Cray’s multithreaded architecture. After a short two year “sabbatical”
at Microsoft where he led a software group developing a
next-generation virtual reality platform, he joined PNNL
Dr. Feo’s research interests are parallel programming, graph
algorithms, multithreaded architectures, functional languages, and
performance studies. He has published extensively in these fields. He
has held academic positions at UC Davis and is an adjunct faculty at
Washington State University.