[CSEE-colloq] CSEE Colloquium in 2 minutes in ITE 227 - Tyler Simon

[Yaacov Yesha]

---------- Forwarded message ----------
From: Yaacov Yesha <yayesha1 at gmail.com>
Date: Thu, Sep 20, 2012 at 3:00 AM
Subject: CSEE Colloquium on September 21 at 1:00 pm - Simon on task
scheduling for high performance distributed systems
To: csee-colloquium-out at cs.umbc.edu




---------- Forwarded message ----------
From: Tim Finin <finin at cs.umbc.edu>
Date: Wed, Sep 12, 2012 at 8:24 AM
Subject: [Csee-faculty-tt] [CSEE-colloq] talk: Simon on Task Scheduling for
High Performance Distributed Systems, 1pm Fri 9/21
To: csee-colloquium-out at cs.umbc.edu


                           CSEE Colloquium

             A Novel Dynamic Task Scheduling Environment
               for High Performance Distributed Systems

                             Tyler Simon
                   Faculty Research Assistant, UMBC

           1:00pm Friday, 21 September 2012, ITE 227, UMBC

The number of concurrently executing tasks required for a single
application to perform at the petascale is on the order of hundreds of
thousands. Given current manycore hardware trends, future peta- and
exa-scale class systems will require applications to run tasks on the
order of hundreds of millions to billions. To address the problem of
creating, running and managing jobs of this scale, both from a system
user and administration perspective we have developed, ARRIA, an
Autonomic Runtime for Resource Intensive Applications. ARRIA uses a
decentralized bag of tasks and workload scheduler that increases
individual job priorities based on weighed factors that are of
interest to the application programmer or the system administrator.
ARRIA is designed to run millions of independent tasks reliably and
efficiently without explicit message passing from the user. In
previous work, using the ARRIA scheduler for scientific MapReduce
workloads, we have shown a 2.1x speedup over the Hadoop Fair Share
scheduler. We investigate novel scheduling parameters and strategies
that guarantee efficient job execution for a wide range of realistic
and simulated workloads with both user and administrator objectives,
such as increased throughput and maximized utilization with minimal
wait times for specific job classes. Finally our experiments
investigate the long tail phenomenon for mixed workloads and the
overheads incurred for increased system size.

Mr. Simon has undergraduate degrees in Computer Science and Philosophy
with a Master of Science in Computer Science from the University of
Mississippi, he is currently pursuing a PhD in Computer Science at the
University of Maryland Baltimore County.  Mr. Simon has worked
professionally in the high performance computing (HPC) field for over
a decade. In 2005 he earned a Department of Energy graduate research
fellowship at Oak Ridge National Laboratory, where he worked for in
the Computer Science and Mathematics Division developing and
implementing the Freeloader distributed storage system.  Mr. Simon has
worked as a computational scientist for the Department of Defense High
Performance Computing Modernization Office based at the U.S. Army
Engineer Research and Development Center in Vicksburg, MS, evaluating
both current and future HPC system requirements for applications of
interest to the Department of Defense. Since 2009 Mr.  Simon has been
a computational scientist and manager of HPC user services at the NASA
Center for Climate Simulation at Goddard Space Flight Center and is
currently a Faculty Research Assistant at the University of Maryland
Baltimore County working at the NSF Center for Hybrid Multicore
Productivity Research.  Mr. Simon’s research involves the study of
dynamic distributed runtime environments, parallelization strategies
and scheduling of large scale scientific applications for current
petascale and future HPC architectures.

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