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About Me
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- Ph.D Student - Research Assistant
- Address:
Computer Sciences Department
University of Wisconsin
1210 West Dayton Street
Madison, WI 53706
- Room: 7352
- Phone: +1-608-262-6622
- Fax: +1-608-262-9777
- Email: mjbrim (at) cs.wisc.edu
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Educational Background
B.S. in Computer Science, 2000
Ohio Northern University
Minors: Mathematics, Business Administration
M.S. in Computer Sciences, May 2003
University of Wisconsin - Madison
Ph.D. in Computer Sciences, expected completion 2010
University of Wisconsin - Madison
Ph.D Minor: Business (Information Systems)
Research Interests
Distributed & cluster computing, which just about covers every area
of computer science. More specifically, I'm
interested in cluster software and hardware infrastructure, including
administration tools, advanced networking & communication software,
distributed and parallel file systems, and optimized operating systems.
Current Research @ UW
I am a member of the Paradyn
project. Paradyn is a performance measurement tool that allows dynamic
instrumentation and performance tuning/monitoring of parallel and distributed
user-level programs.
My Ph.D. thesis topic focuses on improving the scalability of tools and
middleware for extreme-scale High Performance Computing (HPC, aka HEC)
systems. I'm looking into how we might leverage Tree-Based Overlay Networks
(TBONs) to provide an intuitive and scalable approach for performing
process control and inspection on groups of distributed processes. As a key
part of my research, I have defined a new idiom, group file operations,
as a general solution for scalable operations on distributed files.
My initial research at UW focused on a closely related subproject of Paradyn
called KernInst, which
can be used to dynamically instrument and
monitor the performance of commodity operating system kernels.
I ported KernInst for the x86 architecture and Linux 2.4 & 2.6 kernels.
My research using KernInst focused on how to dynamically modify the
kernel to improve the performance of parallel application workloads
through code specialization techniques.
Past Research @ ORNL
While at Oak Ridge National Laboratory, I worked on many projects related
to high-performance
computing with specific focus on commodity cluster infrastructure
software. The two main projects I was involved with are:
Cluster Command & Control (C3) Tool Suite
C3 is a suite of tools that can be used to efficiently manage Linux clusters.
The suite includes tools for cluster-wide command execution, file
distribution and gathering, process termination, and system
image update facilities. C3 uses either rsh or ssh for remote access to
cluster nodes.
Open Source Cluster Application Resources (OSCAR)
OSCAR is a collection of software that enables users with
little cluster experience to easily build a cluster from a
collection of homogeneous machines. OSCAR includes well-known
software used in cluster computing, preventing the user from
having to go out and retrieve and install each piece of software
individually. OSCAR is the first project from the
Open Cluster Group ,
a consortium of groups from industry and research institutions
focused on standardizing open-source cluster solutions.
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