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**Faculty members involved in high performance computing and their areas
of research**

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- Sarita
Adve

Computer architecture, parallel architecture and software, performance
evaluation methods.
- Vikram
Adve

Compilers, programming environments, performance modeling techniques
and tools, and computer architecture, with a particular focus on high-performance
computing and wide-area distributed computing.
- Michael
T. Heath

__General interests__: Large-scale scientific computing, numerical
analysis, parallel computing.

__Specific interests__: Numerical linear algebra, sparse matrix
computation, numerical optimization, parallel performance visualization.
- Eric
de Sturler
- Laxmikant
Kale

Parallel programming tools and techniques, parallel aplications in
science and engineering, parallel symbolic computations.
- David
Padua

Compilers, machine organizations, performance prediction, programming
languages.
- Daniel
Reed,
*Department Head*

Performance instrumentation and analysis techniques for large-scale
parallel systems, dynamic parallel resource management, parallel I/O access
pattern analysis.
- Robert
D. Skeel

Parallel algorithms and software for biomolecular modeling with an
emphasis on numerical methods.
- Shang-Hua
Teng

Mesh generation, graph partitioning, computational geometry, parallel
scientific computing, combinatorial optimization, algorithms and cryptography.
- Josep
Torrellas

Multithreading, processor-memory integration, scalability tools for
parallel applications, cache coherence, COMA vs NUMA, software based COMA,
speculative execution, database workloads, forwarding.
- Marianne
Winslett

High performance I/O for parallel computing. The Panda project's goal
is to provide high-performance input and output by optimizing resource
utilization during movement of data between memory and secondary storage.