39. SCALABLE SYSTEM SOFTWARE FOR
PETASCALE COMPUTER SYSTEMS
High-performance computing (HPC) research in the Office of
Science at the U.S. Department of Energy supports research that contributes to
comprehensive, scalable, and robust computing to enable scientific discoveries.
The HPC currently supports research and development that focus on
petascale computing systems - computers operate 1000 times faster than today’s
petascale systems. The primary areas
of research include scalable system software, scientific visualization systems,
data management tools, programming models, and related issues.
Grant applications addressing these issues are sought in the following
subtopics:
a. Petascale System
Software—Emerging large-scale science endeavors increasingly call for
extreme-scale supercomputing systems. These
systems, which will exploit tens to hundreds of thousands of processors, will be
based on a variety of challenging architectures from distributed memory clusters
of unprecedented scale to radically different innovative architectural concepts
such as PIMs, FPGAs, and complex memory hierarchies.
This requirement can be met by internal parallel I/O subsystems that
comprise dedicated I/O nodes, each with processor, memory, and disks.
Massively parallel processors (MPPs), encompassing from tens to thousands
of processors, are emerging as a major architecture for high-performance
computers. The new supercomputing systems will differ greatly in scale and
complexity from today’s systems, placing new and challenging demands on system
software and related supporting hardware subsystems.
Grant applications for these proposed system software components and
hardware subsystems must address the needs for:
1) optical transceiver development to improve CPU to CPU and CPU to
memory bandwidth performance over copper based solutions, 2) operating systems
tools and support for the effective management of terascale systems and beyond;
and (3) effective tools for feature identification, (4) parallel and network
I/O, and 5) scheduler, lightweight communication mechanisms, and queue
management tools, 6) FPGA algorithm accelerator development that maximizes the
performance of specific algorithms through a direct connection to the network
infrastructure.
Questions – contact Thomas Ndousse-Fetter (tndousse@science.doe.gov)
b. Petascale File
Systems—Global parallel file systems such as GPFS and Lustre are widely
used in the Office of Science to manage file systems in its major computer
systems with few thousand processors. This
subtopic supports the development of file systems that can scale to thousands of
processors. This can be achieved by
scaling existing file systems or developing new ones.
It is well understood that the bandwidth to storage devices is not
keeping pace with computational trends and that the gap will continue to widen
in the future. A balanced petascale
computer with 100,000 processors will require on the order of 1 Terabytes per
second (TB/s) bandwidth. In order to
efficiently utilize Petascale computing resources to provide breakthrough
science, proposals are sought that address the scaling, performance, and/or
stability of an existing or new global parallel file system.
Grant applications are sought to develop scalable parallel file systems
that explore the use of clustered metadata and metadata checksum/mirroring to
handle up to one trillion files in a file system; address the scaling,
performance, and/or stability of an existing global parallel file system; and to
develop I/O disk and client services to bind the global file systems to storage
systems and petascale computing systems.
Questions – contact Thomas Ndousse-Fetter (tndousse@science.doe.gov)
c. Debugging and
Performance Monitoring of Petascale Systems—Current supercomputing systems
consisting of thousands of nodes cannot meet the demands of emerging high-performance
scientific applications. As a
result, a new generation of supercomputing systems consisting of hundreds of
thousands of nodes is being proposed. However,
these systems are likely to experience far more frequent failures than today's
systems, and such failures must be tackled effectively.
Coordinated check-pointing is a common technique to deal with failures in
petascale computing system. Unlike
most of the existing check-pointing models, the proposed model takes into
account failures during check-pointing and recovery, as well as correlated
failures. The parallel debugging
solution today, Total View, does not work for users above 1,000 tasks, and only
works on one near HPC system beyond 1,000 nodes.
Debugging of large scale scientific applications with up to 100,000
interdependent parallel tasks requires renewed exploration of alternative
approaches to debugging at massive concurrency. Grant applications are sought
for relative debugging development which provides a promising new debugging
paradigm for large systems and tens of thousands of processes, fixed block disk
development to accelerate performance, improve reliability, and make cost
improvements.
Questions – contact Thomas Ndousse-Fetter (tndousse@science.doe.gov)
References:
1.
Aguilera, M. K., et al., “Failure Detection and Consensus in the
Crash-Recovery Model,” Distributed
Computing, 13(2): 99-125, April 2000. (Summary
available at: http://www.liafa.jussieu.fr/web9/manifsem/description_en.php?idcongres=129)
2.
3.
Williams, E., et al., “The Characterization of Two Scientific
Workloads Using the Cray X-Mp Performance Monitor,” Proceedings of
Supercomputing '90, pp. 142-152, IEEE, 1990.
(See: http://portal.acm.org/citation.cfm?id=110382.110420)
4.
Fagg, G. E., et al., “Scalable Fault Tolerant MPI:
Extending the Recovery Algorithm,” Lecture Notes in Computer Science,
Volume 3666 – Recent Advances in Parallel Virtual Machine and Messaging
Passing Interface Users' Group Meeting Euro PVMMPI 2005, pp 67-75, Springer
Heidelberg, 2005. (ISSN:
0302-9743) (Full text available at:
http://icl.cs.utk.edu/projectsfiles/rib/pubs/sftmpi-europvm-mpi-2005.pdf)
5.
“National Leadership Computing Facility:
A Partnership in Computational Sciences,”
U.S. DOE Oak Ridge National Laboratory Website, at http://www.ccs.ornl.gov/nlcf/
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