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SCL Overview
The Scalable Computing Laboratory
(SCL)
was created in 1989 as a joint effort of the Department of Energy
(DOE)
through
Ames Laboratory
and Iowa State University
(ISU)
through the Center for Physical and Computational Mathematics
(CPCM),
one of several centers administered by
ISU's Institute for Physical Research and Technology
(IPRT).
Primary funding is from the Mathematical, Information, and Computational Sciences
(MICS)
Division of the DOE Office of Advanced Scientific Computing Research
(ASCR).
The SCL was a major participant in the Presidential
Initiative for High Performance Computing and Communication
(HPCC), and is
currently involved in two
SciDAC
projects. The research at the SCL is driven by the application side, so strong
collaborations have been maintained with the Chemistry and Physics
groups which are funded largely by the Basic Energy Sciences
(BES)
division of DOE.
Interaction with computer vendors has always played a major role
in the development of new computing systems, and often results
in leveraging of hardware resources such as with our IBM clusters.
The mission of the SCL is to advance the use of scalable computing in scientific
and engineering computation within the Laboratory and the University.
Much of the research is driven by the needs of key applications in the
Chemistry
and
Condensed Matter Physics
groups that have been active participants in the high-performance computing efforts.
For example, the
GAMESS quantum chemistry code has played a central role
in aquiring the IBM clusters and in a SciDAC project on
Advancing Multi-Reference Methods in Electronic Structure Theory.
The
Array Compression Library
is being developed to allow codes such as these to trade CPU cycles to
reduce communication bandwidth and storage requirements.
Research into performance analysis has focused on several key areas
needed to understand the limiting factors that prevent applications
from efficiently taking advantage of the resources available.
The
HINT
benchmark was developed to analyze the capabilities of
the processor and memory subsystem, providing a graph of the performance
for a range of problem characteristics. The
NetPIPE
utility is a flexible tool for measuring the point-to-point network
performance for different communication protocols.
This is ideal for identifying inefficiencies in the message-passing
layers, and identifying problems in the network hardware and drivers.
NetPIPE is also being expanded to measure the global network properties
to help understand the effect of the network topology on applications.
A
cache-aware matrix benchmark
is being developed to study the use of mixed programming models on SMP systems.
The SCL therefore has a set of performance analysis tools that probe
the individual components of a high-performance computing system,
and also a benchmark that exercises all components at the same time.
Performance is often lost due to inefficiencies in the message-passing layer.
The goal of the
MP_Lite
project is to investigate methods to improve message-passing performance
and to enable efficient message-passing across new hardware.
The Generalized Portable SHMEM
GPSHMEM
project provides greater efficiency and brings the one-sided SHMEM
interface to a wide variety of multi-processor systems.
The NodeMap
utility is being developed to
determine the topology of the underlying network at run-time,
which can then be used to automatically provide the best mapping
of an application to the network.
Research improving the management techniques of mutli-processor systems is not
only making them easier to use by providing a single-system image,
but also allows the resources to be used more efficiently. The SCL is part of the
Scalable System Software SciDAC
project, where we focus our efforts on parallel resource management using the
Maui Scheduler for the PBS batch queueing system. A small cluster has also been
set up to test the MOSIX cluster management system.
We have a very wide variety of
computer resources
from small test-beds for measuring CPU and point-to-point communciation
performance, to large clusters for evaluating network topologies and
the performance of full applications.
The clusters include Pentium, Athlon, IBM Power3II, G4 PPC, and Alpha processors,
running Linux, AIX, and Tru64 Unix, connected by Fast Ethernet, Gigabit
Ethernet, Myrinet, SCI, and InfiniBand.
The hardware research is done in close collaboration with many vendor
partners such as
IBM
,
Myrinet
, and
Mellanox
. Examples of some current research projects include porting 64-bit Linux
to the IBM Power3II architecture, evaluating and improving drivers for various
network interface cards, working with vendors and MPI developers
to bring InfiniBand technology to the cluster community, and analyzing
the performance capabilities of a 2D SCI network.
The experience gained from working with a wide variety of hardware
and operating systems, and the measurements made with the
performance analysis tools being developed, is being used to
help groups within Ames Laboratory to purchase and use parallel
computing systems to their fullest capabilities.
Through the Center for Physical and Computational Mathematics
(CPCM),
this experience is being disseminated throughout the University. Many of
the principal investigators also hold adjunct faculty positions in
various departments, and are teaching courses on high-performance computing.
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Questions? Comments? Please send an email to
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or contact us at 515-294-7336.