Connection
Machine, by Thinking Machines.
These are long, long gone. The CM-2 had 64K processors, connected in
a mesh network. 2 GB memory, 10 GB disk typically. It was massive
for the time (1990). CM-5 has some of the best LED displays.
Cray,
vector supercomputing. Their systems often followed the SPMD model.
Cray was bought by SGI and later sold to Tera, which renamed itself
Cray.
Intel
Paragon. Paragon was
another mesh-interconnected system. The processors were partitioned
among jobs. Intel has since gotten out of the supercomputer business,
but its processors are used in many of the world's fastest computers
today.
ASCI-class supercomputers: Teraflop Computing
Mid-late 1990's - the Accelerated Strategic Computing Initiative
(ASCI) program from the Department of Energy program made the push for
a teraflop system.
Intel Cluster. ASCI Red, Sandia National Labs
(SNL). World's
first teraflop system. Linux cluster, but different from most. Its
OS is based on linux, but was customized significantly. They stripped
out anything that was not needed to make sure as much physical memory
as possible was available for user jobs.
PC Cluster. Try this at home. Many fall into the category of
Beowulf Clusters. Our cluster
would be considered one of these.
IBM SP.
Basically a cluster with high-end RS6000/PowerPC processors and a
high-speed switch interconnect. The switch was the key to its
performance and the cause of its very high pricetag. Many of the
world's top supercomputers in the early 2000's were IBM SP systems.
SGI Origin
3000, and its
predecessor, the SGI Origin 2000. The ccNUMA and NUMA-Flex systems
provide non-uniform shared memory access. These systems were
popular among those who preferred threads to MPI.
IBM was selected to build ASCI White, at
LLNL, the second
generation ASCI platform. A smaller version is Blue Horizon at
San Diego Supercomputing Center
(SDSC), available to a wider
group. Larger clusters built using larger SMPs. Single-node
processor utilization is important, but may be difficult to achieve.
Number one on the Top 500 Supercomputers for a while was
Terascale
at Pittsburgh Supercomputing Center. It was nicknamed "LeMieux" for
obvious reasons. This system was built from Alpha processors.
Issues for Cluster-based Systems
Assignment of nodes to jobs - we want to keep as many nodes as
possible busy computing, but we don't want to let small jobs (few
processors) starve larger jobs (many processors).
Some jobs may require special resources available only on some
nodes - for example in the bullpen cluster, some nodes have 4
processors while others have two, some nodes have more memory than
others, and some nodes have a gigabit interconnect and others don't.
A scheduler might require jobs submissions to include a maximum
running time to be able to schedule more intelligently.
Scheduling is likely non-preemptive, but we can consider a
"shortest job first" approach.
Another issue: are compute nodes granted exclusively to one job,
or are they shared?
IBM Blue
Gene
systems are the leaders: high-density clusters, essentially
Lots of cores!
Issues:
how to make use of nodes with many cores
how to lower power consumption and heat generation
how to program a machine with 100,000+ processors
Something Different: TeraGrid:
An Internet "cluster of clusters".
Many new issues arise here - it is no longer a resource stored in one
building in one place with one adminstrative entity. We need to worry
about scheduling on a larger scale. User authentication. Use of
computers at multiple sites simultaneously will involve slow wide-area
network links. How to get the data to the computers, where to store
results?
