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USC Macintosh Cluster Running the AltiVec Fractal Benchmark
Large Macintosh cluster achieves over 1/5 TeraFlop on 152 G4's and
demonstrates excellent scalability.
||56 Power Mac Dual-Processor G4/533's + 20 Power Mac Dual-Processor G4/450's
USC Language Arts Center and other facilities
||December 17, 19, 20, & 27, 2001
The above figure illustrates the potential performance and scalability of Macintosh clusters.
Over Christmas Break 2001, Kay Ferdinandsen, Curtis Safford, and Tom Katsouleas of the
Unversity of Southern California (USC)
invited Viktor Decyk of the
University of California, Los Angeles, (UCLA) and
Dean Dauger of
Dauger Research, Inc., & UCLA to perform
these and other benchmarks on the Macs residing in computer labs at USC.
Except for Decyk's physics codes, this was the first time the
software was run on that many
nodes or processors.
Note that, at 48 nodes and below, we were able to use a homogenous cluster of DP G4/533's;
however, beyond 56 nodes, we combined DP G4/450's with the 533's. As a result,
that hetereogeneous cluster cannot be expected to perform as evenly as
a homogeneous one of the same size. Nevertheless, we were
able to acheive over 1/5 TeraFlop
(1 TF = 1000 GF = one trillion floating-point calculations per second).
The different colored lines indicate the fractal benchmark code operating on different
problem sizes. As expected on any parallel computer running a particular problem type,
larger problems scale better.
The AltiVec Fractal Carbon demo
uses fractal computations that are iterative in nature.
For a portion of the fractal image, these iterations
may continue ad infinitum; therefore, a maximum iteration count is imposed.
In the AltiVec Fractal Carbon demo, this limit is specified using the Maximum Count setting,
whose the default value is 4096 iterations.
By increasing the Maximum Count setting to 16384, then 65536, and so on,
we increased the problem size.
The performance is determined by the total number of floating-point calculations
performed that contribute to the answer and the time it takes to construct the answer.
This time includes not
only the time it takes to complete the computation, but also the time it takes to
communicate the results to the screen on node 0 for the user to see. Also note that
we quote the actual achieved performance, a practical measure of
true performance while solving a problem, rather than the theoretical peak performance.
The time it takes to compute most of these fractals is roughly proportional
to the Maximum Count setting, yet, since the number of pixels is the same, the
communications time remains constant. When running
on over 50 nodes at the 4096 setting, the total time was less than a half second, so it was
clear that communications time became similar to the computation time. By increasing
the problem size significantly, the computation time was once again much greater than
the communications time.
The grey "Ideal" line is an extrapolation multiplying the node count by
the performance of one node alone. As shown in the graph, the cluster's performance
while solving the larger problems
closely approach that "Ideal" extrapolation.
That observation tells us we can find no evidence of an intrinsic limit to the size of a Mac cluster.
After running a series of numerically-intensive trials on a 76-node Macintosh
cluster, we were able to achieve over 1/5 TeraFlop on certain problems. These
results were very repeatable.
No evidence of an intrinsic limit to the size of a Macintosh cluster could be found,
indicating that Macintosh clusters are capable of excellent scalability in performance.
This just in: Compare with
a new result using 33 XServes at NASA's JPL.
The above could not be accomplished without the help of others.
Many thanks to:
the University of Southern California,
Tim Parker, Steve Cook, and Frank Callaham from
Apple Computer, Inc.
- Kay Ferdinandsen - ISD Program Director and Facilitator at the Center for High Performance Computing and Communications,
- Curtis Safford - ISD Macintosh System Adminstrator, and
- Thomas Katsouleas - Professor of Electrical Engineering