On Wed, 10 May 2006 20:51:43 -0400, Eric Lynum wrote:
> I'd like to know have there been any new computational architectures that
> people are looking at today other than multiprocessing? As a hardware
That depends on what you mean by new architectures. Most of the
custom machines (FPGA or ASIC) are essentially new processing
architectures. Examples include the FPGA-based hardware units
from Adaptive Genomics and TimeLogic. Paracel's processing
hardware is an ASIC solution. All of these designs were
(probably) done by engineers working from the specification of an
algorithm. In the case of Adaptive Genomics, our goal was to
design a hardware solution that provides both flexibility and
high throughput for the Smith-Waterman algorithm. The result is
not based on any other particular processing architecture, although
it does make use of well-known matrix solution techniques. Of
FPGA-based solutions, Cray's XD1 solution is probably the closest to
a traditional computational architecture, since it was developed much
like a standard co-processor (their approach is described pretty well
in Steve Margerm's article "Reconfigurable Computing in Real-World
Applications," FPGA and Structured ASIC Journal, Feb 2006).
There are people developing Smith-Waterman (and other bioinformatic)
solutions for many other non-microprocessor architectures as well.
For examplt, Cray's traditional vector-based machines (not really "new")
have a bioinformatics library.
> engineer interested in the field of Bioinformatics since I'm not in the
> field, it seems from reading the posts that Cray machines and Opteron
> processors are used? Why is this, are there no other computational
Processors of of all sorts are used. Cray probably benchmarked
the SSEARCH34 algorithm on an Opteron since that processor is a
primary component of the XD1. Of course, these days comparisons
are generally made against standard microprocessors for most
things, since it provides perspective to a broad audience.
> architectures that are appropriate? Also, what algorithms require these
> processors and why?
Many of the algorithms used in bioinformatics are inherently
parallel (perhaps even embarassingly so, as Kevin mentioned earlier).
While they don't _require_ a parallel architecture, they tend to perform
well on systems that exploit parallelism. For more information on how
processing architectures and algorithms work together (i.e. "what
algorithms and why") you might like H.S. Stone's "High-Performance
Computer Architecture" (Addison-Wesley) or D. Cutler, J.P. Singh and A.
Gupta's "Parallel Computer Architecture : A Hardware/Software Approach"
. Dr. Scott Harper
. Adaptive Genomics Corp.
. 620 N. Main St, Suite 103
. Blacksburg, VA 24060
. Scott.Harper at AdaptiveGenomics.com, 540-552-2700