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Click on this link to Intel Supercomputer Tracks Oil Spill.
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<strong>Oil Spill Chemistry:</strong> Parallelization
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Computer simulations take a LOT of computing power and making them
accurate and efficient enough to make scientific conclusions about
their results poses real problems. Computer scientists must address
these issues if simulations are to be useful models in chemistry,
atmospheric science, oceanography, or other fields.
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How do we get computers to run faster and more efficient?
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The Problem
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<img src="heatsink.jpg">
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Computers run on electricity, and electricity can only travel at a
finite speed. Though electrons themselves don't travel that fast,
electrical current in a conductor travels close to the speed of
light, 300,000,000 m/s. As fast as that is, it is still a limit.
Computers have gotten faster because fabrication technology has
enabled transistors (the element on the computer chip that performs
a single operation) to get closer together. With transistors packed
together, electrons can perform more operations faster because they
do not have to travel as far. Unfortunately, the movement of
electrons creates heat. Transistors packed too close generate so
much heat that the computer chip actually melts. Over a small area,
some computer chips are capable of reaching temperatures close to
10,000°F, which is equal to the surface of the sun! Innovative
methods to cool computer chips have become necessary for faster
processing speeds.
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<font size="2" face="Verdana, Arial, Helvetica, sans-serif">http://image3.examiner.com/images/blog<br>/wysiwyg/image/heatsink.jpg</font>
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<font face="Arial, Helvetica, sans-serif" size="4"><strong>What is the
main problem in creating faster computers, and why has it become a problem?</strong></font>
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A Solution
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What if you could get a computer to do two or more small tasks at
once? Wouldn't that give it the illusion of performing faster?
Parallel computing is a form of computation in which many
calculations are carried out simultaneously, operating on the
principle that large problems can often be divided into smaller
ones, which are then solved concurrently ("in parallel.") Multi-core
processors allow this to happen, but software must be designed to
divide a large task into smaller ones that can be performed
simultaneously. Multi-core processors require additional power and
produce more heat, but at least the heat is generated over a larger
area. As the physical limitation for the speed of each processor is
being approached, parallel computing has become the dominant
paradigm in computer architecture to continue the advance of the
processing time of computers.
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<img src="quadcore.jpg">
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<font face="Arial, Helvetica, sans-serif" size="4"><strong>How many cores
or processors are in the computer you are currently using? Who do you know
that has a duo-core or quad-core computer?</strong></font>
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Unfortunately, the problem isn't completely solved by parallelism.
Breaking up computation into pieces that fit well into memory can be
done, but often those pieces must communicate with each other or be
re-assembled. Communication between pieces takes processing time
which actually slows down computer speed. Efficient communication
between pieces (called threads) has become ever more critical since
all desktop machines currently manufactured now have multiple
processors.
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Supercomputers and the Gulf Oil Spill
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http://scoop.intel.com/intel_supercomputer_tracks_bp_oil_spill/20
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<font face="Arial, Helvetica, sans-serif" size="4"><strong>How does the
Rio Rancho supercomputer solve the heat problem? (What is used to cool the
supercomputer?)</strong></font>
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<font face="Arial, Helvetica, sans-serif" size="4"><strong>How many
processors does the Rio Rancho Supercomputer have? (Only 1,000 were used
for the simulation.) You will have to do the math: # of quad-core
processors x 4 = ?)</strong></font>
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