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5. Performing tasks on the cluster

This section is still being developed as the usage on my cluster evolves, but so far we tend to write our own sets of message passing routines to communicate between processes on different machines.

Many applications, particularly in the computational genomics areas, are massively and trivially parallelisable, meaning that perfect distribution can be achieved by spreading tasks equally across the machines (for example, when analysing a whole genome using a technique that operates on a single gene/protein, each processor can work on one gene/protein at a time independent of all the other processors).

So far we have not found the need to use a professional queueing system, but obviously that is highly dependent on the type of applications you wish to run.

5.1 Rough benchmarks

For the single most important program we run (our ab initio protein folding simulation program), using the Pentium 3 1 GHz processor machine as a frame of reference, the Athlon 1.2 GHz processor machine is about 16% faster on average, the Xeon 1.7 GHz machine is about 25-32% faster on average, the Athlon 1.5 GHz processor is about 38% faster on average, and the Athlon 1.7 GHz processor is about 46% faster on average (yes, the Athlon 1.5 GHz is faster than the Xeon 1.7 GHz since the Xeon executes only six instructions per clock (IPC) whereas the Athlon executes nine IPC (you do the math!)).

5.2 Uptimes

These machines are incredibly stable both in terms of hardware and software once they have been debugged (usually some in a new batch of machines have hardware problems), running constantly under very heavy loads. One example is given below. Reboots have generally occurred when a circuit breaker is tripped.

  2:29pm  up 495 days,  1:04,  2 users,  load average: 4.85, 7.15, 7.72

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