Parallel Processing

# Parallel Processing - The Need For High Performance...

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The Need For High Performance Computers Many of todays applications such as weather prediction, aerodynamics and artificial intelligence are very computationally intensive and require vast amounts of processing power. To calculate a 24 hour weather forcast for the UK requires about 10^ 12 operations to be performed. This would take about 2.7 hours on a Cray-1 ( capable of 10^ 8 operations per second ). So to give accurate long range forecasts ( e.g. a week ) much more powerful computers are needed. One way of doing this is to use faster electronic components. The limiting factor is however the speed of light. The speed of light is 3 * 10^ 8 m/s. Considering two electronic devices (each capable of performing 10^ 12 operations per second ) 0.5mm apart. It takes longer for a signal to travel between them than it takes for either of them to process it ( 10^ -12 seconds ). So producing faster components is ultimately of no good. So it appears that the only way forward is to use PARALLELISM. The idea here is that if several operations can be performed simultaneously then the total computation time is reduced. The parallel version has the potential of being 3 times as fast as the sequential machine.

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Classification of Parallel Machines Models of Computation ( Flynn 1966 ) Any computer, whether sequential or parallel, operates by executing instructions on data. a stream of instructions (the algorithm) tells the computer what to do. a stream of data (the input) is affected by these instructions. Depending on whether there is one or several of these streams, we have four classes of computers. There is also a discussion of an additional 'pseudo-machine' SPMD. 1. Single Instruction Stream, Single Data Stream : SISD. 2. Multiple Instruction Stream, Single Data Stream : MISD. 3. Single Instruction Stream, Multiple Data Stream : SIMD. 4. Multiple Instruction Stream, Multiple Data Stream : MIMD. 5. Single Program Multiple Data: SPMD. SISD Computers This is the standard sequential computer. A single processing unit receives a single stream of instructions that operate on a single stream of data. To compute the sum of N numbers a1, a2, . ... aN the processor needs to gain access to memory N consecutive times ( to receive one number ). Also N-1 additions are executed in sequence. Therefore the computation takes O(N) operations. i.e. algorithms for SISD computers do not contain any parallelism, there is only one processor MISD Computers N processors, each with its own control unit, share a common memory.
There are N streams of instructions (algorithms / programs) and one stream of data. Parallelism is achieved by letting the processors do different things at the same time on the same datum. MISD machines are useful in computations where the same input is to be subjected to

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Parallel Processing - The Need For High Performance...

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