Question

In: Computer Science

Briefly describe why parallelizing sequential algorithms is challenging and thus why the full processing power of...

Briefly describe why parallelizing sequential algorithms is challenging and thus why the full processing power of the fastest supercomputers is underutilized.

Solutions

Expert Solution

Reasons:

  1. Many problems require the results from a preceding step to effectively carry on with the next step – these are called inherently serial problems and the algorithms to solve such problems just can't be converted to parallel algorithms. For example, Newton's method for finding roots is one such problem as each subsequent step depends on the result of the previous step.
  2. Parallel slowdown: This is a phenomenon that may occur when the overhead of communication required between different processors executing parallel processes of an algorithm overweighs the initially expected gains from parallelizing an algorithm. In such cases, the parallel version of the algorithm turns out to be more costly & slower than the sequential version.

Due to these reasons, a vast majority of the algorithms and processes being used today in all computer systems are still sequential or largely sequential (with small portions them being parallelized). Also as most of the modern supercomputers employ thousands of (multicore) processors working in parallel their full processing power remains underutilized.


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