Chapter: An Introduction to Parallel Programming - Why Parallel Computing?

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Why We Need Ever-Increasing Performance

The vast increases in computational power that we’ve been enjoying for decades now have been at the heart of many of the most dramatic advances in fields as diverse as science, the Internet, and entertainment.

WHY WE NEED EVER-INCREASING PERFORMANCE

The vast increases in computational power that we’ve been enjoying for decades now have been at the heart of many of the most dramatic advances in fields as diverse as science, the Internet, and entertainment. For example, decoding the human genome, ever more accurate medical imaging, astonishingly fast and accurate Web searches, and ever more realistic computer games would all have been impossi-ble without these increases. Indeed, more recent increases in computational power would have been difficult, if not impossible, without earlier increases. But we can never rest on our laurels. As our computational power increases, the number of prob-lems that we can seriously consider solving also increases. The following are a few

.examples:


. Climate modeling. In order to better understand climate change, we need far more accurate computer models, models that include interactions between the atmosphere, the oceans, solid land, and the ice caps at the poles. We also need to be able to make detailed studies of how various interventions might affect the global climate.


Protein folding. It’s believed that misfolded proteins may be involved in dis-eases such as Huntington’s, Parkinson’s, and Alzheimer’s, but our ability to study configurations of complex molecules such as proteins is severely limited by our

current computational power.

 

Drug discovery. There are many ways in which increased computational power can be used in research into new medical treatments. For example, there are many drugs that are effective in treating a relatively small fraction of those suffering from some disease. It’s possible that we can devise alternative treatments by care-ful analysis of the genomes of the individuals for whom the known treatment is ineffective. This, however, will involve extensive computational analysis of

genomes.

 

Energy research. Increased computational power will make it possible to program

 

much more detailed models of technologies such as wind turbines, solar cells, and batteries. These programs may provide the information needed to construct far

more efficient clean energy sources.

 

Data analysis. We generate tremendous amounts of data. By some estimates, the quantity of data stored worldwide doubles every two years [28], but the vast majority of it is largely useless unless it’s analyzed. As an example, knowing the sequence of nucleotides in human DNA is, by itself, of little use. Understand-ing how this sequence affects development and how it can cause disease requires extensive analysis. In addition to genomics, vast quantities of data are generated by particle colliders such as the Large Hadron Collider at CERN, medical imaging, astronomical research, and Web search engines—to name a few.

 

These and a host of other problems won’t be solved without vast increases in computational power.


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