Faster Programs, Easier Programming

Faster Programs, Easier Programming

Published By: MIT News, 11/7/2016

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Researchers from MIT’s CSAIL and Stony Brook University are researching ways to make using multi-core computers easier. They have created a method for describing, in general terms, the computation task desired, and then automatically converting this to a parallelized program. This makes it easier for domain experts (such as computational biologists or cybersecurity experts) to quickly write programs to support their research or tasks, without having to be parallel-programming experts as well.

Extended Discussion Questions

  • The article mentions that dynamic computing prevents the need to recompute the same value repeatedly. What are the advantages of using this strategy to solve complex problems? What are the disadvantages of using this strategy?
  • As computers march toward what seems to be an end to Moore’s law, how could taking advantage of multiple separate processors concurrently impact the future of computing?
  • What kinds of scientific endeavors does the described method support? What kinds of scientific endeavors might it not be so useful for?

Relating This Story to the CSP Curriculum Framework

Global Impact Learning Objectives:

  • LO 7.2.1 Explain how computing has impacted innovations in other fields.

Global Impact Essential Knowledge:

  • EK 7.2.1B Scientific computing has enabled innovation in science and business.

Other CSP Big Ideas:

  • Idea 2 Abstraction
  • Idea 4 Algorithms
  • Idea 5 Programming

Banner Image: “Network Visualization – Violet – Offset Crop”, derivative work by ICSI. New license: CC BY-SA 4.0. Based on “Social Network Analysis Visualization” by Martin Grandjean. Original license: CC BY-SA 3.0

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