ever, a lack of standardization can impede progress inasmuch as the presence of many incompatible approaches allows none to achieve the benefits of wide adoption and reuse—a major reason that industry participates in standards efforts. The committee encourages the development of programming-interface standards that can facilitate wide adoption of parallel programming even as they foster competition in other matters.

Recommendation: Invest in the development of tools and methods to transform legacy applications to parallel systems.

Whatever long-term success is achieved in the effective use of parallel systems from rethinking algorithms and developing new programming methods will probably come at the expense of the backward-platform and cross-platform compatibility that has been an economic cornerstone of IT for decades. To salvage value from the nation’s current, substantial IT investment, we should seek ways to bring sequential programs into the parallel world. On the one hand, there are probably no “silver bullets” that enable automatic transformation. On the other hand, it is prohibitively expensive to rewrite many applications. The committee urges industry and academe to develop “power tools” for experts that can help them to migrate legacy code to tomorrow’s parallel computers. In addition, emphasis should be placed on tools and strategies to enhance code creation, maintenance, verification, and adaptation of parallel programs.

Recommendation: Incorporate in computer science education an increased emphasis on parallelism, and use a variety of methods and approaches to better prepare students for the types of computing resources that they will encounter in their careers.

Who will develop the parallel software of the future? To sustain IT innovation, we will need a workforce that is adept in writing parallel applications that run well on parallel hardware, in creating parallel software systems, and in designing parallel hardware.

Both undergraduate and graduate students in computer science, as well as in other fields that make intensive use of computing, will need to be educated in parallel programming. The engineering, science, and computer-science curriculum at both the undergraduate and graduate levels should begin to incorporate an emphasis on parallel computational thinking, parallel algorithms, and parallel programming. With respect to the computer-science curriculum, because no general-purpose paradigm has emerged, universities should teach diverse parallel-programming languages, abstractions, and approaches until effective ways of teaching



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