The Multicore Challenge, Part 2

September 22nd, 2008 by Peter Lee Post a comment »

The problem of parallel computing is occupying the minds of a growing number of researchers. Why is this age-old concept so “hot” today? In this article — the second in a series of opinion pieces –Andrew Chien, Vice President and Corporate Technology Group Director for Intel Research, gives us his perspective on the issue, with a particular focus on the challenges facing us in education and funding.

Multicore (parallelism) represents a fundamental challenge and change for all of computing and computer science. It represents the fundamental constraints of physics — nature loves parallelism — surfacing and interacting with some fundamental tenets of computing. We have formulated our theory of computation and complexity primarily on sequence — in control and state. Fundamental physics (and consequently circuits and architecture) which makes parallelism fundamentally cheaper is now challenging us to broaden the foundation of computing with parallelism as a first class element. I believe that as a research community, this is a first-order challenge to respond — in nearly all disciplines of computer science. First and foremost, this is a major intellectual challenge to the computer science community to “reinvent” or at least broaden computer science in this way. Second, this is a major educational challenge, where students we are training today to think about “Computer Science founded on sequence” are being launched into a world of parallelism. For their benefit, we must mount a rapid response in pedagogy and curriculum to ensure these students emerge armed to deal with the future of computing in their careers.

Now, let me turn to research funding in parallelism — which is a critical need in all areas from architecture, runtimes, compilers, programming languages, algorithms, and theory. We need major increases in funding and research activity in all of these areas. Governments must take the primary role in funding research in information technology for the long term economic development and societal well-being. We would like to see aggressive large-scale funding of long-range research in parallelism, and that the fruits of that research be made broadly available for commercialization. In the U.S., DARPA has a long track record of funding such research in IT, but such investment has decreased in recent years. We would like to see it increase both in DARPA, as well as other parts of the US government, and yes around the world. History has proven that only governments are able to invest in this type long-term general economic development, and it is critical that the research outputs be generally available for society at large to benefit — not just a small population of gatekeepers. It is great to see this vision being pursued in many regions around the world.

At Intel, we depend heavily on a broad range of science and engineering research pursued by the global academic community. Many of the innovations we commercialize were first conceived in universities — often many years before their practicality — and we have contributed additional innovations and refinements to bring them to the broadest swath of society possible. We strongly support (and contribute our time, money, and leadership to) the health of the research and innovation community globally. We have made significant investments in education (multicore curriculum and training) and research (research grants, Universal Parallel Computing Research Center with Microsoft) for parallelism, and continue to encourage others to join us in doing so.

Andrew Chien

To see the first article in this series, click here.