academia is
debating when and
how to add parallel
programming to the
curriculum, instead
of only offering an
upper-level course
as is now common.

imum set of code changes required to exploit that parallelism. “Put another way,” Stewart says, “how much does Amdahl’s Law screw me up?”

 

a firm ceiling

For years, the promise of parallel computing has run afoul of the harsh reality of an axiom posited by computer architect Gene Amdahl in 1967. Amdahl’s Law puts a firm ceiling on the benefit of converting code from sequential to parallel. It states that the speedup of an application using multiple processors in parallel computing is limited by the time needed for the sequential fraction of the program. The upshot: going down the path of parallelism will not necessarily reap rewards.

“If 50% of your program is serial and the other half can be parallelized, the biggest speedup you’re going to see is a factor of two,” says Microsoft’s Larus. “It doesn’t matter how many cores you have. And that doesn’t seem very compelling if you’re going to have to rewrite a huge amount of software.” Amdahl’s Law, Larus says, might very well mean that a wholesale rush to convert serial applications to parallel platforms in order to preserve a Moore’s Law pace of progress would be misguided. In many cases, it will be more cost-effective to improve serial applications’ performance via algorithmic advances and custom circuitry rather than going for the marginal return on investment that parallelizing those applications might provide.

For Larus, reconciling the true computational needs of future applications with the overall move to parallel-capa-

ble multicore processors must entail rigorous evaluation of what type of application might deliver the most benefit to users. Because the bulk of general-purpose computing has been done successfully on serial platforms, he says it’s been difficult to pin down exactly which applications might derive the most benefit from parallelization.

“This is a challenging problem,” he says. “A lot of people take the attitude, ‘If we build it they will come,’ and that may very well happen—there might be a killer app. But not knowing what that is makes it really hard to build the infrastructure and the tools to facilitate the app.”

So far, Larus says, the computer engineering community is basing its idea of what future general-purpose multicore platforms are capable of due to niche applications such as high-performance scientific data analysis software, where parallelization has shown its value. But there’s no guarantee it will be possible to extrapolate from this experience to create the development frameworks most programmers will need as parallelism goes mainstream in general-purpose computing.

“In this case we’re going backwards; we’re building the tools based on our experience with high-performance computing or scientific computing and saying people are going to need this. And that may be true, but it has a funny feel to me—to have the tools leading.”

Larus says the key to successful parallel platforms might be in finding a way to combine existing discrete serial platforms. One example, he says, might be a virtual receptionist that needs to process visual cues from a camera taking images of a visitor while also responding to spoken queries such as the visitor’s request for directions to a nearby restaurant. “This type of thing has been gradually building up in discrete fields over the years,” Larus says. “When you put it together there are all these big, independent pieces that only interact at these well-defined boundaries. That’s a problem that’s actually easy to parallelize.”

 

Gregory Goth is an oakville, CT-based writer who specializes in science and technology. David A. Patterson, University of California, Berkeley, contributed to the development of this article.

© 2009 ACM 0001-0782/09/0900 $10.00

Milestones
Computer
Science
Awards

president Barack obama and the national science Foundation (nsF) recently honored members of the computer science community for their innovative research. among them:

NSf caReeR a WaRD tiffany Barnes, an assistant professor in the department of computer science at the University of north Carolina at Charlotte, has received a Career award from the nsF for her research on artificial intelligence and education. the goal of Barnes’ project is to create technology for a new generation of data-driven intelligent tutors, enabling the rapid creation of individualized instruction to support learning in science, technology, engineering, and mathematics fields.

PReSiDeNTiaL eaRLY caReeR a WaRDS

president obama has named 100 beginning researchers as recipients of the presidential Early Career awards for scientists and Engineers (pECasE), the highest honor bestowed by the

U.s. government on young professionals in the early stages of their independent research careers.

of the 100 pECasE winners, 15 are computer scientists. they are: Cecilia r. aragon, Lawrence Berkeley national Laboratory; david p. arnold, University of Florida; seth r. Bank, University of texas, austin; Joel L. dawson, Massachusetts institute of technology; Chris L. dwyer, duke University; anthony grbic, University of Michigan; Carlos E. guestrin, Carnegie Mellon University; sean Hallgren, penn state University; yu Huang, University of California, Los angeles; gregory H. Huff, texas a&M University; sanjay Kumar, University of California, Berkeley; rada F. Mihalcea, University of north texas; adam d. smith, penn state University; adrienne d. stiff-roberts, duke University; and sharon M. weiss, Vanderbilt University.