Intel exec: Programming for multicore chips a challenge
Adding more cores is desirable to meet growing computing demands, but it could
create more challenges for programmers writing code that enables applications
to work effectively with multicore chips.
As technology develops at a fast rate, a challenge for developers is to adapt
to programming for multicore systems, said Doug Davis, vice president of the
digital enterprise group at Intel, during a speech Tuesday at the Multicore
Expo in Santa Clara, California. Programmers will have to transition from programming
for single-core processors to multiple cores, while future-proofing the code
to keep up-to-date in case additional cores are added to a computing system.
Programming models can be designed that take advantage of hyperthreading, which
enables parallel processing capabilities of multiple cores to boost application
performance in a cost-effective way, Davis said. Intel is working with universities
and funding programs that will train programmers to develop applications that
solve those problems, Davis said.
Intel, along with Microsoft, has donated $20 million to the University of California
at Berkeley and the University of Illinois at Champaign-Urbana, to train students
and conduct research on multicore programming and parallel computing. The centers
will tackle the challenges of programming for multicore processors to carry
out more than one set of program instructions at a time, a scenario known as
parallel computing.
Beyond future-proofing code for parallelism, adapting legacy applications to
work in new computing environments that take advantage of multicore processing
is a challenge coders face, Davis said. Writing code from scratch is the ideal
option, but it can be expensive.
"The world we live in today has millions of lines of legacy code ... how
do we take legacy of software and take advantage of legacy technology?"
Coders could need to deliver what's best for their system, Davis said.
Every major processor architecture has undergone quick changes because of the
rapid rate of change as described by Moore's Law, which calls for better application
and processor performance every two years, but now the challenge is to deliver
performance within a defined power envelope. Power consumption is driving multicore
chip development, and programmers need to write code that works within that
power envelope, Davis said.
Adding cores to a chip to boost performance is a better power-saving option
than cranking up clock frequency of a single-core processor, Davis said. Adding
cores increases performance, but cuts down on power consumption.
In 2007, about 40 percent of desktops, laptops and servers shipped with multicore
processors. By 2011, about 90 percent of PCs shipping will be multicore systems.
Almost all of Microsoft Windows Vista PCs shipping today are multicore, Davis
said.
Intel is also working on an 80-core Polaris chip, which brings teraflops of
performance.
"We're not only talking about terabit computing, but the terabyte sets
[of data] we can manage." Davis said. Users are consuming and storing tremendous
amounts of data now, and in a few years, the amount of data should reach zettabytes,
Davis said.
The next "killer" application for multicore computing could be tools
that enable the real-time collection, mining and analysis of data, Davis said.
For example, military personnel using wearable multicore computers are able
to simulate, analyze and synthesize data in real time to show how a situation
will unfold. Doing so is viable and doesn't create risk for military personnel,
Davis said.
"These types of applications have taken weeks to do ... now these types
of applications are literally running in minutes," Davis said.
As cores are added, the performance boost may also enable more applications,
Davis said. The oil and gas industry will demand one petaflop of computing capacity
in 2010, compared to 400 teraflops in 2008, to cost-effectively collect seismic
data, compare it to historical data and analyze the data. Compared to the past,
oil and gas explorers can collect and analyze data much faster now, Davis said.
IDG News Service
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