Nvidia's efforts to push graphics chip technology into mainstream computing received
a significant boost May 18 when IBM
announced that the newest version of its iDataPlex server will run on both
traditional computing chips and GPUs from Nvidia.
The announcement marks the first time a top-tier systems vendor
has made the move to offer a hybrid CPU-GPU server in the HPC
(high-performance computing) space.
Nvidia officials said having IBM
adopt Tesla 20-series GPUs in its iDataPlex dx360 M3 system is a validation of
both Nvidia and of the vision the company is promoting.
"Having IBM [put GPUs
into the server] means that anyone considering a high-performance computing
system will now have options," Sumit Gupta, senior product manager for
Nvidia's Tesla business, said in an interview, noting that IBM
and Hewlett-Packard dominate the Top500 list of the world's most powerful
supercomputers. "This really makes GPUs a mainstream [technology]."
Nvidia has led the effort to bring GPUs into mainstream,
general-purpose computing. Company officials unveiled
the Tesla 20-series in November 2009 at the Supercomputing show in
Portland, Ore. Based on Nvidia's new "Fermi" architecture, the Tesla
20-series graphics chips are meant to be used for general-purpose computing,
offering the performance of traditional CPU-based clusters, but at a 10th
of the cost and a 20th of the power.
Nvidia officials began promoting the shift in 2006, when the
company rolled out the CUDA architecture. Several smaller HPC
server makers, including SGI,
Appro and Super Micro Computer, are already using Nvidia GPUs in some of
their systems. IBM will be the largest OEM to do so.
In a video
presentation, Scott Denham, a member of IBM's
Deep Computing technical team, said the IT industry needs to find a way to meet
business demands for more performance from their systems, but at less cost.
"Many of our customers are constrained by the amount of
power and cooling they can get into their existing facilities," Denham
said. "They have a demand for a much higher level of computation to
implement advanced algorithms."
The only real options for doing that are to build larger
buildings, bring in larger power supplies or find another way of doing things.
"GPU technology is an ideal way to get this much higher
level of computational ability in this same power footprint as the existing
systems while increasing throughput four to 10 times," Denham said.
The iDataPlex dx360 M3 server is powered by two Intel CPUs, and
two GPU cards are attached. The architectures can "add a tremendous amount
of compute power to the existing infrastructure," he said.
Nvidia officials are saying in order to keep computing capabilities
improving at the same pace they have for the past few decades, there has to be
shift away from serial CPUs and toward parallel processing found in GPUs.
Intel and AMD are looking to
keep making significant gains in performance through small chip sizes and more
processing cores. However, in a column
on Forbes.com in April, Bill Dally, vice president and chief technologist
at Nvidia, said the power needs of compute chips from Intel and Advanced Micro
Devices are making it difficult
to sustain Moore's Law.
"It is past time for the computing industry—and everyone
who relies on it for continued improvements in productivity, economic growth
and social progress—to take the leap into parallel processing," Dally
wrote.
IBM's Denham agreed.
"The future of computing in high-performance computing
space [is] moving toward this hybrid model where we have a combination of
standard [CPU] cores and very high-performance [GPU] cores, hundreds per
chip," he said, adding that parallel computing is the answer.
"Parallelism inside the chip is the most effective way to do that."
AMD, on the strength of its ATI
unit, is looking to closely integrate CPU and GPU technologies on a single
chip, part of its Fusion initiative. Intel also is enhancing the graphics
capabilities of its CPUs.
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