Nvidia, AMD Bulk Up Their GPU Accelerators

 
 
By Jeffrey Burt  |  Posted 2013-11-18 Email Print this article Print
 
 
 
 
 
 
 

Nvidia's K40 GPU and AMD's new FirePro S10000 both will offer 12GB of memory, which is a key feature for HPC and big data workloads.

Nvidia and Advanced Micro Devices are pushing the capabilities of their respective graphics cards as they look to capture larger shares of the growing interest in GPU accelerators in the high-performance computing space.

At the SC '13 supercomputing show in Denver Nov. 18, Nvidia officials unveiled the Tesla K40 GPU accelerator, which the company said will offer twice the memory—at 12GB—and 40 percent the performance of its current K20X accelerators. The chip, aimed at such workloads as big data and scientific calculations, also offers 10 times the performance of systems using only CPUs, according to Nvidia officials.

Nvidia's announcement came four days after AMD rolled out its FirePro S10000 12GB Edition graphics card, which is aimed at high-performance computing (HPC) and big data tasks and marks the vendor's most significant push into the high-end computing field with its GPU technology.

"Our compute application customers asked for a solution that offers increased memory to support larger data sets as they create new products and services," David Cummings, senior director and general manager of professional graphics at AMD, said in a statement. "In response, we're announcing the AMD FirePro S10000 12GB Edition graphics card to meet that additional memory demand with support for OpenCL and high-end compute and graphics technologies."

Both Nvidia and AMD for the past several years have been promoting GPUs as accelerators for use in high-end systems running HPC workloads. The GPUs enable OEMs to build systems that can improve performance and handle more parallel-processing workloads while also driving up the power efficiency, an increasingly critical metric in highly dense data centers.

Interest in the HPC space in GPU accelerators and coprocessors—like Intel's x86-based Xeon Phi many-core chips—continues to gain momentum. According to the organizers of the Top500 list of the world's fastest supercomputers, 53 systems on the list are using either GPU accelerators or coprocessors—38 of which are using Nvidia GPUs, and another two using AMD's. Thirteen are using Xeon Phi coprocessors.

More than 240 applications can leverage GPU acceleration, according to Nvidia.

Sumit Gupta, general manager of Tesla accelerated computing products at Nvidia, said interest in GPU accelerators has been strong over the past few years.

"No one expected that kind of adoption," Gupta told eWEEK, adding that the kinds of use cases for systems with GPU accelerators range greatly, from use on Dutch Navy warships to systems that help develop new shampoos. End users "keep coming up with cool use cases."

Nvidia's new K40 GPU is being embraced by a range of OEMs—such as Dell, IBM, Hewlett-Packard, Cray, SGI and Bull—that will being rolling out systems leveraging the graphics cards.

"NVIDIA's accelerators enable our customers to realize significant improvements in processing performance," Bill Mannel, general manager of compute at SGI, said in a statement.



 
 
 
 
 
 
 
 
 
 
 
 
 

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