Feeds

Petaflops beater: Nvidia chief talks exascale

Programming for parallel processes

Beginner's guide to SSL certificates

"Power is now the limiter of every computing platform, from cellphones to PCs and even data centres," said NVIDIA chief executive Jen-Hsun Huang, speaking at the company's GPU Technology Conference in Beijing last week. There was much talk there about the path to exascale, a form of supercomputing that can execute 1018 flop/s (Floating Point Operations per Second).

Currently, the world's fastest supercomputer, Japan's K computer, achieves 10 petaflops (one petaflop = a thousand trillion floating point operations per second), just 1 per cent of exascale. The K computer consumes 12.66MW (megawatts), and Huang suggests that a realistic limit for a supercomputer is 20MW, which is why achieving exascale is a matter of power efficiency as well as size. At the other end of the scale, power efficiency determines whether your smartphone or tablet will last the day without a recharge, making this a key issue for everyone.

Huang's thesis is that the CPU, which is optimised for single-threaded execution, will not deliver the required efficiency. "With four cores, in order to execute an operation, a floating point add or a floating point multiply, 50 times more energy is dedicated to the scheduling of that operation than the operation itself," he says.

Jen-Hsun Huang, photo Tim Anderson

Power limits: NVIDIA chief executive Jen-Hsun Huang

"We believe the right approach is to use much more energy-efficient processors. Using much simpler processors and many of them, we can optimise for throughput. The unfortunate part is that this processor would no longer be good for single-threaded applications. By adding the two processors, the sequential code can run on the CPU, the parallel code can run on the GPU, and as a result you can get the benefit of the both. We call it heterogeneous computing."

He would say that. NVIDIA makes GPUs after all. But the message is being heard in the supercomputing world, where 39 of the top 500 use GPUs, up from 17 a year ago, and including the number 2 supercomputer: Tianhe-1A in China. Thirty-five of those 39 GPUs are from NVIDIA.

At a mere 2.57 petaflops though, Tianhe-1A is well behind the K computer, which does not use GPUs. Does that undermine Huang's thesis? "If you were to design the K computer with heterogeneous architecture, it would be even more," he insists. "At the time the K computer was conceived, almost 10 years ago, heterogeneous was not very popular."

Using GPUs for purposes other than driving a display is only practical because of changes made to the architecture to support general-purpose programming. NVIDIA's system is called CUDA and is programmed using CUDA C/C++. The latest CUDA compiler is based on LLVM, which makes it easier to add support for other languages. In addition, the company has just announced that it will release the compiler source code to researchers and tool vendors. "It's open source enough that anybody who would like to develop their target compiler can do it," says Huang.

Another strand to programming the GPU is OpenACC, a set of directives you can add to C code that tell the compiler to transform it to parallelised code that runs on the GPU when available. "We've made it almost trivial for people with legacy applications that have large parallel loops to use directives to get a huge speedup," claims Huang.

OpenACC is not yet implemented, though it is based on an existing product from the Portland Group called PGI Accelerator. Cray and CAPS also plan to have OpenACC support in their compilers. These will require NVIDIA GPUs to get the full benefit, though it is a standard that others could implement. There is a programming standard called OpenCL that is already supported by multiple GPU vendors, but it is lower level and therefore less productive than CUDA or OpenACC.

Security for virtualized datacentres

Next page: Blurred lines

More from The Register

next story
It's Big, it's Blue... it's simply FABLESS! IBM's chip-free future
Or why the reversal of globalisation ain't gonna 'appen
'Hmm, why CAN'T I run a water pipe through that rack of media servers?'
Leaving Las Vegas for Armenia kludging and Dubai dune bashing
Bitcasa bins $10-a-month Infinite storage offer
Firm cites 'low demand' plus 'abusers'
Facebook slurps 'paste sites' for STOLEN passwords, sprinkles on hash and salt
Zuck's ad empire DOESN'T see details in plain text. Phew!
CAGE MATCH: Microsoft, Dell open co-located bit barns in Oz
Whole new species of XaaS spawning in the antipodes
Microsoft and Dell’s cloud in a box: Instant Azure for the data centre
A less painful way to run Microsoft’s private cloud
prev story

Whitepapers

Choosing cloud Backup services
Demystify how you can address your data protection needs in your small- to medium-sized business and select the best online backup service to meet your needs.
Forging a new future with identity relationship management
Learn about ForgeRock's next generation IRM platform and how it is designed to empower CEOS's and enterprises to engage with consumers.
Security for virtualized datacentres
Legacy security solutions are inefficient due to the architectural differences between physical and virtual environments.
Reg Reader Research: SaaS based Email and Office Productivity Tools
Read this Reg reader report which provides advice and guidance for SMBs towards the use of SaaS based email and Office productivity tools.
Storage capacity and performance optimization at Mizuno USA
Mizuno USA turn to Tegile storage technology to solve both their SAN and backup issues.