Nvidia and AMD have announced high-performance graphics chips for supercomputers. While not suitable for use in the kind of workstations Digital Arts readers use, they provide an interesting insight into the level of power that's possible using GPUs, even when they're not being used for graphics.
Nvidia announced GPUs (graphics processing units) called K20 and K20X, with the latter being used in Titan, a 20-petaflop supercomputer at the U.S. Department of Energy's Oak Ridge National Laboratory. AMD announced the FirePro SM10000 graphics processor, which is targeted at high-performance computers and servers in virtualized environments.
Co-processors like GPUs are considered more powerful that CPUs for specific tasks such as scientific and math applications. The GPUs are important in providing more computing power for simulation and experimentation in research areas such as biosciences, climate, energy and space. IBM and Intel also offer accelerators for supercomputers.
Some of the world's fastest supercomputers today harness the processing power of CPUs and graphics chips for complex calculations. The Titan supercomputer pairs 18,688 Nvidia Tesla K20X GPUs with 18,688 AMD 16-core Opteron 6274 CPUs, with the GPUs handling 80 to 90 percent of the processing load. Other supercomputers that pair CPUs and GPUs include the Tianhe-1A at the National Supercomputer Center in Tianjin, China.
Nvidia has a big lead over AMD in GPUs for supercomputing, said Dan Olds, principal analyst at Gabriel Consulting Group.
Nvidia pushed parallel programming tools many years ago so coders could write applications for GPUs, Olds said. AMD has virtually no presence in the supercomputing market and needs to foster a programming environment for parallel frameworks like OpenCL to be a worthy alternative to Nvidia, Intel and other companies, Olds said.
Nvidia's K20 has 5GB of memory and delivers 1.17 teraflops of double-precision performance and 3.52 teraflops of single-precision performance. Double-precision performance is more important for supercomputing applications as it carries higher precision for floating-point calculations than single-precision calculations. The faster K20X has 6GB of memory and delivers 1.31 teraflops of double-precision performance. The K20X is three times faster than its predecessor, the Tesla M2090, which was released in the middle of last year.
The K20 products will be available in computers from companies such as Hewlett-Packard, IBM, Asus, Fujitsu, Tyan, Quanta Computer and Cray. Nvidia declined to provide pricing, saying the GPUs would be sold through server vendors.
The new chips have thousands of small processing cores that will be able to more effectively execute application code simultaneously. The Hyper-Q feature will speed up execution of legacy code through smarter scheduling of code execution.
AMD claimed that its FirePro SM10000 delivered 1.48 teraflops of peak double-precision performance. The graphics card has 6GB of memory.
The SM10000 is designed for multiple server deployments, AMD said in a slide presentation. GPUs in servers are capable of deploying virtual desktops to client devices like PCs and tablets. The GPU can accelerate graphics on the server side for full high-definition virtual desktops on client devices.
The faster processing speed of SM10000 could also help deploy virtual machines at a faster rate in computing environments, AMD said. A single graphics card will be able to deploy many virtual machines, and AMD has worked with Citrix, VMware and Microsoft to boost virtualization performance on the GPU.
AMD is also targeting the FirePro SM10000 at workstations. The company did not immediately comment on questions related to single-precision performance and pricing for the graphics card.