«

»

NVIDIA Tesla K40 GPUs Accelerate IBM Data Center Supercomputers


NVIDIA Tesla K40 GPUs Accelerate IBM Data Center Supercomputers

Companies Tap GPU-Enabled Supercomputing to Analyze Enterprise Data on the Fly

NVIDIA and IBM [NYSE: IBM] today announced plans to collaborate on GPU-accelerated versions of IBM’s wide portfolio of enterprise software applications on IBM Power Systems.

The move marks the first time that GPU accelerator technology will move beyond the realm of supercomputing and into the heart of enterprise-scale data centers. The collaboration aims to enable IBM customers to more rapidly process, secure and analyze massive volumes of streaming data.

“Companies are looking for new and more efficient ways to drive business value from Big Data and analytics,” said Tom Rosamilia, senior vice president, IBM Systems & Technology Group and Integrated Supply Chain. “The combination of IBM and NVIDIA processor technologies can provide clients with an advanced and efficient foundation to achieve this goal.”

NVIDIA_Tesla_K40_GPU_Accelerator

Companies to Integrate POWER Processor, Tesla GPUs

NVIDIA and IBM also plan to integrate the joint-processing capabilities of NVIDIA® Tesla® GPUs with IBM POWER processors. The move makes it easier and more efficient for a wider range of companies to employ a style of supercomputing hardware used primarily by the scientific and technical communities for computing tasks like space exploration, decoding the human genome and speeding new products to market.

By combining IBM POWER8 CPUs with the world’s highest-performance and most energy-efficient GPU accelerators, the companies aim to deliver a new class of technology that maximizes performance and efficiency for all types of scientific, engineering, big data analytics and other high performance computing (HPC) workloads.

“This partnership will bring supercomputer performance to the corporate data center, expanding the use of GPU accelerators well beyond the traditional supercomputing and technical computing markets,” said Ian Buck, vice president of Accelerated Computing at NVIDIA. “It will also provide existing supercomputing and high performance computing customers with new choices and technologies to build powerful, energy-efficient systems that drive innovation and scientific discovery.”

IBM Power Systems will fully support existing scientific, engineering and visualization applications developed with the NVIDIA CUDA® programming model, allowing supercomputing centers and HPC customers to immediately take advantage of groundbreaking performance advantages. IBM also plans to make its Rational brand of enterprise software development tools available to supercomputing developers, making it easier for programmers to develop cutting-edge applications.

The partnership between NVIDIA and IBM builds on the August announcement of the OpenPOWER Consortium, in which IBM, NVIDIA, Google, Mellanox and Tyan aim to establish an open ecosystem based on IBM’s POWER architecture.

About NVIDIA Tesla GPU Accelerators

NVIDIA Tesla GPUs are massively parallel accelerators based on the NVIDIA CUDA parallel computing platform and programming model. Tesla GPUs are designed from the ground up for power-efficient, high performance computing, computational science and supercomputing, delivering dramatically higher application acceleration for a range of scientific and commercial applications than a CPU-only approach.

To learn more about CUDA or download the latest version, visit the CUDA website.

About IBM

For more information on IBM High Performance Computing technologies, visit www.ibm.com/technicalcomputing.

For more information on IBM Software, visit www.ibm.com/software.

About NVIDIA
Since 1993, NVIDIA (NASDAQ: NVDA) has pioneered the art and science of visual computing. The company’s technologies are transforming a world of displays into a world of interactive discovery — for everyone from gamers to scientists, and consumers to enterprise customers. More information at http://nvidianews.nvidia.com and http://blogs.nvidia.com.


Comments

comments

Leave a Reply