NVIDIA partners with IBM for GPU accelerated Super Computing, Unveils Tesla K40 GPU

NVIDIA_Tesla_K40_GPU_Accelerator_TopSo most folks understand that they have a special chip or card in their gadgets which runs the graphics on their computers, phones, game consoles, etc. A Graphics Processing Unit is really good at crunching numbers to provide us things like detailed environments, high resolution textures, dynamic lighting, and fluid particle effects. A GPU is purpose built to chew through information our CPU’s aren’t great at dealing with.

Over the last couple years, that number crunching ability is now being harnessed for other computing tasks. As an example, my video editing software uses my GPU to render video, so my aged workstation is still pretty quick at pushing high quality HD video out the door. The fact that I have an old CPU, doesn’t hamstring me that much.

2_Piz_Daint_destra_con_persona_LRWell, moving up the computing ladder, many number crunching super computers are incorporating GPUs. Piz Daint in Switzerland, activated earlier this year, utilizes NVIDIA K20X GPU’s. It was built for life science, physics, and meteorological simulations. The system is not only the fastest supercomputer in Europe, but it’s also up to 7 times more energy efficient than traditional computing solutions. 

vulcan-supercomputer-LLNL-HPCIC-warmer2Now IBM is looking to move beyond brute force number crunch, modeling, and simulation to bring a host of enterprise and business software solutions to GPU computing. IBM produces corporate server solutions based on their own POWER8 CPU, by incorporating GPU acceleration into their software, businesses will now be able to tap into super computing style performance while also enjoying the power efficiency found in this purpose built hardware.

Just like my home workstation, my CPU is responsible for coordinating software across my whole system. My GPU takes over to drive “power” applications like HD video, gaming, and video rendering. IBM’s move here would enable even more software to utilize the GPU. Take crunching analytics on a video streaming site for example. GPU computing is perfect for chewing up large data sets.

NVIDIA_Tesla_K40_GPU_Accelerator_Front1Alongside their partnership with IBM, NVIDIA is also announcing a new Tesla GPU, the K40. Based on similar technology as what’s found in their top of the line graphics cards, the K40 has twice as much memory as the K20X and should be good for a 40% performance improvement. This should make for almost ten times the performance improvement over traditional CPU server solutions.

And now I’m thinking I might want to upgrade my graphics card again…

Full PR below.

NVIDIA Launches World’s Fastest Accelerator
for Supercomputing and Big Data Analytics

NVIDIA Tesla K40 Accelerator Doubles Memory of Its Predecessor, Enabling New Categories of Accelerated Applications
DENVER—SC13—Nov. 18, 2013—NVIDIA today unveiled the NVIDIA® Tesla® K40 GPU accelerator, the world’s highest performance accelerator ever built, delivering extreme performance to a widening range of scientific, engineering, high performance computing (HPC) and enterprise applications.

NVIDIA_Tesla_K40_GPU_Accelerator_3Qtr1Providing double the memory and up to 40 percent higher performance than its predecessor, the Tesla K20X GPU accelerator, and 10 times higher performance than today’s fastest CPU, the Tesla K40 GPU is the world’s first and highest-performance accelerator optimized for big data analytics and large-scale scientific workloads.

Featuring intelligent NVIDIA GPU Boost™ technology, which converts power headroom into a user-controlled performance boost, the Tesla K40 GPU accelerator enables users to unlock the untapped performance of a broad range of applications.
“GPU accelerators have gone mainstream in the HPC and supercomputing industries, enabling engineers and researchers to consistently drive innovation and scientific discovery,” said Sumit Gupta, general manager of Tesla Accelerated Computing products at NVIDIA. “With the breakthrough performance and higher memory capacity of the Tesla K40 GPU, enterprise customers can quickly crunch through massive volumes of data generated by their big data analytics applications.”

Ultimate Performance for Science, Big Data
Based on the NVIDIA Kepler™ compute architecture – the highest performance, most efficient architecture ever built – the Tesla K40 GPU accelerator surpasses all other accelerators on two common measures of computational performance: 4.29 teraflops single-precision and 1.43 teraflops double-precision peak floating point performance.

Key features of the Tesla K40 GPU accelerator include:
 12GB of ultra-fast GDDR5 memory allows users to process 2X larger datasets, enabling them to rapidly analyze massive volumes of data.
 2,880 CUDA® parallel processing cores deliver application acceleration by up to 10X compared to using a CPU alone.
 Dynamic Parallelism enables GPU threads to dynamically spawn new threads, enabling users to quickly and easily crunch through adaptive and dynamic data structures.
 PCIe Gen-3 interconnect support accelerates data movement by 2X compared to PCIe Gen-2 technology.

In a related announcement, the Texas Advanced Computing Center (TACC) at The University of Texas at Austin — one of the leading advanced computing centers in the United States — plans to deploy “Maverick,” a new interactive, remote visualization and data analysis system powered by NVIDIA Tesla K40 GPU accelerators. Maverick is expected to be fully operational in January 2014.
“The Tesla K40 GPU accelerators will help researchers crunch through massive volumes of big data and gain new insights through large-scale, sophisticated visualizations,” said Kelly Gaither, director of Visualization at TACC. “With NVIDIA GPUs, Maverick will provide researchers powerful interactive capabilities to advance their most complex scientific challenges.”

The Tesla K40 GPU accelerates the broadest range of scientific, engineering, commercial and enterprise HPC and data center applications. Today, more than 240 software applications take advantage of GPU acceleration. The complete catalog of GPU-accelerated applications is available as a free download.

More information about the Tesla K40 GPU accelerator is available at NVIDIA booth 613 at SC13, Nov. 18-21, and on the NVIDIA high performance computing website. To learn more about CUDA or download the latest version, visit the CUDA website.
Users can also try the Tesla K40 GPU accelerator for free on remotely hosted clusters. Visit the GPU Test Drive website for more information.

Availability

Shipping today, the NVIDIA Tesla K40 GPU accelerator is available now and in the coming months from a variety of server manufacturers, including Appro, ASUS, Bull, Cray, Dell, Eurotech, HP, IBM, Inspur, SGI, Sugon, Supermicro and Tyan, as well as from NVIDIA reseller partners.
To Keep Current on NVIDIA:
 Like NVIDIA on Facebook.
 Connect with NVIDIA on LinkedIn.
 Follow @NVIDIA and @NVIDIATesla on Twitter.
 View NVIDIA videos on YouTube.
 Keep up with the NVIDIA Blog.
 Use the Pulse news reader to subscribe to the NVIDIA Daily News feed.

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.
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IBM, NVIDIA to Supercharge Corporate Data Center
Applications and Next-Generation Supercomputers

Companies Tap GPU-Enabled Supercomputing to Analyze Enterprise Data on the Fly
DENVER—SC13—Nov. 18, 2013—NVIDIA and 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.”
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.
To Keep Current on NVIDIA:
 Like NVIDIA on Facebook.
 Connect with NVIDIA on LinkedIn.
 Follow @NVIDIA and @NVIDIATesla on Twitter.
 View NVIDIA videos on YouTube.
 Keep up with the NVIDIA Blog.
 Use the Pulse news reader to subscribe to the NVIDIA Daily News feed.

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.

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