SGI Supports New NVIDIA Tesla K40 GPU Accelerators Delivering 10x Performance
GPU accelerators complement SGI computing to enable faster breakthroughs, drive new innovations
DENVER, CO — November 18, 2013 — SGI (NASDAQ: SGI), the trusted leader in high performance computing and Big Data, today announced the availability of NVIDIA® Tesla® K40 GPU accelerators in fully managed and integrated solutions across its entire server product line. The NVIDIA Tesla K40 GPU accelerator is the first and highest-performance accelerator optimized for Big Data analytics and large-scale scientific workloads. It delivers double the memory and up to 40 percent higher performance than its predecessor, and 10 times higher performance than today's fastest CPU. Completely integrated and tested in SGI's manufacturing facility, the solutions include SGI® Management Center™ software and options including Performance Suite to enable customers to be productive in just hours, as opposed to weeks.
SGI customers in financial services, academia and homeland security continue to see significant performance improvements using NVIDIA Tesla accelerators. Example applications are edge trading in financial services, weapons testing, seismic wave applications at Princeton University, along with Sendai Nation College of Technology using SGI with Tesla for electromagnetic field analysis. Swinburne University is another SGI customer that has continued to leverage the NVIDIA Tesla technology for astrophysics research.
"With the assistance of NVIDIA and the Kepler GPU accelerators, the Swinburne supercomputers from SGI have proven to be excellent research tools in areas of astronomy, ranging from simulations of the dynamical evolution of the universe to the processing of data collected from radio telescopes," said Dr. Jarrod Hurley, manager of Swinburne University's supercomputer.
"NVIDIA's accelerators enable our customers to realize significant improvements in processing performance," said Bill Mannel, general manager, Compute at SGI. "Accelerator-based HPC solutions feature intelligent NVIDIA GPU Boost technology, which converts power headroom into a user-controlled performance boost, enabling our customers to unlock the untapped performance of a broad range of applications to address compute and Big Data challenges."
Based on the NVIDIA Kepler™ computing architecture, the NVIDIA Tesla K40 GPU accelerator provides 2,880 CUDA parallel processing cores, 4.29 teraflops single-precision and 1.43 teraflops double-precision peak floating point performance, 12GB of ultra-fast GDDR5 on-board memory and a memory bandwidth of 288 GB/s.
The accelerators are powered by NVIDIA CUDA®, the world's most pervasive parallel computing platform and programming model, and take advantage of innovative technologies like Dynamic Parallelism and Hyper-Q to boost performance and power efficiency. "The Tesla K40 GPU accelerator is designed to bring extreme performance to the industry's broadest range of scientific, engineering, HPC and enterprise big data analytics," said Sumit Gupta, general manager of Tesla Accelerated Computing Products at NVIDIA. "SGI's new Tesla accelerator-enabled servers provide researchers with unique architectures and application capabilities, and a powerful and flexible platform upon which customers can innovate."
All SGI UV and Rackable solutions are available and shipping today. Specific support for NVIDIA Tesla K40 GPUs varies with the platform. Limited numbers of NVIDIA Tesla K40 GPU accelerators can be configured in ICE X solutions via specialty nodes today as well.
Atomic Public Relations | Tessa Chen | (415) 593-1400 | email@example.com
© 2013 Silicon Graphics International Corp. All rights reserved. SGI, SGI UV, SGI ICE X, SGI Management Center, Rackable and the SGI logo are trademarks or registered trademarks of Silicon Graphics International Corp. or its subsidiaries in the United States and/or other countries. NVIDIA Tesla, NVIDIA CUDA and NVIDIA Kepler are registered trademarks of NVIDIA. All other trademarks are property of their respective holders.