Silicon Mechanics now offers NVIDIA® Tesla® K10 GPUs

Get three times the performance and greater accessibility

Silicon Mechanics, Inc., a leading manufacturer of rackmount servers, storage, and high-performance computing hardware, announces that it now offers the NVIDIA® Tesla® K10 GPU Computing Accelerator in its hybrid architecture server product line. The new ultra-efficient Kepler-based GPU is designed for high throughput of large, single-precision workloads, and is ideal for seismic processing, signal and image processing, and video analytics.

Developers and researchers can enjoy up to three times more performance per watt with this latest generation of Tesla GPUs, based on Kepler, the world's fastest and most efficient high-performance computing architecture. GPU computing offers unprecedented application performance by offloading compute-intensive portions of the application to the GPU, while the remainder of the code runs on the CPU.

"The Tesla K10 GPUs are designed for single-precision compute performance and memory bandwidth," said Sumit Gupta, senior director of Tesla business at NVIDIA. "The K10 GPU delivers substantial out-of-the-box performance increases for customers running applications like signal processing and image processing."

With a Silicon Mechanics hybrid architecture server equipped with the NVIDIA® Tesla® K10 GPU Computing Accelerator, applications run significantly faster, as users can process large datasets with a massively multi-threaded computing architecture. The Tesla K10 GPU is optimized for a range of scientific and technical single-precision computing applications.

Based on the ultra-efficient GK104 Kepler GPU, the accelerator board features two GK104 GPUs and delivers up to twice the performance for single-precision applications compared to the previous generation Fermi-based Tesla M2090, in the same power envelope. With 4.58 teraflops peak single-precision performance and 320 gigabytes per second memory bandwidth, the Tesla K10 is perfect for workloads where data reliability and overall performance are critical.