NVIDIA Unveils Tesla K80 Dual-Chip Compute Accelerator - HardwareHeaven.comHardwareHeaven.com
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The Tesla K80 dual-GPU accelerator was designed with the most difficult computational challenges in mind, ranging from astrophysics, genomics and quantum chemistry to data analytics. It is also optimized for advanced deep learning tasks, one of the fastest growing segments of the machine learning field.

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•Two GPUs per board – Doubles throughput of applications designed to take advantage of multiple GPUs. Essay-writing-service •24GB of ultra-fast GDDR5 memory – 12GB of memory per GPU, 2x more memory than Tesla K40 GPU, allows users to process 2x larger datasets. College Essay Application •480GB/s memory bandwidth – Increased data throughput allows data scientists to crunch though petabytes of information in half the time compared to the Tesla K10 accelerator. Optimized for energy exploration, video and image processing, and data analytics applications. •4,992 CUDA parallel processing cores – Accelerates applications by up to 10x compared to using a CPU alone. Dissertation Proposal For Accounting And Finance •Dynamic NVIDIA GPU Boost Technology – Dynamically scales GPU clocks based on the characteristics of individual applications for maximum performance. Masters Dissertation Abstract Get Distinction •Dynamic Parallelism – Enables GPU threads to dynamically spawn new threads, enabling users to quickly and easily crunch through adaptive and dynamic data structures. http://ducasco.gr/how-to-write-an-essay-on-abortion/ How To Write An Essay On Abortion The Tesla K80 accelerates the broadest range of scientific, engineering, commercial and enterprise HPC and data center applications — more than 280 in all. The complete catalog of GPU-accelerated applications (PDF) is available as a free download.

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Shipping today, the NVIDIA Tesla K80 dual-GPU accelerator will be available from a variety of server manufacturers, including ASUS, Bull, Cirrascale, Cray, Dell, Gigabyte, HP, Inspur, Penguin, Quanta, Sugon, Supermicro and Tyan, as well as from NVIDIA reseller partners.

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