March 14, 2016
At the 2016 ISC High Performance conference this June, distinguished Sandia computational combustion scientist Jacqueline H. Chen will deliver a keynote highlighting the latest advances in combustion modeling and simulation. In this interesting and informative Q&A, Chen describes the challenges and opportunities involved in preparing combustion codes for exascale machines. Read more…
August 6, 2015
Among the chief challenges of deploying useful exascale machines, resilience looms large. Today's error rates combined with tomorrow's node counts cannot susta Read more…
July 2, 2015
Today’s launch by IBM, NVIDIA, and Mellanox of a new POWER Acceleration and Design Center in Montpellier, France, ratchets up their campaign to attract a wide Read more…
March 26, 2015
The Indian government has approved a seven-year supercomputing program worth $730 million (Rs. 4,500-crore) intended to restore the nation's status as a world- Read more…
October 6, 2014
India's plans to be a world-class computing power are taking shape as the nation's government lays out its strategy to build a vast supercomputing grid, compri Read more…
July 15, 2014
Quick obsolescence goes hand-in-hand with cutting-edge technology. Supercomputing is no exception, and it's not unusual for these great machines to have lifespa Read more…
June 5, 2014
In supercomputing, it is often the case that top systems are only around for about half a decade. With the breaking of the petascale barrier now fixed in the r Read more…
April 15, 2014
German researchers are helping to push back the goalposts on large-scale simulation. Using the the IBM “SuperMUC” high performance computer at the Leibniz S Read more…
Many organizations looking to meet their CAE HPC requirements focus on the HPC on-premises hardware or cloud options. But one surprise that many find is that the bulk of their HPC total cost of ownership (TCO) comes from the complexity of integrating HPC software with CAE applications and in perfectly orchestrating the many technologies to use the hardware and CAE licenses optimally.
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Five Recommendations to Optimize Data Pipelines
When building AI systems at scale, managing the flow of data can make or break a business. The various stages of the AI data pipeline pose unique challenges that can disrupt or misdirect the flow of data, ultimately impacting the effectiveness of AI storage and systems.
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