The Hard Limits for Deep Learning in HPC
If the hype is to be believed, there is no computational problem that cannot be tackled faster and better by artificial intelligence. …
If the hype is to be believed, there is no computational problem that cannot be tackled faster and better by artificial intelligence. …
We caught wind of the “Aurora” Vector Engine vector processor and the “Tsubasa” system from NEC that makes use of it ahead of the SC17 supercomputer conference, and revealed everything we could find out about the system and speculated a bit about how the underlying processor in the absence of real data. …
Every year at the Supercomputing Conference (SC) an unofficial theme emerges. …
The oil and gas industry has been on the cutting edge of many waves of computing over the several decades that supercomputers have been used to model oil reservoirs in both the planning of the development of an oil field and in quantifying the stored reserves of a field and therefore the future possible revenue stream of the company. …
When talking about the future of supercomputers and high-performance computing, the focus tends to fall on the ongoing and high-profile competition between the United States with its slowly eroding place as the kingpin in the industry and China and the tens of billions of dollars that the government has invested in recent years to rapidly expand the reach of the country’s tech community and the use of home-grown technologies in massive new systems. …
All the compute power in the world is useless against code that cannot scale. …
For years, the pace of change in large-scale supercomputing neatly tracked with the curve of Moore’s Law. …
Many hands make light work, or so they say. So do many cores, many threads and many data points when addressed by a single computing instruction. …
This fall will mark twenty years since the publication of the v1.0 specification of OpenMP Fortran. …
After years of planning and delays after a massive architectural change, the Blue Waters supercomputer at the National Center for Supercomputing Applications at the University of Illinois finally went into production in 2013, giving scientists, engineers and researchers across the country a powerful tool to run and solve the most complex and challenging applications in a broad range of scientific areas, from astrophysics and neuroscience to biophysics and molecular research. …
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