Jupyter Expands Orbit in Supercomputing
Jupyter may have had its beginnings in enterprise data problems but some in the high performance computing community has been adopting it as the prime platform for both data science and AI at massive scale. …
Jupyter may have had its beginnings in enterprise data problems but some in the high performance computing community has been adopting it as the prime platform for both data science and AI at massive scale. …
There are a few unignorable trends in high performance computing, especially in the exascale age. …
The 2010s provided a range of new quantum hardware makers to evaluate but the 2020s will be focused far more software for broader use of nascent quantum devices. …
While the promise of neuromorphic computing going mainstream is still mostly unrealized, there are steps being taken to bring it closer to reality. …
For those who are at the intersection of AI hardware and software, the open source Apache TVM effort is already well known and used among a number of chipmakers as well as developers. …
The rapid adoption by enterprises of hybrid cloud and multicloud environments along with the rise of the Internet of Things, a much more remote workforce and other trends that have contributed to the increasingly distributed nature of modern IT has put the vast amounts of data that is being generated in a precarious position. …
Although hardware gets all the attention during Supercomputing week, much has been happening behind the scenes to make all the software run on the latest, fastest systems. …
“Times were simpler not so long ago” is an understatement these days, but when it comes to supercomputing, this has yet another meaning. …
Java turned 25 years old in May, marking a quarter of a century in which it has consistently been one of the most widely used programming languages. …
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