We have a good sense of what projects U.S. companies open source but when it comes to Chinese webscale companies, most notably the big three—Baidu, Alibaba, and Tencent—that ecosystem is less public and not often discussed. …
Seismic processing and analysis at scale take scalable HPC resources but also need an analytics backend that can scale with massive datasets. …
Silent but deadly: there is nothing more destructive than data corruptions that cannot be caught by the various error capture tools in hardware and even in software, can be hard to spot before they have infected an entire application. …
In the accelerated era of exascale supercomputing, MPI is being pushed to its logical limits. …
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. …
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