It would be ideal if we lived in a universe where it was possible to increase the capacity of compute, storage, and networking at the same pace so as to keep all three elements expanding in balance. …
The novel architectures story is still shaping out for 2017 when it comes machine learning, hyperscale, supercomputing and other areas. …
There are plenty of things that the members of the high performance community do not agree on, there is a growing consensus that machine learning applications will at least in some way be part of the workflow at HPC centers that do traditional simulation and modeling. …
The US Department of Energy – and the hardware vendors it partners with – are set to enliven the exascale effort with nearly a half billion dollars in research, development, and deployment investments. …
IPOs and major investments in storage startups are one thing, but when it comes to a safe tech company investment, all bets are still on tape. …
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. …
The US Department of Energy fiscal year 2018 budget request is in. …
GPU computing has deep roots in supercomputing, but Nvidia is using that springboard to dive head first into the future of deep learning. …
Enterprise spending on servers was a bit soft in the first quarter, as evidenced by the financial results posted by Intel and by its sometime rival IBM, but the hyperscale and HPC markets, at least when it comes to networking, was a bit soft, according to high-end network chip and equipment maker Mellanox Technologies. …
Energy efficiency and operating costs for systems are as important as raw performance in today’s datacenters. …
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