
The Biggest Shift in Supercomputing Since GPU Acceleration - Katydid
https://www.nextplatform.com/2017/06/22/biggest-shift-supercomputing-since-gpu-acceleration/
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njyx
Software trumping hardware. Question is how generalizable is that approach.

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Katydid
Wouldn't say it's that simple. The biggest supercomputers need to have a
balance between fat-ass manycore for the MPI/numerics (which won't go away
until physics problems can be solved by DL--seems unlikely); GPUs for
training, and probably something ultra low-power that can take advantage of
power-in-numbers across thousands of nodes (FPGAs potentially). This is still
a co-design effort, but like other areas that have been automated out of
existence, it might be our best and brightest (supposedly) at the top of
computing creating and maintaining these scientific applications should watch
their futures.

