[Beowulf] interesting article on HPC vs evolution of 'big data' analysis

[Scott Atchley]

There is concern by some and outright declaration by others (including
hardware vendors) that MPI will not scale to exascale due to issues like
rank state growing too large for 10-100 million endpoints, lack of
reliability, etc. Those that make this claim then offer up their favorite
solution (a PGAS variant, Chapel, Legion, Open Community Runtime). Several
assert that the event-driven/task-driven runtimes will take care of data
partitioning, data movement, etc. and that the user only has to define
relationships and dependencies while exposing as much parallelism as
possible.

The domain scientists shudder at the thought of rewriting existing codes,
some of which have existed for decades. If they do get funding to rewrite,
which new programming model should they pick? At this point, there is no
clear favorite.



On Wed, Apr 8, 2015 at 2:31 PM, Prentice Bisbal <prentice.bisbal at rutgers.edu
> wrote:

> I got annoyed by this article and had to stop reading it. I'll go back
> later and try to give it a proper critique, but obviously disagree with
> most of what I've read so far. Right of the bat, the author implies that
> Big Data = HPC, and I disagree with that.
>
> More ranting to come....
>
> Prentice
>
>
> On 04/08/2015 01:16 PM, H. Vidal, Jr. wrote:
>
>> Curious as to what the body of thought is here on this article:
>>
>> http://www.dursi.ca/hpc-is-dying-and-mpi-is-killing-it/
>>
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