Re: System Panic Makes My Life Easier

On Fri, Jul 29, 2016 at 04:19:28AM +0000, Karen Shaeffer wrote:
> On Thu, Jul 28, 2016 at 05:44:38PM -0700, Rick Moen wrote:
> > Quoting Ivan Sergio Borgonovo ([email protected]):
> > 
> > > Hitting *hard* hardware in the proper way to test it is *hard*.
> > > You could get an idea about it looking at what memtest does, and I'm not 
> > > even sure memtest covers all memory technology.
> > 
> > Memtest will not always catch bad RAM.
> > 
> > The method whose links I posted upthread, which is running iterative
> > kernel compiles in a loop with 'make -j N' for sufficiently high values
> > of N to exercise _all_ RAM, does.  Details in the links.
> > 
> > > If I had to test hardware I would, as Rick suggested boot from a live 
> > > distro, possibly one specialized in testing hardware... and well that's 
> > > exactly what you find if you google it ;)
> > > 
> > > http://www.inquisitor.ru/about/
> > 
> > Please note that VA-CTCS was what VA Linux Systems, Inc. used to
> > torture-test hardware.  It was used for multiple days of burn-in per
> > unit at the factory, and it was used for multiple days of burn-in on all
> > returned units received under RMA.
> > 
> > And then VA's successor in the hardware business, California Digital
> > Corporation, used it that way, too.  
> > 
> > I had the privilege of working at both those firms, and I can say that
> > if a machine doesn't seize up under multiple days of VA-CTCS
> > stress-testing, it's pretty solid.  (It does not test desktop-centric
> > hardware components such as GPUs, though.)
> 
> Hi Rick,
> 
> I understand GPGPUs are key hardware components for consumer platforms. And in
> the past 5 years GPGPUs have become the hottest technology in datacenters as
> well. For example:
> 
> https://code.facebook.com/posts/1687861518126048/facebook-to-open-source-ai-hardware-design/
> 
> Computational loads have evolved with the emergence of deep learning
> algorithms. And GPGPUs in the datacenter are at the tip of the spear of
> bleeding edge ML and AI related distributed applications these days.

For those interested, here is an informative paper:

http://ai.stanford.edu/~acoates/papers/CoatesHuvalWangWuNgCatanzaro_icml2013.pdf


enjoy,
Karen
-- 
Karen Shaeffer                 Be aware: If you see an obstacle in your path,
Neuralscape Services           that obstacle is your path.        Zen proverb