Re:Lawrence Livermore National Lab's powerful new supercomputer
by halbritt on Tuesday October 30, 2018 @12:20PM
(#18338257)
My back of the napkin calculation says that I can get 270 petaflops with 2160 n1-highmem-16 each with 8 v100 gpu on preemptible instances costing roughly $13k/hr or about $10m/mo
[ Parent
| on HN ]
Re:Lawrence Livermore National Lab's powerful new supercomputer
by rdtsc on Tuesday October 30, 2018 @02:45PM
(#18340047)
So with $120m/y in less than 2 years you'd exceed the price of the whole thing and also likely get worse interconnect speed and possibly raw computational speed.
AWS looks like a bad deal here.
Re:Lawrence Livermore National Lab's powerful new supercomputer
by karambahh on Tuesday October 30, 2018 @03:57PM
(#18340749)
If you have a constant load, on premise is always cheaper. Scientific computation has, for a large enough organization, a 100%
If you have a variable load, cloud infrastructure may make sense if you can easily auto-scale.
In my experience, most business real world applications are multi tiered applications with variable loads hence are a good fit for cloud infrastructure.
However, attaining the required application flexibility and KPIs for efficient auto scaling is quite hard and require strong functional & technical expertise.
Re:Lawrence Livermore National Lab's powerful new supercomputer
by halbritt on Wednesday October 31, 2018 @11:24AM
(#18346440)
My experience totally reflects this. Most enterprise IT infrastructure is idle the majority of the time.
I'm running infrastructure for a SaaS app in k8s. I feel like I'm doing well sustaining >50% efficiency, i.e. all cores running >50% all the time and more than half the memory consumed for things that aren't page cache. Hard to get better efficiency without creating hot spots.