Hi Linas,

> On Aug 4, 2020, at 23:51, Linas Vepstas <[email protected]> wrote:
> 
> We could use memory-mapped files on SSD.
> 
> Ohhh! I like that! This is actually a very interesting idea! And with the 
> appropriate programmer-fu, this should not be hard to proof-of-concept, I 
> think ... so I'm guessing, sometime before the AtomSpace starts up, replace 
> the memory allocator by something that is allocating out of the mapped memory 
> (I think I've seen libraries out there that simplify this). 

I'm glad that you like the idea. I want to try to make the poc!

We may even use sparse memory-mapped files representing much much bigger 
virtual address space than physical RAM as well as SSD storage. All nodes have 
the same file as previously described. Memory management functionality will 
deallocate unused blocks to maintain the file sparse enough, keeping actual 
storage usage limited. I hope this could simplify handling of Atom's identity.

> To get scientific about it, you'd want to create a heat-map -- load up some 
> large datasets, say, some of the genomics datasets, run one of their standard 
> work-loads as a bench-mark, and then see which pages are hit the most often. 
> I mean -- what is the actual working-set size of the genomics processing? No 
> one knows -- we know that during graph traversal, memory is hit "randomly" .. 
> but what is the distribution? It's surely not uniform. Maybe 90% of the work 
> is done on 10% of the pages? (Maybe it's Zipfian?  I'd love to see those 
> charts...)
> 

I would like to see the heat-map for realistic dataset too. That's a next step. 

Are you referring to this genomics dataset benchmark: 
https://github.com/opencog/benchmark/tree/master/query-loop 
<https://github.com/opencog/benchmark/tree/master/query-loop> or there is some 
bigger and better benchmark and dataset for this kind of experiments. What 
about https://github.com/opencog/agi-bio <https://github.com/opencog/agi-bio> ?


best regards, Pedja

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