On Jan 31, 2013, at 10:15 AM, Chas Emerick wrote:
>> 
>> Then Wm. Josiah posted a full-application benchmark, which appears to
>> have entirely different performance problems from the synthetic `burn`
>> benchmark.  I’d rejected GC as the cause for the slowdown there too, but
>> ATM can’t recall why or what I tested, so GC may definitely be a
>> candidate to re-examine:
>> 
> 
> I've not looked at clojush at all; it is AFAICT a complex application in its 
> own right, and I wouldn't know where to start.  My understanding is that the 
> `burn` function is considered representative of the bulk of operations in 
> clojush, but I'm happy to assume that that's not the case.  There's likely a 
> number of things that go into the results of the `burn` benchmark, nevermind 
> the apparent performance of clojush.

FWIW I wrote the "burn" benchmark because "lots of intensive list manipulation" 
is at the heart of our real applications, and that seemed to be a nicely 
minimal way to see how that could scale across cores.

Our real applications may indeed raise other issues too, but getting "lots of 
intensive list manipulation" to scale well is bound to be good.

FWIW the "full-application benchmark" that Josiah posted was made deterministic 
in a way that means that big chunks of our code won't actually be executing. 
The system generates and interprets lots of "Push" programs, and if I recall 
correctly the benchmark hardcodes all of the Push programs to be the same 
constant program, meaning that not all of the Push instructions will run, etc. 
It'd be trickier to get the "real" mix of instructions in a way that makes for 
an easily reproducible benchmark, and this benchmark is at least testing the 
basic interpreter and population-level infrastructure. If we can get this to 
scale reasonably then we could try to see how much that helps under 
more-completely "real" conditions.

 -Lee

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