For the archives... Though this turned out not to be the issue for David's code, Elliot corrected my memory in one regard that seems worth clarifying here:
I was thinking that in the 1.13 compiler, --ieee-float was the default if no flags were used. In actuality, the default w.r.t. floating point arithmetic is actually "whatever the back-end compiler does by default" and the --[no-]ieee-float flag is a means of explicitly overriding this default by asking for stricter or less strict floating point semantics. For that reason, and because of the defaults for various compilers combined with the state of the code base in 1.11, very few use cases would actually have been affected by this version 1.12 change. If I've got the picture straight now, our belief is that it would only affect users who had been using the Cray CCE compiler. -Brad On Tue, 12 Jul 2016, Brad Chamberlain wrote: > > One other possibility that occurred to me groggily this morning is that in > version 1.12.0 we made the --fast flag no longer throw --no-ieee-float by > default (a flag which permits the back-end compiler to use relaxed IEEE > floating point semantics). Specifically, we decided that --fast shouldn't > result in potentially surprising semantic changes like this and that the user > should have to request it explicitly. > > To verify whether this is the cause or not, you ought to be able to compile a > version 1.11 program with --ieee-float *after* your --fast flag or a version > 1.13 program with --no-ieee-float in addition to your --fast flag to see if > that reduced the performance gap you're seeing. > > -Brad > > > On Mon, 11 Jul 2016, Elliot Ronaghan wrote: > >> Hi Dave, >> >> Chapel's performance has significantly improved over the last few releases, >> so it's surprising that you would see a 2X slowdown after upgrading. >> Without >> seeing the code, my initial guess is that you might be getting bad >> first-touch for some arrays now. Prior to 1.11 we serially initialized >> arrays, but we switched to parallel initialization by default in 1.12. If >> you're using a machine with multiple numa domains (it sounds like you are >> since you have multiple cpus) and your code is serial, this could cause a >> slowdown. >> >> You can check if parallel array initialization is causing the slowdown by >> compiling with `-sparallelInitElts=false` and seeing if you get your old >> performance back. That's a big hammer, but it will at least tell us if >> that's the cause of the performance loss. >> >> Feel free to send your code along, and note that there's no problem with >> installing multiple versions of Chapel. >> >> Elliot >> >>> We've upgraded from Chapel 1.11 to 1.13 recently, and we're seeing a >>> drop-off in performance (by about a factor of two) of our Chapel code for >>> Nussinov's Algorithm for RNA sequence alignment. Has anyone else noticed a >>> difference? Does anyone have easy access to both 1.11 and 1.13 and time >>> to >>> verify this result if I send the specific code? We could perhaps try to >>> install two versions at once, but if this is a known problem, I don't want >>> to bother, and if it is new, I thought this might be easier for the >>> developers to confirm, and interesting if it is indeed a change. >>> >>> Note that we also did a hardware upgrade recently, and it is possible that >>> the old numbers come from the old hardware, but I wouldn't expect an >>> hardware upgrade to make things slower ... in case anyone cares, we went >>> from first-generation i7's (i7-860, I think?) to new i5-6500's, and this >>> is >>> a single-threaded code. >>> >>> Thanks for any insight anyone can provide, >>> Dave Wonnacott >> >> >> >> >> ------------------------------------------------------------------------------ >> Attend Shape: An AT&T Tech Expo July 15-16. Meet us at AT&T Park in San >> Francisco, CA to explore cutting-edge tech and listen to tech luminaries >> present their vision of the future. This family event has something for >> everyone, including kids. Get more information and register today. >> http://sdm.link/attshape >> _______________________________________________ >> Chapel-users mailing list >> [email protected] >> https://lists.sourceforge.net/lists/listinfo/chapel-users >> > ------------------------------------------------------------------------------ What NetFlow Analyzer can do for you? Monitors network bandwidth and traffic patterns at an interface-level. Reveals which users, apps, and protocols are consuming the most bandwidth. Provides multi-vendor support for NetFlow, J-Flow, sFlow and other flows. Make informed decisions using capacity planning reports.http://sdm.link/zohodev2dev _______________________________________________ Chapel-users mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/chapel-users
