By: Maynard Handley (name99.delete@this.name99.org), December 9, 2014 11:41 am
Room: Moderated Discussions
Gabriele Svelto (gabriele.svelto.delete@this.gmail.com) on December 9, 2014 7:48 am wrote:
> Linus Torvalds (torvalds.delete@this.linux-foundation.org) on December 8, 2014 8:08 pm wrote:
> > Maybe. And probably not. Given the choice between 16 cores and 4, I suspect most people
> > will take 4, and prefer more cache, graphics, and integrated networking etc.
>
> I'd take the 4-core option you proposed any day over the 16 cores one
> in spite of still spending a large portion of my time compiling code.
>
> > Some things are cheap and easy. But those are done already. Building stuff in parallel? Trivial
> > - except even there people tend to have build tools and Makefiles etc that make it not work that
> > well in many cases. So even something really simple like a software workstation often doesn't
> > scale that well (I'm happy to say that the kernel build scales exceptionally well, but most projects
> > don't have tens of thousands of files and lots of effort on the build system.
>
> I've got an interesting data-point to add that goes to show that a full parallel approach is not
> always the best choice. Mozilla's Gecko has a bizarre, complex build system it inherited from the
> good ole' days of Netscape and the new economy bubble. Last year quite a few developers sunk a significant
> portion of their time modernizing it and making sure it scaled properly by removing the typical
> scalar sections that plague almost all older codebases (recursive make invocations, non-parallel
> build steps, etc...). With well north of 20k source files, once the build system was properly parallelized,
> we could fully scale compilation on pretty much *any* existing hardware.
>
> However compiling a file does have both fixed costs (e.g. bootstrapping today's large compilers)
> as well as totally redundant variable ones (e.g. re-parsing the same header files multiple times,
> which in a C++ codebase are usually both large and many). Enter unified builds: the next step after
> parallelizing the build system was to build sources in batches of 16 per compiler invocation instead
> of one at a time. This has a few drawbacks such as a significant increase in memory consumption as
> well as some nuisances if the sources have similarly named symbols or muck around with #defines.
> However the speedup was well worth it; I'll let a ML post from that period do the talking:
>
> Recent build time improvements due to unified sources
>
>
> less thanks to not having to deal with the crazy C++ let's-stick-implementations-in-our-header-files
> plague. But this goes to show that parallelizing a workload to the extreme will not always
> guarantee you the best performance. Quite the contrary in many cases.
>
Of course, per my previous post, the obvious rejoinder to this would be: "get a better language and a better codebase".
Now that is flip, but it carries a core of truth. IF your goal is to keep on using an ancient codebase indefinitely, then you're, more or less by definition, in the business of wanting computers that look exactly like what the ancient codebase targeted, only faster. Point is, new codebases come along as well, and THEY are willing to adapt themselves to new hardware.
IBM seems to be doing OK selling mainframes, but I don't see the rest of us assuming that we need to write our code using mainframe paradigms. At some point a Google says "to hell with this, we're starting from scratch and can organize things completely differently"...
> Linus Torvalds (torvalds.delete@this.linux-foundation.org) on December 8, 2014 8:08 pm wrote:
> > Maybe. And probably not. Given the choice between 16 cores and 4, I suspect most people
> > will take 4, and prefer more cache, graphics, and integrated networking etc.
>
> I'd take the 4-core option you proposed any day over the 16 cores one
> in spite of still spending a large portion of my time compiling code.
>
> > Some things are cheap and easy. But those are done already. Building stuff in parallel? Trivial
> > - except even there people tend to have build tools and Makefiles etc that make it not work that
> > well in many cases. So even something really simple like a software workstation often doesn't
> > scale that well (I'm happy to say that the kernel build scales exceptionally well, but most projects
> > don't have tens of thousands of files and lots of effort on the build system.
>
> I've got an interesting data-point to add that goes to show that a full parallel approach is not
> always the best choice. Mozilla's Gecko has a bizarre, complex build system it inherited from the
> good ole' days of Netscape and the new economy bubble. Last year quite a few developers sunk a significant
> portion of their time modernizing it and making sure it scaled properly by removing the typical
> scalar sections that plague almost all older codebases (recursive make invocations, non-parallel
> build steps, etc...). With well north of 20k source files, once the build system was properly parallelized,
> we could fully scale compilation on pretty much *any* existing hardware.
>
> However compiling a file does have both fixed costs (e.g. bootstrapping today's large compilers)
> as well as totally redundant variable ones (e.g. re-parsing the same header files multiple times,
> which in a C++ codebase are usually both large and many). Enter unified builds: the next step after
> parallelizing the build system was to build sources in batches of 16 per compiler invocation instead
> of one at a time. This has a few drawbacks such as a significant increase in memory consumption as
> well as some nuisances if the sources have similarly named symbols or muck around with #defines.
> However the speedup was well worth it; I'll let a ML post from that period do the talking:
>
> Recent build time improvements due to unified sources
>
>
In less than 4 months, clobber build time on my machine has decreased by ~44%,Now Gecko - as a large C++ codebase - is a special case; a C codebase would have benefited
> objdir size by ~22%, and DWARF size (approximated by libxul-(text+data+bss))
> by ~34%.
>
>
> less thanks to not having to deal with the crazy C++ let's-stick-implementations-in-our-header-files
> plague. But this goes to show that parallelizing a workload to the extreme will not always
> guarantee you the best performance. Quite the contrary in many cases.
>
Of course, per my previous post, the obvious rejoinder to this would be: "get a better language and a better codebase".
Now that is flip, but it carries a core of truth. IF your goal is to keep on using an ancient codebase indefinitely, then you're, more or less by definition, in the business of wanting computers that look exactly like what the ancient codebase targeted, only faster. Point is, new codebases come along as well, and THEY are willing to adapt themselves to new hardware.
IBM seems to be doing OK selling mainframes, but I don't see the rest of us assuming that we need to write our code using mainframe paradigms. At some point a Google says "to hell with this, we're starting from scratch and can organize things completely differently"...