[lld] r288606 - Add comments about the use of threads in LLD.

[Rui Ueyama via llvm-commits]

On Sun, Dec 4, 2016 at 1:55 AM, Sean Silva <chisophugis at gmail.com> wrote:

>
>
> On Sat, Dec 3, 2016 at 3:35 PM, Rui Ueyama via llvm-commits <
> llvm-commits at lists.llvm.org> wrote:
>
>> Author: ruiu
>> Date: Sat Dec  3 17:35:22 2016
>> New Revision: 288606
>>
>> URL: http://llvm.org/viewvc/llvm-project?rev=288606&view=rev
>> Log:
>> Add comments about the use of threads in LLD.
>>
>> Modified:
>>     lld/trunk/ELF/Threads.h
>>
>> Modified: lld/trunk/ELF/Threads.h
>> URL: http://llvm.org/viewvc/llvm-project/lld/trunk/ELF/Threads.h?
>> rev=288606&r1=288605&r2=288606&view=diff
>> ============================================================
>> ==================
>> --- lld/trunk/ELF/Threads.h (original)
>> +++ lld/trunk/ELF/Threads.h Sat Dec  3 17:35:22 2016
>> @@ -6,6 +6,54 @@
>>  // License. See LICENSE.TXT for details.
>>  //
>>  //===------------------------------------------------------
>> ----------------===//
>> +//
>> +// LLD supports threads to distribute workloads to multiple cores. Using
>> +// multicore is most effective when more than one core are idle. At the
>> +// last step of a build, it is often the case that a linker is the only
>> +// active process on a computer. So, we are naturally interested in using
>> +// threads wisely to reduce latency to deliver results to users.
>> +//
>> +// That said, we don't want to do "too clever" things using threads.
>> +// Complex multi-threaded algorithms are sometimes extremely hard to
>> +// justify the correctness and can easily mess up the entire design.
>> +//
>> +// Fortunately, when a linker links large programs (when the link time is
>> +// most critical), it spends most of the time to work on massive number
>> of
>> +// small pieces of data of the same kind. Here are examples:
>> +//
>> +//  - We have hundreds of thousands of input sections that need to be
>> +//    copied to a result file at the last step of link. Once we fix a
>> file
>> +//    layout, each section can be copied to its destination and its
>> +//    relocations can be applied independently.
>> +//
>> +//  - We have tens of millions of small strings when constructing a
>> +//    mergeable string section.
>> +//
>> +// For the cases such as the former, we can just use parallel_for_each
>> +// instead of std::for_each (or a plain for loop). Because tasks are
>> +// completely independent from each other, we can run them in parallel
>> +// without any coordination between them. That's very easy to understand
>> +// and justify.
>> +//
>> +// For the cases such as the latter, we can use parallel algorithms to
>> +// deal with massive data. We have to write code for a tailored algorithm
>> +// for each problem, but the complexity of multi-threading is isolated in
>> +// a single pass and doesn't affect the linker's overall design.
>> +//
>> +// The above approach seems to be working fairly well. As an example,
>> when
>> +// linking Chromium (output size 1.6 GB), using 4 cores reduces latency
>> to
>> +// 75% compared to single core (from 12.66 seconds to 9.55 seconds) on my
>> +// machine. Using 40 cores reduces it to 63% (from 12.66 seconds to 7.95
>> +// seconds). Because of the Amdahl's law, the speedup is not linear, but
>> +// as you add more cores, it gets faster.
>> +//
>> +// On a final note, if you are trying to optimize, keep the axiom "don't
>> +// guess, measure!" in mind. Some important passes of the linker are not
>> +// that slow. For example, resolving all symbols is not a very heavy
>> pass,
>> +// although it would be very hard to parallelize it. You want to first
>> +// identify a slow pass and then optimize it.
>>
>
> Actually, LLD's symbol resolution (the approach with Lazy symbols for
> archives) is a perfect example of a MapReduce type problem, so it is
> actually quite parallelizable.
> You basically have a huge number of (SymbolName,SymbolValue) pairs and you
> want to coalesce all values with the same SymbolName into pairs
> (SymbolName, [SymbolValue1,SymbolValue2,...]) which you can then process
> all the SymbolValueN's to see which is the real definition. This is
> precisely the problem that MapReduce solves.
>

How do you handle static archives?


>
> (note: I don't necessarily mean that it needs to be done in a distributed
> fashion, just that the core problem is really one of coalescing values with
> the same keys.
> )
>
> MapReduce's core abstraction is also a good tool for deduplicating strings.
>
>
> Richard Smith and I were actually brainstorming at the latest llvm social
> a distributed linker may be a good fit for the linking problem at Google
> (but it was just brainstorming; obviously that would be a huge effort and
> we would need very serious justification before embarking on that effort).
>
> -- Sean Silva
>
>
>> +//
>> +//===------------------------------------------------------
>> ----------------===//
>>
>>  #ifndef LLD_ELF_THREADS_H
>>  #define LLD_ELF_THREADS_H
>>
>>
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>>
>
>
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