Add comments about the use of threads in LLD.

llvm-svn: 288606

1 files changed, 48 insertions, 0 deletions

diff --git a/lld/ELF/Threads.h b/lld/ELF/Threads.h
index 4103762c7d5..58d24970e7b 100644
--- a/lld/ELF/Threads.h
+++ b/lld/ELF/Threads.h
@@ -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.
+//
+//===----------------------------------------------------------------------===//
 
 #ifndef LLD_ELF_THREADS_H
 #define LLD_ELF_THREADS_H