内容简介:This is a post about how the Go compiler implements inlining and how this optimisation affects your Go code.Inlining is the act of combining smaller functions into their respective callers. In the early days of computing this optimisation was typically pe
This is a post about how the Go compiler implements inlining and how this optimisation affects your Go code.
n.b This article focuses on gc the de facto Go compiler from golang.org . The concepts discussed apply broadly to other Go compilers like gccgo and llgo but may differ in implementation and efficacy.
What is inlining?
Inlining is the act of combining smaller functions into their respective callers. In the early days of computing this optimisation was typically performed by hand. Nowadays inlining is one of a class of fundamental optimisations performed automatically during the compilation process.
Why is inlining important?
Inlining is important for two reasons. The first is it removes the overhead of the function call itself. The second is it permits the compiler to more effectively apply other optimisation strategies.
Function call overhead
Calling a function in any language carries a cost. There are the overheads of marshalling parameters into registers or onto the stack (depending on the ABI) and reversing the process on return. Invoking a function call involves jumping the program counter from one point in the instruction stream to another which can cause a pipeline stall. Once inside the function there is usually some preamble required to prepare a new stack frame for the function to execute and a similar epilogue needed to retire the frame before returning to the caller.
In Go a function call carries additional costs to support dynamic stack growth. On entry the goroutine’s amount of stack available is compared to the amount required for the function. If insufficient stack space is available, the preamble jumps into the runtime logic that grows the stack by copying it to a new, larger, location. Once this is done the runtime jumps back to the start of the original function, the stack check is performed again, which now passes, and the call continues. In this way goroutines can start with a small dynamic stack allocation which grows only when needed.
This check is cheap–only a few instructions–and because goroutine stacks grows geometrically the check rarely fails thus the branch prediction units in modern processors can hide the cost of the stack check by assuming it will always be successful. In the case where the processor mis-predicts the stack check and has to discard the work done while it was executing speculatively, the cost of the pipeline stall is relatively small compared to the cost of the work needed by the runtime to grow a goroutines stack.
While the overhead of the generic and Go specific components of each function call are well optimised by modern processors using speculative execution techniques, those overheads cannot be eliminated, thus each function call carries with it a performance cost over and above the time it takes to perform useful work. As a function call’s overhead is fixed, smaller functions pay a larger cost relative to larger ones because they tend to do less useful work per invocation.
The solution to eliminating these overheads must therefore be to eliminate the function call itself, which the Go compiler does by, under certain conditions, replacing the call to a function with the contents of the function. This is called inlining because it brings the body of the function in line with its caller.
Improved optimisation opportunities
Dr. Cliff Click describes inlining as the optimisation performed by modern compilers because it forms the basis for optimisations like constant proportion and dead code elimination. In effect, inlining allows the compiler to see furthe r, allowing it to observe, in the context that a particular function is being called, logic that can be further simplified or eliminated entirely. As inlining can be applied recursively optimisation decisions can be made not only as specific point optimisations, but also applied to the functions in a call path.
Inlining in action
The effects of inlining can be demonstrated with this small example
package main import "testing" //go:noinline func max(a, b int) int { if a > b { return a } return b } var Result int func BenchmarkMax(b *testing.B) { var r int for i := 0; i < b.N; i++ { r = max(-1, i) } Result = r }
Running this benchmark gives the following result:
% <strong>go test -bench=. </strong> BenchmarkMax-4 530687617 2.24 ns/op
So, the cost of max(-1, i)
is around 2.24 nanoseconds on my 2015 MacBook Air. Now let’s remove the //go:noinline
pragma and see the result:
% <strong>go test -bench=. </strong> BenchmarkMax-4 1000000000 0.514 ns/op
From 2.24 ns to 0.51 ns, or according to benchstat
, a 77% improvement.
% <strong>benchstat {old,new}.txt</strong> name old time/op new time/op delta Max-4 2.21ns ± 1% 0.49ns ± 6% -77.96% (p=0.000 n=18+19)
Where did the improvements come from?
First, the removal of the function call and associated preamble
was a major contributor. Pulling the contents of max
into its caller reduced the number of instructions executed by the processor and eliminated several branches.
Now the contents of max
are visible to the compiler as it optimises BenchmarkMax
it can make some additional improvements. Consider that once max
is inlined, this is what the body of BenchmarkMax
looks like to the compiler:
func BenchmarkMax(b *testing.B) { var r int for i := 0; i < b.N; i++ { if -1 > i { r = -1 } else { r = i } } Result = r }
Running the benchmark again we see our manually inlined version performs as well as the version inlined by the compiler
% <strong>benchstat {old,new}.txt</strong> name old time/op new time/op delta Max-4 2.21ns ± 1% 0.48ns ± 3% -78.14% (p=0.000 n=18+18)
Now the compiler has access to the result of inlining max
into BenchmarkMax
it can apply optimisation passes which were not possible before. For example, the compiler has noted that i
is initialised to 0
and only incremented so any comparison with i
can assume i
will never be negative. Thus, the condition -1 > i
will never be true.
Having proved that -1 > i
will never be true, the compiler can simplify the code to
func BenchmarkMax(b *testing.B) { var r int for i := 0; i < b.N; i++ { if false { r = -1 } else { r = i } } Result = r }
and because the branch is now a constant, the compiler can eliminate the unreachable path leaving it with
func BenchmarkMax(b *testing.B) { var r int for i := 0; i < b.N; i++ { r = i } Result = r }
Thus, through inlining and the optimisations it unlocks, the compiler has reduced the invocation of max(-1, i)
to r = i
.
The limits of inlining
In this article I’ve discussed, so called, leaf inlining; the act of inlining a function at the bottom of a call stack into its direct caller. Inlining is a recursive process, once a function has been inlined into its caller, the compiler may inline the resulting code into its caller, as so on. For example, this code
func BenchmarkMaxMaxMax(b *testing.B) { var r int for i := 0; i < b.N; i++ { r = max(max(-1, i), max(0, i)) } Result = r }
Runs as fast as the previous examples as the compiler is able to repeatedly apply the optimisations outlined above to reduce the code to the same r = i
loop.
In the next article I’ll discuss an alternative inlining strategy when the Go compiler wishes to inline a function in the middle of a call stack. Finally I’ll discuss the limits that the compiler is prepared to go to to inline code, and which Go constructs are currently beyond its capability.
- In Go, a method is just a function with a predefined formal parameter, the receiver. The relative costs of calling a free function vs a invoking a method, assuming that method is not called through an interface, are the same.
- Up until Go 1.14 the stack check preamble was also used by the garbage collector to stop the world by setting all active goroutine’s stacks to zero, forcing them to trap into the runtime the next time they made a function call. This system was recently replaced with a mechanism which allowed the runtime to pause an goroutine without waiting for it to make a function call.
-
I’m using the
//go:noinline
pragma to prevent the compiler from inliningmax
. This is because I want to isolate the effects of inlining onmax
rather than disabling optimisations globally with-gcflags='-l -N'
. I go into detail about the//go
: comments inthis presentation. -
You can check this for yourself by comparing the output of
go test -bench=. -gcflags=-S
with and without the//go:noinline
annotation. -
You can check this yourself with the
-gcflags=-d=ssa/prove/debug=on
flag.
以上就是本文的全部内容,希望本文的内容对大家的学习或者工作能带来一定的帮助,也希望大家多多支持 码农网
猜你喜欢:本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们。
Spring Cloud微服务实战
翟永超 / 电子工业出版社 / 2017-5 / 89
《Spring Cloud微服务实战》从时下流行的微服务架构概念出发,详细介绍了Spring Cloud针对微服务架构中几大核心要素的解决方案和基础组件。对于各个组件的介绍,《Spring Cloud微服务实战》主要以示例与源码结合的方式来帮助读者更好地理解这些组件的使用方法以及运行原理。同时,在介绍的过程中,还包含了作者在实践中所遇到的一些问题和解决思路,可供读者在实践中作为参考。 《Sp......一起来看看 《Spring Cloud微服务实战》 这本书的介绍吧!