Original post

At EDGE we write a lot of , and we love it for various reasons, one of them being speed. One day I got into a situation where I need to assign an int to a variable based on another string value.

Sounds easy right? well yes, but this particular use case awakened the beast in me and made me think what’s the best way to do it.

The journey finished by me contributing to the language compiler and make map lookups faster.

Situation

Our binaries can be found in 3 flavors, amd64, arm64, and arm. Sometimes a running binary needs to know what is its architecture, for example when pulling images/other binaries if the current running binary is an amd64 binary then we should use the amd64 repository or registry.

In Go that’s easy. The constant runtime.GOARCH gives us the running program’s architecture.

In one case, I needed to assign an int to a variable based on the value of runtime.GOARCH. And the code below does exactly that:

var archIndex int
switch runtime.GOARCH {
    case "amd64": 
        archIndex = 0
    case "arm64": 
        archIndex = 1
    case "arm": 
        archIndex = 2
}

But I didn’t want it to be that way because the day we support another architecture I need to add another case clause and that didn’t feel right to me.

It’s a simple value mapping and I though using a map followed by a lookup would be better. Below was the map based solution:

archIndex := map[string]int{
        "amd64": 0,
        "arm":   1,
        "arm64": 2,
}[runtime.GOARCH]

Problem

The map based solution felt more readable and maintainable to me but I was curious which solution was faster?

The code is not in a hot path, and micro-optimizing it is not needed. But still wanted to know what’s faster.

To satisfy my curiosity, I benchmarked both approaches.

goos: darwin
goarch: amd64
BenchmarkMapImpl-4     19503195       58.0 ns/op
BenchmarkSwitchImpl-4  1000000000     0.648 ns/op

Turns out the map based solution is 96 times slower than the switch based one. To understand why it’s the case I start analyzing the generated code for both approaches.

Compiler generated code

Like any other language compiler, to generate the final output the Go compiler will pass through various phases:

  • Scanning: Scans the source code and split it into tokens
  • Parsing: Parses those tokens and build the Abstract Syntax Tree (AST). Also checks that the code is a valid Go code (type checking etc..)
  • Code generating: convert the AST to a lower-level representation of the program, specifically into a Static Single Assignment (SSA) form

At the end of the parsing phase, we are certain the program is valid Go code. The interesting phase for our case is the last one.

The code generation phase takes the AST, applies some optimization to the AST itself by re-writing it, and then convert it into an SSA form. After the initial version of the SSA has been generated, several optimization passes will be applied like “dead code elimination”, “constant propagation” and “bound check elimination”

We can see the work of each optimizer and the final SSA for our function by running this command

GOSSAFUNC=switchImplementation go tool compile benchmark_test.go

The command generates a html file ssa.html showing the generated SSA for the function switchImplementation.

switch based implementation

The final SSA form for our switchImplementation function looks like this:

00000 (8) TEXT "".switchImplementation(SB), ABIInternal
00001 (8) FUNCDATA $0, gclocals·33cdeccccebe80329f1fdbee7f5874cb(SB)
00002 (8) FUNCDATA $1, gclocals·33cdeccccebe80329f1fdbee7f5874cb(SB)
00003 (8) FUNCDATA $2, gclocals·33cdeccccebe80329f1fdbee7f5874cb(SB)
00004 (+11) PCDATA $0, $0
00005 (+11) PCDATA $1, $0

00006 (+11) MOVQ $0, "".~r0(SP)

00007 (11) RET
00008 (?) END

The first block is the function epilogue where mainly a stack frame needs to be allocated. The second one is the body, and the final block is the function prologue where the functions need to return to its caller.

The function body in our case is a simple move instruction which moves 0 to the ~r0 registry. So the function is only returning 0 immediately there is nothing else. To confirm this I generated the SSA for the following function:

func return0() int {
    return 0
}

And the final generated code is exactly the same as you can see it here. And that’s why it’s so fast.

map based implementation

As for the SSA form of the mapImplementation function, it’s longer, I annotated it so it’s easier to understand what’s happening.

00000 (31) TEXT "".mapImplementation(SB), ABIInternal
00001 (31) FUNCDATA $0, gclocals·7d2d5fca80364273fb07d5820a76fef4(SB)
00002 (31) FUNCDATA $1, gclocals·b9237f7ca55cc8bf6e05646631ad00ce(SB)
00003 (31) FUNCDATA $2, gclocals·a5ed3e65458aadaa1d48863859d2a323(SB)
00004 (31) FUNCDATA $3, "".mapImplementation.stkobj(SB)
00005 (+32) PCDATA $0, $0
00006 (+32) PCDATA $1, $1
00007 (+32) XORPS X0, X0
00008 (32) MOVUPS X0, ""..autotmp_2-256(SP)
00009 (32) MOVUPS X0, ""..autotmp_2-240(SP)
00010 (32) MOVUPS X0, ""..autotmp_2-224(SP)
00011 (32) PCDATA $0, $1
00012 (32) PCDATA $1, $2
00013 (32) LEAQ ""..autotmp_3-208(SP), DI
00014 (32) PCDATA $0, $0
00015 (32) LEAQ -48(DI), DI
00016 (32) DUFFZERO $239
00017 (32) PCDATA $0, $2
00018 (32) PCDATA $1, $1
00019 (32) LEAQ ""..autotmp_3-208(SP), AX
00020 (32) PCDATA $0, $0
00021 (32) MOVQ AX, ""..autotmp_2-240(SP)
00022 (32) CALL runtime.fastrand(SB)
00023 (32) MOVL (SP), AX
00024 (32) MOVL AX, ""..autotmp_2-244(SP)
00025 (33) PCDATA $0, $2
00026 (+33) LEAQ type.map[string]int(SB), AX
00027 (33) PCDATA $0, $0
00028 (33) MOVQ AX, (SP)
00029 (33) PCDATA $0, $3
00030 (33) LEAQ ""..autotmp_2-256(SP), CX
00031 (33) PCDATA $0, $0
00032 (33) MOVQ CX, 8(SP)
00033 (33) PCDATA $0, $4
00034 (33) LEAQ go.string."amd64"(SB), DX
00035 (33) PCDATA $0, $0
00036 (33) MOVQ DX, 16(SP)
00037 (33) MOVQ $5, 24(SP)
00038 (+33) CALL runtime.mapassign_faststr(SB)    // assign "amd64" key
00039 (33) PCDATA $0, $2
00040 (33) MOVQ 32(SP), AX
00041 (33) PCDATA $0, $0
00042 (33) MOVQ $0, (AX)                          // assign "0" value
00043 (34) PCDATA $0, $2
00044 (+34) LEAQ type.map[string]int(SB), AX
00045 (34) PCDATA $0, $0
00046 (34) MOVQ AX, (SP)
00047 (34) PCDATA $0, $3
00048 (34) LEAQ ""..autotmp_2-256(SP), CX
00049 (34) PCDATA $0, $0
00050 (34) MOVQ CX, 8(SP)
00051 (34) PCDATA $0, $4
00052 (34) LEAQ go.string."arm"(SB), DX
00053 (34) PCDATA $0, $0
00054 (34) MOVQ DX, 16(SP)
00055 (34) MOVQ $3, 24(SP)
00056 (+34) CALL runtime.mapassign_faststr(SB)    // assign "arm" key
00057 (34) PCDATA $0, $2
00058 (34) MOVQ 32(SP), AX
00059 (34) PCDATA $0, $0
00060 (34) MOVQ $1, (AX)                          // assign "1" value
00061 (35) PCDATA $0, $2
00062 (+35) LEAQ type.map[string]int(SB), AX
00063 (35) PCDATA $0, $0
00064 (35) MOVQ AX, (SP)
00065 (35) PCDATA $0, $3
00066 (35) LEAQ ""..autotmp_2-256(SP), CX
00067 (35) PCDATA $0, $0
00068 (35) MOVQ CX, 8(SP)
00069 (35) PCDATA $0, $4
00070 (35) LEAQ go.string."arm64"(SB), DX
00071 (35) PCDATA $0, $0
00072 (35) MOVQ DX, 16(SP)
00073 (35) MOVQ $5, 24(SP)
00074 (+35) CALL runtime.mapassign_faststr(SB)    // assign "arm64" key
00075 (35) PCDATA $0, $2
00076 (35) MOVQ 32(SP), AX
00077 (35) PCDATA $0, $0
00078 (35) MOVQ $2, (AX)                          // assign "2" value
00079 (36) PCDATA $0, $2
00080 (+36) LEAQ type.map[string]int(SB), AX
00081 (36) PCDATA $0, $0
00082 (36) MOVQ AX, (SP)
00083 (36) PCDATA $0, $2
00084 (36) PCDATA $1, $0
00085 (36) LEAQ ""..autotmp_2-256(SP), AX
00086 (36) PCDATA $0, $0
00087 (36) MOVQ AX, 8(SP)
00088 (36) PCDATA $0, $2
00089 (36) LEAQ go.string."amd64"(SB), AX
00090 (36) PCDATA $0, $0
00091 (36) MOVQ AX, 16(SP)
00092 (36) MOVQ $5, 24(SP)
00093 (+36) CALL runtime.mapaccess1_faststr(SB)  // perform the map lookup
00094 (36) PCDATA $0, $2
00095 (36) MOVQ 32(SP), AX
00096 (36) PCDATA $0, $0
00097 (36) MOVQ (AX), AX
00098 (+32) MOVQ AX, "".~r0(SP)
00099 (+36) RET
00100 (?) END

The reason behind this is the fact that the generated code is building the map which requires allocating it, assign the different values, and then doing a lookup.

Constant folding

The reason why the switch implementation is similar to a return 0 is something called constant folding.

Constant folding is the process of recognizing and evaluating constant expressions at compile time rather than computing them at runtime – Wikipedia

We know that runtime.GOARCH is a constant, so not only its value cannot change but also it’s known at compile time. The compiler can use this two properties to evaluate constant expression at compile time instead of doing that when running, in our case the compiler knew which of the case clauses is true so it deleted the conditional structure and replaced it with a naked return 0.

This was not the case on the map based implementation.

Implement the optimization

Our map lookup looks like this:

map[string]int{
        "amd64": 0,
        "arm":   1,
        "arm64": 2,
}[runtime.GOARCH]

This is represented in the AST using an INDEXMAP node. The INDEXMAP has two childs left and right (remember it’s a tree).

The left child is the map we will lookup from, and the right child is the key we are looking for. Both childs are also nodes, for example the right node can be a FUNCCALL node for a lookup like this:

map[string]int{
        "amd64": 0,
        "arm":   1,
        "arm64": 2,
}[aRandomFunc()]

At compile time, we can check if both right and left nodes are constant, if they are, we see if what are we looking for (the key), is defined in the constant map, and if it’s the case we replace the INDEXMAP node in the AST by the value of that key. This will replace all lookups on maps where the map is an OMAPLIT and the key is a constant with a constant if possible.

This optimization is applied directly to the AST and not the SSA form. This type of AST optimization is implemented inside the walk function.

The PR with this optimization can be seen here: https://go-review.googlesource.com/c/go/+/208323

The new generated SSA with that optimization can be found here

Now if we benchmark both implementations using the Go compiler from that branch we see that both are similar. They are both similar to our return 0 function.

BenchmarkSwitchImpl-4           1000000000               0.599 ns/op           0 B/op          0 allocs/op
BenchmarkMapImpl-4              1000000000               0.612 ns/op           0 B/op          0 allocs/op

Conclusion

The PR is not merged yet, hopefully soon, it got added to Go 1.15 milestone which should be released in a month.

Huge thanks to everyone in the # channel in Gophers slack