Array vs Slice: accessing speed

Question

This question is about the speed of accessing elements of arrays and slices, not about the efficiency of passing them to functions as arguments.

I would expect arrays to be faster than slices in most cases because a slice is a data structure describing a contiguous section of an array and so there may be an extra step involved when accessing elements of a slice (indirectly the elements of its underlying array).

So I wrote a little test to benchmark a batch of simple operations. There are 4 benchmark functions, the first 2 test a global slice and a global array, the other 2 test a local slice and a local array:

var gs = make([]byte, 1000) // Global slice
var ga [1000]byte           // Global array

func BenchmarkSliceGlobal(b *testing.B) {
    for i := 0; i < b.N; i++ {
        for j, v := range gs {
            gs[j]++; gs[j] = gs[j] + v + 10; gs[j] += v
        }
    }
}

func BenchmarkArrayGlobal(b *testing.B) {
    for i := 0; i < b.N; i++ {
        for j, v := range ga {
            ga[j]++; ga[j] = ga[j] + v + 10; ga[j] += v
        }
    }
}

func BenchmarkSliceLocal(b *testing.B) {
    var s = make([]byte, 1000)
    for i := 0; i < b.N; i++ {
        for j, v := range s {
            s[j]++; s[j] = s[j] + v + 10; s[j] += v
        }
    }
}

func BenchmarkArrayLocal(b *testing.B) {
    var a [1000]byte
    for i := 0; i < b.N; i++ {
        for j, v := range a {
            a[j]++; a[j] = a[j] + v + 10; a[j] += v
        }
    }
}

I ran the test multiple times, here is the typical output (go test -bench .*):

BenchmarkSliceGlobal      300000              4210 ns/op
BenchmarkArrayGlobal      300000              4123 ns/op
BenchmarkSliceLocal       500000              3090 ns/op
BenchmarkArrayLocal       500000              3768 ns/op

Analyzing the results:

Accessing the global slice is slightly slower than accessing the global array which is as I expected:
4210 vs 4123 ns/op

But accessing the local slice is significantly faster than accessing the local array:
3090 vs 3768 ns/op

My question is: What is the reason for this?

Notes

I tried varying the following things but none changed the outcome:

the size of the array/slice (tried 100, 1000, 10000)
the order of the benchmark functions
the element type of the array/slice (tried byte and int)

There are several factors which influence such micro benchmarks: Bounds checking, allocation (heap, stack), code generation, peephole optimizations, etc. Have a look at the generated assembly output under different conditions like disabled bound checking or disabled optimizations. — Volker
Interestingly enough, if you add a pointer to array to the benchmarks, you'll see that they perform about the same as slices. — Ainar-G

thwd thwd · Accepted Answer · 2015-05-29T09:37:58

Comparing the amd64 assembly of both BenchmarkArrayLocal and BenchmarkSliceLocal (too long to fit in this post):

The array version loads the address of a from memory multiple times, practically on every array-access operation:

LEAQ    "".a+1000(SP),BX

Whereas the slice version is computing exclusively on registers after loading once from memory:

LEAQ    (DX)(SI*1),BX

This is not conclusive but probably the cause. Reason being that both methods are otherwise virtually identical. One other notable detail is that the array version calls into runtime.duffcopy, which is a quite long assembly routine, whereas the slice version doesn't.

Array vs Slice: accessing speed

2 Answers