Home / Improving speed of pure Go SMAZ compressor by 2.6x/1.5x

I was testing fast compressors in pure Go. One of them was Go implementation of SMAZ algorithm for compressing small strings. It’s simple, fast and works well for English text.

It wasn’t as fast as I expected so I looked at the code and with a few tweaks I managed to speed up decompression 2.61x times and compression 1.54x times:

kjkmacpro:smaz kjk$ benchcmp before.txt after.txt
benchmark                  old ns/op     new ns/op     delta
BenchmarkCompression       3387936       2195304       -35.20%
BenchmarkDecompression     2667583       1022908       -61.65%

benchmark                  old MB/s     new MB/s     speedup
BenchmarkCompression       40.35        62.26        1.54x
BenchmarkDecompression     28.34        73.90        2.61x

The speed increase came from 3 micro-optimizations.

1. Don’t use bytes.Buffer if []byte will do.

The biggest decompression speed-up came from this change where I replaced the use of bytes.Buffer with using slices directly.

bytes.Buffer is a wrapper around []byte. It adds convenience by implementing popular interfaces like io.Reader, io.Writer etc. but decreased speed is the price of that.

Usuaully it doesn’t matter but when there are lots of operations on byte.Buffer, even small differences add up.

2. Re-using buffers is another common optimization trick in Go.

The original API was:

compressed := smaz.Compress(source)

Compress function has no option but to allocate a new buffer for the compressed data every time. Allocations are not free and they slow down the program by making garbage collector do more work.

Other compression libraries allow the caller to provide a buffer for the result:

compressed := make([]byte, 1024)
compressed = smaz.Encode(compressed, source)

If the buffer is not big enough, it’ll be enlarged. If the caller doesn’t want additional complexity of managing reusable buffers, it can pass nil.

3. Avoid un-necessary copies

Compression and decompression improves reading data from memory, transforming it and writing the result to another memory location.

Memory operations are expensive. You can execute 7 CPU instructions for one memory operation in L2 cache.

I noticed that compression was making unnecessary temporary copies of data. The code got a bit more complicated but also 1.14x faster.

A digression on benchmarking tools in Go

One of the features that distinguish Go from other programming language implemenations is that out-of-the-box it comes with tooling for testing, profiling and benchmarking.

Writing benchmarks is straightforward. Here’s a benchmark for compression speed:

func BenchmarkCompression(b *testing.B) {
    inputs, n := loadTestData(b)
    var dst []byte
    for i := 0; i < b.N; i++ {
        for _, input := range inputs {
            dst = Encode(dst, input)

You run the benchmarks with go test -bench=.. You can benchmark only selected function thanks to -bench argument (or pass . to run all of them).

Go minimizes amount of work the programmer needs to do in several ways:

  • benchmarking functions are automatically recognized by convention: a function that starts with Benchmark in *_test.go file is a benchmark function
  • the results are in a standardized, human-readable form
  • benchmarking tool not only measures time but you can also get MB/s metric by using testing.B.SetBytes(), which is a better way to think about and compare code like compression algorithms.

Finally, Go comes with a tool that makes it easy to compare speed before and after the change:

> go get -u golang.org/x/tools/cmd/benchcmp
> go test -bench=. >before.txt
> ... make the changes
> go test -bench=. >after.txt
> benchcmp before.txt after.txt