Go library providing algorithms that use the full power of modern CPUs to get the best performance.

The cloud makes it easier than ever to access large scale compute capacity, and it's become common to run distributed systems deployed across dozens or sometimes hundreds of CPUs. Because projects run on so many cores now, program performance and efficiency matters more today than it has ever before.

Modern CPUs are complex machines with performance characteristics that may vary by orders of magnitude depending on how they are used. Features like branch prediction, instruction reordering, pipelining, or caching are all input variables that determine the compute throughput that a CPU can achieve. While compilers keep being improved, and often employ micro-optimizations that would be counter-productive for human developers to be responsible for, there are limitations to what they can do, and Assembly still has a role to play in optimizing algorithms on hot code paths of large scale applications.

SIMD instruction sets offer interesting opportunities for software engineers. Taking advantage of these instructions often requires rethinking how the program represents and manipulates data, which is beyond the realm of optimizations that can be implemented by a compiler. When renting CPU time from a Cloud provider, programs that fail to leverage the full sets of instructions available are therefore paying for features they do not use.

This package aims to provide such algorithms, optimized to leverage advanced instruction sets of modern CPUs to maximize throughput and take the best advantage of the available compute power. Users of the package will find functions that have often been designed to work on arrays of values, which is where SIMD and branchless algorithms shine.

The functions in this library have been used in high throughput production environments at Segment, we hope that they will be useful to other developers using Go in performance-sensitive software.

The library is composed of multiple Go packages intended to act as logical groups of functions sharing similar properties:

When no assembly version of a function is available for the target platform, the package provides a generic implementation in Go which is automatically picked up by the compiler.

The purpose of this library being to improve the runtime efficiency of Go programs, we compiled a few snapshots of benchmark runs to showcase the kind of improvements that these code paths can expect from leveraging SIMD and branchless optimizations:

goos: darwin
goarch: amd64
cpu: Intel(R) Core(TM) i9-8950HK CPU @ 2.90GHz

pkg: github.com/segmentio/asm/ascii
name                  old time/op    new time/op     delta
EqualFoldString/0512     276ns ± 1%       21ns ± 2%    -92.50%  (p=0.008 n=5+5)

name                  old speed      new speed       delta
EqualFoldString/0512  3.71GB/s ± 1%  49.44GB/s ± 2%  +1232.79%  (p=0.008 n=5+5)

pkg: github.com/segmentio/asm/bswap
name    old time/op    new time/op     delta
Swap64    11.2µs ± 1%      0.9µs ± 9%    -92.06%  (p=0.008 n=5+5)

name    old speed      new speed       delta
Swap64  5.83GB/s ± 1%  73.67GB/s ± 9%  +1162.98%  (p=0.008 n=5+5)

pkg: github.com/segmentio/asm/qsort
name            old time/op    new time/op     delta
Sort16/1000000     269ms ± 2%       46ms ± 3%   -83.08%  (p=0.008 n=5+5)

name            old speed      new speed       delta
Sort16/1000000  59.4MB/s ± 2%  351.2MB/s ± 3%  +491.24%  (p=0.008 n=5+5)

The assembly code is generated with AVO, and orchestrated by a Makefile which helps maintainers rebuild the assembly source code when the AVO files are modified.

The repository contains two Go modules; the main module is declared as github.com/segmentio/asm at the root of the repository, and the second module is found in the build subdirectory.

The build module is used to isolate build dependencies from programs that import the main module. Through this mechanism, AVO does not become a dependency of programs using github.com/segmentio/asm, keeping the dependency management overhead minimal for the users, and allowing maintainers to make modifications to the build package.

Versioning of the two modules is managed independently; while we aim to provide stable APIs on the main package, breaking changes may be introduced on the build package more often, as it is intended to be ground for more experimental constructs in the project.

Some libraries have custom purpose code for both amd64 and arm64. Others (qsort) have only amd64. Search for a .s file matching your architecture to be sure you are using the assembler optimized library instructions.

The Go code requires Go 1.17 or above. These versions contain significant performance improvements compared to previous Go versions.

asm version v1.1.5 and earlier maintain compatibility with Go 1.16.

Programs in the build module should add the following declaration:

func init() {
	ConstraintExpr("!purego")
}

It instructs AVO to inject the !purego tag in the generated files, allowing the libraries to be compiled without any assembly optimizations with a build command such as:

go build -tags purego ...

This is mainly useful to compare the impact of using the assembly optimized versions instead of the simpler Go-only implementations.