Libmorton v0.2.7

Libmorton is a C++ header-only library with methods to efficiently encode/decode 64, 32 and 16-bit Morton codes and coordinates, in 2D and 3D. Morton order is also known as Z-order or the Z-order curve.
Libmorton is a lightweight and portable library - the only dependencies are standard C++ headers. Architecture-specific optimizations are available.
More info and some benchmarks in these blogposts: Morton encoding, Libmorton and BMI2 instruction set

Usage

Include libmorton/morton.h. This will always have stub functions that point to the most efficient way to encode/decode Morton codes. If you want to test out alternative (and possibly slower) methods, you can find them in libmorton/morton2D.h and libmorton/morton3D.h. All libmorton functionality is in the libmorton namespace to avoid conflicts.

// ENCODING 2D / 3D morton codes, of length 32 and 64 bits
inline uint_fast32_t morton2D_32_encode(const uint_fast16_t x, const uint_fast16_t y);
inline uint_fast64_t morton2D_64_encode(const uint_fast32_t x, const uint_fast32_t y);
inline uint_fast32_t morton3D_32_encode(const uint_fast16_t x, const uint_fast16_t y, const uint_fast16_t z);
inline uint_fast64_t morton3D_64_encode(const uint_fast32_t x, const uint_fast32_t y, const uint_fast32_t z);
// DECODING 2D / 3D morton codes, of length 32 and 64 bits
inline void morton2D_32_decode(const uint_fast32_t morton, uint_fast16_t& x, uint_fast16_t& y);
inline void morton2D_64_decode(const uint_fast64_t morton, uint_fast32_t& x, uint_fast32_t& y);
inline void morton3D_32_decode(const uint_fast32_t morton, uint_fast16_t& x, uint_fast16_t& y, uint_fast16_t& z);
inline void morton3D_64_decode(const uint_fast64_t morton, uint_fast32_t& x, uint_fast32_t& y, uint_fast32_t& z);

Installation

No installation is required (just download the headers and include them), but I was informed libmorton is packaged for Microsoft's VCPKG system as well, if you want a more controlled environment to install C++ packages in.

Instruction sets

In the standard case, libmorton only uses operations that are supported on pretty much any CPU you can throw it at. If you know you're compiling for a specific architecture, you might gain a speed boost in encoding/decoding operations by enabling implementations for a specific instruction set. Libmorton ships with support for:

BMI2 instruction set: Intel: Haswell CPU's and newer. AMD: Ryzen CPU's and newer. Define __BMI2__ before including morton.h. This is definitely a faster method when compared to the standard case.
AVX512 instruction set (experimental): Intel Ice Lake CPU's and newer. Uses _mm512_bitshuffle_epi64_mask. Define __AVX512BITALG__ before including morton.h. For more info on performance, see this PR.

When using MSVC, these options can be found under Project Properties -> Code Generation -> Enable Enhanced Instruction set. When using GCC (version 9.0 or higher), you can use -march=haswell (or -march=znver2) for BMI2 support and -march=icelake-client for AVX512 support.

Testing

The test folder contains tools I use to test correctness and performance of the libmorton implementation. You can regard them as unit tests. This section is under heavy re-writing, but might contain some useful code for advanced usage.

You can build the test suite:

With the included Visual Studio 2019 project in test\msvc*
Using make: test\makefile
Using Cmake (thanks @shohirose)

Citation

If you use libmorton in your published paper or work, please reference it, for example as follows:

@Misc{libmorton18,
author = "Jeroen Baert",
title = "Libmorton: C++ Morton Encoding/Decoding Library",
howpublished = "\url{https://github.com/Forceflow/libmorton}",
year = "2018"}

Publications / products that use libmorton

I'm always curious what libmorton ends up on. If you end up using it, send me an e-mail!

Thomas Bläsius, Tobias Friedrich et al, 2019. Efficiently Generating Geometric Inhomogeneous and Hyperbolic Random Graphs (link)
Alexander Dieckmann, Reinhard Klein, 2018. Hierarchical additive poisson disk sampling (link)
Sylvain Rousseau and Tamy Boubekeur, 2017. Fast lossy compression of 3D unit vector sets (PDF)
Jan Watter, 2018. Generation of complex numerical meshes using space-filling curves (PDF)
Esri
Cesium Ion
CLAIRE

Thanks / See ALso

To @gnzlbg and his Rust implementation bitwise for finding bugs in the Magicbits code
@kevinhartman made a C++14 library that supports N-dimensional morton codes morton-nd. He upstreamed a lot of fixes back to libmorton - thanks!
Everyone making comments and suggestions on the original blogpost
@Wunkolo for AVX512 implementation
Fabian Giesen's post on Morton Codes

Contributing

See Contributing.md

TODO

Add morton operations like described here
Write better test suite (with L1/L2 trashing, better tests, ...)
A better naming system for the functions, because m3D_e_sLUT_shifted? That escalated quickly.

itcastpygit/libmorton