peclet-morton

A small, header-only C++17 library for Morton (Z-order) codes whose distinguishing feature is arithmetic directly in Morton space.

Most Morton libraries only encode (interleave coordinates into a code) and decode (the inverse). This one adds the operations you actually want when you navigate a Z-ordered grid:

• increment / decrement / add along a single axis,
• find a neighbour,
• step to the next or previous cell in Z-order,
• sweep an axis-aligned region,

…all without the usual decode → modify → re-encode round trip. Each is a handful of branchless integer instructions.

#include "morton/morton.hpp"
using morton::Morton;

Morton<2, 32> m = Morton<2, 32>::encode(x, y);  // interleave (PDEP)
m.inc(0);          // x += 1, in place, leaving y's interleaved bits untouched
m.add(1, 10);      // y += 10
auto n = m.neighbor(0, -1);   // the cell at (x-1, y+10)
auto [xx, yy] = m.decode();   // back to coordinates (PEXT)

Why this is faster

Holding a Morton code and needing a neighbour is extremely common: stencils, finite-difference sweeps, octree/quadtree traversal, ray marching, spatial hashing. The conventional approach decodes to coordinates, changes one, and re-encodes. This library mutates the relevant axis' bits in place.

Measured on this machine (Intel x86-64 with BMI2, g++ 14, -O3), 2D 32-bit:

Encode/decode are at parity with libmorton (both use the hardware PDEP/PEXT instructions). The win is in the arithmetic operations, which libmorton and similar libraries do not provide.

Honest caveat (from profiling): for a dense, contiguous full-region sweep, simply re-encoding each (x, y) from scratch is actually faster than the arithmetic walk, because independent encodes pipeline while the arithmetic walk has a loop-carried dependency. The arithmetic advantage is for scattered / data-dependent neighbour access, where you already hold a code and cannot batch. See docs/EVALUATION.md.

Design

• Header-only, C++17, no dependencies. #include "morton/morton.hpp".
• Morton<Dim, Bits> interleaves Dim coordinates of Bits bits each; the code is stored in the smallest unsigned integer that fits. Dim * Bits ≤ 64 uses a built-in integer; 65–128 bits use __uint128_t where available, so 3D 32-bit (Morton3D32, 96-bit) and 2D 64-bit (Morton2D64, 128-bit) work too.
• Encode/decode use BMI2 PDEP/PEXT when compiled with -mbmi2, with a portable software fallback otherwise. Both paths are tested for agreement.
• constexpr: the software path runs at compile time (selected via __builtin_is_constant_evaluated()), so you can build lookup tables in constexpr.
• Arithmetic wraps modulo 2^Bits per axis (branchless); add_sat/sub_sat/ try_add/try_sub clamp or refuse instead of wrapping.

Headers

Convenience aliases: Morton2D32, Morton2D16, Morton3D21, Morton3D16, Morton3D32, Morton2D64. Codes wider than 128 bits (up to MORTON_MAX_BITS, default 256) work too, e.g. Morton<3,64> (192-bit), Morton<2,128> (256-bit).

GPU (Kokkos)

A portable Kokkos backend lives in include/morton/kokkos.hpp (morton::kokkos). Because the core marks its functions with MORTON_HD (which defers to KOKKOS_FUNCTION), the device kernels run the same Morton<Dim,Bits> code as the CPU — no separate implementation — on any Kokkos backend (CUDA / HIP / OpenMP / Serial); the backend and architecture come from the Kokkos build, not the source. It offers Kokkos::View-based bulk ops (encode2/3, decode2/3, per-axis add/sub/step) plus *_host raw-pointer convenience wrappers. On an RTX 5080 (CUDA backend), 2D-32 encode hits ~51,000 Mops/s when data is resident on the GPU (~33× one CPU core); a one-shot call on host data is PCIe-transfer-bound and no faster than the CPU, so the GPU pays off only when codes live on-device across a pipeline. Opt in with -DMORTON_ENABLE_KOKKOS=ON (see DEVELOPMENT.md).

Build, test, benchmark

Full per-platform setup (incl. Python wheels and the GPU build) is in DEVELOPMENT.md. Quick start:

cmake -S . -B build -DCMAKE_BUILD_TYPE=Release
cmake --build build -j
ctest --test-dir build --output-on-failure   # or: ./build/tests/morton_tests
./build/benchmarks/morton_bench

As a header-only dependency in another CMake project — either vendored:

add_subdirectory(morton)          # this repo, e.g. as a submodule
target_link_libraries(your_target PRIVATE morton::morton)

…or installed and found via find_package (an install exports a CMake package config; Conan recipe in conanfile.py, vcpkg port in packaging/vcpkg/morton/):

find_package(morton CONFIG REQUIRED)
target_link_libraries(your_target PRIVATE morton::morton)

The test suite cross-checks every encode/decode against both a bit-by-bit reference and libmorton, validates all arithmetic exhaustively on small grids and against decode/modify/encode on large random inputs, and validates the region iterators against brute force (>1M assertions).

Python

A vectorised NumPy interface (pure ctypes, no pybind11/native build deps beyond a C++ compiler), published on PyPI as peclet-morton and imported as peclet.morton (part of the peclet suite namespace). Install as a wheel with scikit-build-core:

pip install .            # builds the extension and bundles it into the wheel
python -m pytest bindings/python/tests -q

import numpy as np, peclet.morton as ma
x = np.arange(1000, dtype=np.uint32); y = x * 2
codes = ma.encode(x, y, bits=32)
shifted = ma.shift(codes, axis=0, delta=+1, dims=2, bits=32)  # +1 in x, no decode
print(ma.decode(shifted, dims=2, bits=32))

For a quick dev loop without installing, drop the .so next to the package and use PYTHONPATH:

cmake --build build --target peclet_morton_c
PYTHONPATH=bindings/python python3 -m pytest bindings/python/tests -q

Every call runs over whole arrays in compiled code. The arithmetic shift is ~3× faster than decode+encode in Python too (see bindings/python/bench_python.py).

Repository layout

include/morton/      the library: morton.hpp, iterate.hpp, batch.hpp, simd.hpp,
                     wide_uint.hpp, kokkos.hpp (portable GPU backend)
tests/               doctest suite (encode/decode, arithmetic, constexpr, wide,
                     neighbours, batch, iterate)
benchmarks/          C++ micro-benchmarks (vs libmorton) + batch/SIMD benchmark
bindings/            morton_c.h + morton_c.cpp: the C ABI (libpeclet_morton_c);
                     python/: the ctypes + NumPy wrapper and its pytest tests
pyproject.toml       scikit-build-core wheel build + cibuildwheel config
conanfile.py         Conan recipe;  packaging/vcpkg/  vcpkg port
cmake/               CMake package-config template (find_package(morton))
.github/workflows/   ci.yml (build matrix) + release.yml (PyPI wheels on tag)
docs/                EVALUATION.md, ROADMAP.md, HILBERT_GPU_NOTES.md, Doxyfile
third_party/         vendored doctest and libmorton (tests/benchmarks only)

The project's original prototype (an arbitrary-width BitArray, a wide-code Morton, and an octree built on it) is no longer in the tree; it is reachable at the pre-legacy-removal git tag.

License

MIT — see LICENSE.