LSST Applications 29.1.1,g0fba68d861+94d977d4f8,g1fd858c14a+0a42b1a450,g21d47ad084+bae5d1592d,g35bb328faa+fcb1d3bbc8,g36ff55ed5b+4036fd6440,g4e0f332c67+abab7ee1ee,g53246c7159+fcb1d3bbc8,g60b5630c4e+4036fd6440,g67b6fd64d1+31de10a2f7,g72a202582f+7a25662ef1,g78460c75b0+2f9a1b4bcd,g786e29fd12+cf7ec2a62a,g86c591e316+1a75853d69,g8852436030+8220ab3cb6,g88f4e072da+7005418d1d,g89139ef638+31de10a2f7,g8b8da53e10+8f7b08dc1c,g9125e01d80+fcb1d3bbc8,g989de1cb63+31de10a2f7,g9f1445be69+4036fd6440,g9f33ca652e+fcef3ba435,ga9baa6287d+4036fd6440,ga9e4eb89a6+a41a34c2ba,gabe3b4be73+1e0a283bba,gb0b61e0e8e+d456af7c26,gb1101e3267+f17a9d70ea,gb58c049af0+f03b321e39,gb89ab40317+31de10a2f7,gce29eb0867+05ed69485a,gcf25f946ba+8220ab3cb6,gd6cbbdb0b4+11317e7a17,gd9a9a58781+fcb1d3bbc8,gde0f65d7ad+b4f50ea554,ge278dab8ac+50e2446c94,ge410e46f29+31de10a2f7,ge80e9994a3+32bb9bc1c9,gf5e32f922b+fcb1d3bbc8,gf67bdafdda+31de10a2f7
LSST Data Management Base Package
|
This file contains functions for space-filling curves. More...
#include <cstdint>
#include <tuple>
Go to the source code of this file.
Namespaces | |
namespace | lsst |
namespace | lsst::sphgeom |
Functions | |
std::uint64_t | lsst::sphgeom::mortonIndex (std::uint32_t x, std::uint32_t y) |
mortonIndex interleaves the bits of x and y. | |
std::tuple< std::uint32_t, std::uint32_t > | lsst::sphgeom::mortonIndexInverse (std::uint64_t z) |
mortonIndexInverse separates the even and odd bits of z. | |
std::uint64_t | lsst::sphgeom::mortonToHilbert (std::uint64_t z, int m) |
mortonToHilbert converts the 2m-bit Morton index z to the corresponding Hilbert index. | |
std::uint64_t | lsst::sphgeom::hilbertToMorton (std::uint64_t h, int m) |
hilbertToMorton converts the 2m-bit Hilbert index h to the corresponding Morton index. | |
std::uint64_t | lsst::sphgeom::hilbertIndex (std::uint32_t x, std::uint32_t y, int m) |
hilbertIndex returns the index of (x, y) in a 2-D Hilbert curve. | |
std::tuple< std::uint32_t, std::uint32_t > | lsst::sphgeom::hilbertIndexInverse (std::uint64_t h, int m) |
hilbertIndexInverse returns the point (x, y) with Hilbert index h, where x and y are m bit integers. | |
std::uint8_t | lsst::sphgeom::log2 (std::uint64_t x) |
std::uint8_t | lsst::sphgeom::log2 (std::uint32_t x) |
This file contains functions for space-filling curves.
Mappings between 2-D points with non-negative integer coordinates and their corresponding Morton or Hilbert indexes are provided.
The Morton order implementation, mortonIndex, is straightforward. The Hilbert order implementation is derived from Algorithm 2 in:
C. Hamilton. Compact Hilbert indices. Technical Report CS-2006-07, Dalhousie University, Faculty of Computer Science, Jul 2006. https://www.cs.dal.ca/research/techreports/cs-2006-07
Using the variable names from that paper, n is fixed at 2. As a first step, the arithmetic in the loop over the bits of the input coordinates is replaced by a table lookup. In particular, the lookup maps the values of (e, d, l) at the beginning of a loop iteration to the values (e, d, w) at the end. Since e and d can both be represented by a single bit, and l and w are 2 bits wide, the lookup table has 16 4 bit entries and fits in a single 64 bit integer constant (0x8d3ec79a6b5021f4). The implementation then looks like:
inline std::uint64_t hilbertIndex(std::uint32_t x, std::uint32_t y, std::uint32_t m) { std::uint64_t const z = mortonIndex(x, y); std::uint64_t h = 0; std::uint64_t i = 0; for (m = 2 * m; m != 0;) { m -= 2; i = (i & 0xc) | ((z >> m) & 3); i = UINT64_C(0x8d3ec79a6b5021f4) >> (i * 4); h = (h << 2) | (i & 3); } return h; }
Note that interleaving x and y with mortonIndex beforehand allows the loop to extract 2 bits at a time from z, rather than extracting bits from x and y and then pasting them together. This lowers the total operation count.
Performance is further increased by executing j loop iterations at a time. This requires using a larger lookup table that maps the values of e and d at the beginning of a loop iteration, along with 2j input bits, to the values of e and d after j iterations, along with 2j output bits. In this implementation, j = 3, which corresponds to a 256 byte LUT. On recent Intel CPUs the LUT fits in 4 cache lines, and, because of adjacent cache line prefetch, should become cache resident after just 2 misses.
For a helpful presentation of the technical report, as well as a reference implementation of its algorithms in Python, see Pierre de Buyl's notebook. The Hilbert curve lookup tables below were generated by a modification of that code (available in makeHilbertLuts.py).
Definition in file curve.h.