.manhattan_distance_matrix_gpu_batch

Uses 3D tensors: repeat s1 along dim2, repeat s2 along dim1,
then sub -&gt; abs -&gt; sum_rows.
Result shape is (1, N1, N2) which gives the N1 x N2 distance matrix.

internal

Implements algorithms for analyzing Cayley graphs of permutation groups,
with a focus on the TopSpin puzzle and similar permutation-based combinatorial
puzzles. Provides methods for cycle detection, state space exploration,
bidirectional BFS pathfinding, and finding optimal operation sequences
in permutation groups generated by shift and reverse operations.
Includes C++ implementations of core operations via 'Rcpp' for performance.
Optional GPU acceleration via 'ggmlR' Vulkan backend for batch distance
calculations and parallel state transformations.

Yuri Baramykov

cayleyR

Cayley Graph Analysis for Permutation Puzzles

.manhattan_distance_matrix_gpu_batch function

<dl><dt>states1</dt>
<dd>Numeric matrix (N1 x n)</dd>
<dt>states2</dt>
<dd>Numeric matrix (N2 x n)</dd></dl>

Arguments

Single-batch GPU pairwise Manhattan distance — .manhattan_distance_matrix_gpu_batch

<dl>

<dt>states1</dt>
<dd>Numeric matrix (N1 x n)</dd>


<dt>states2</dt>
<dd>Numeric matrix (N2 x n)</dd>

</dl>

.manhattan_distance_matrix_gpu_batch: Single-batch GPU pairwise Manhattan distance

Description

Usage

Value

Arguments