//----------------------------------------------------------------------- // ----------------------------------------------------------------------- // file="MatrixCompute.Factorize" // Project: StgSharp // AuthorGroup: Nitload // Copyright (c) Nitload. All rights reserved. // // Permission is hereby granted, free of charge, to any person obtaining a copy // of this software and associated documentation files (the "Software"), to deal // in the Software without restriction, including without limitation the rights // to use, copy, modify, merge, publish, distribute, sublicense, and/or sell // copies of the Software, and to permit persons to whom the Software is // furnished to do so, subject to the following conditions: // // The above copyright notice and this permission notice shall be included in all // copies or substantial portions of the Software. // // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR // IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, // FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE // AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER // LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, // OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE // SOFTWARE. // // ----------------------------------------------------------------------- // ----------------------------------------------------------------------- using StgSharp.Internal; using System; using System.Collections.Generic; using System.Linq; using System.Text; using System.Threading.Tasks; namespace StgSharp.Mathematics.Numeric { public static partial class MatrixCompute { public static unsafe void FactorizePLU( Matrix matrix, Span pivot, Matrix lower, Matrix upper ) { if (matrix.ColumnLength != matrix.RowLength) { throw new InvalidOperationException("Matrix must be square."); } if (matrix.Layout != MatrixLayout.DenseRectangle) { throw new NotSupportedException("Only dense square matrices are supported."); } int n = matrix.RowLength; if (pivot.Length < n) { throw new ArgumentException("Pivot span length is insufficient.", nameof(pivot)); } if (lower.RowLength != n || lower.ColumnLength != n || lower.Layout != MatrixLayout.UpperTriangle) { throw new ArgumentException("Lower matrix must be lower-triangular with same dimensions as input.", nameof(lower)); } if (upper.RowLength != n || upper.ColumnLength != n || upper.Layout != MatrixLayout.UpperTriangle) { throw new ArgumentException("Upper matrix must be upper-triangular with same dimensions as input.", nameof(upper)); } int size = matrix.KernelColumnLength * matrix.KernelRowLength; if (size < 256) { for (int i = 0; i < n; i++) { pivot[i] = i; // identity permutation } // Aggressive: always call native pivot to fetch four-column candidates ulong* pivots = stackalloc ulong[4]; for (int kBlock = 0; kBlock < n; kBlock += 4) { NumericalModule.GlobalContext .mat_sk[(int)MatrixElementType.F32].pivot(matrix.Buffer, (ulong)(kBlock >> 2), (ulong)(matrix.KernelRowLength - (kBlock >> 2)), (ulong)pivots); int colsInBlock = Math.Min(4, n - kBlock); for (int offset = 0; offset < colsInBlock; offset++) { int k = kBlock + offset; int pivotRow = k; float maxAbs; int candidateRow = (int)pivots[offset]; int idx = -1; for (int r = k; r < n; r++) { if (pivot[r] == candidateRow) { idx = r; break; } } if (idx != -1) { pivotRow = idx; maxAbs = MathF.Abs(matrix.GetElementUnsafe(pivot[idx], k)); } else { maxAbs = MathF.Abs(matrix.GetElementUnsafe(pivot[k], k)); for (int r = k + 1; r < n; r++) { float val = MathF.Abs(matrix.GetElementUnsafe(pivot[r], k)); if (val > maxAbs) { maxAbs = val; pivotRow = r; } } } if (maxAbs == 0f) { throw new InvalidOperationException("Zero pivot encountered in PLU."); } if (pivotRow != k) { (pivot[k], pivot[pivotRow]) = (pivot[pivotRow], pivot[k]); } lower[k, k] = 1.0f; // unit diagonal for L // Compute U[k, j] for j >= k for (int j = k; j < n; j++) { float sum = 0f; for (int s = 0; s < k; s++) { sum += lower[k, s] * upper[s, j]; } upper[k, j] = matrix.GetElementUnsafe(pivot[k], j) - sum; } // Compute L[i, k] for i > k for (int i = k + 1; i < n; i++) { float sum = 0f; for (int s = 0; s < k; s++) { sum += lower[i, s] * upper[s, k]; } float u = upper[k, k]; if (u == 0f) { throw new InvalidOperationException("Zero pivot encountered in PLU."); } lower[i, k] = (matrix.GetElementUnsafe(pivot[i], k) - sum) / u; } } } // TODO: For larger kernels, consider calling native pivot helper to extract 4 pivots at once. } else if (size < 1024) { } else { } } } }