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diff --git a/thirdparty/thekla_atlas/nvmath/Sparse.h b/thirdparty/thekla_atlas/nvmath/Sparse.h
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-// This code is in the public domain -- castanyo@yahoo.es
-
-#pragma once
-#ifndef NV_MATH_SPARSE_H
-#define NV_MATH_SPARSE_H
-
-#include "nvmath.h"
-#include "nvcore/Array.h"
-
-
-// Full and sparse vector and matrix classes. BLAS subset.
-
-namespace nv
-{
- class FullVector;
- class FullMatrix;
- class SparseMatrix;
-
-
- /// Fixed size vector class.
- class FullVector
- {
- public:
-
- FullVector(uint dim);
- FullVector(const FullVector & v);
-
- const FullVector & operator=(const FullVector & v);
-
- uint dimension() const { return m_array.count(); }
-
- const float & operator[]( uint index ) const { return m_array[index]; }
- float & operator[] ( uint index ) { return m_array[index]; }
-
- void fill(float f);
-
- void operator+= (const FullVector & v);
- void operator-= (const FullVector & v);
- void operator*= (const FullVector & v);
-
- void operator+= (float f);
- void operator-= (float f);
- void operator*= (float f);
-
-
- private:
-
- Array<float> m_array;
-
- };
-
- // Pseudo-BLAS interface.
- NVMATH_API void saxpy(float a, const FullVector & x, FullVector & y); // y = a * x + y
- NVMATH_API void copy(const FullVector & x, FullVector & y);
- NVMATH_API void scal(float a, FullVector & x);
- NVMATH_API float dot(const FullVector & x, const FullVector & y);
-
-
- enum Transpose
- {
- NoTransposed = 0,
- Transposed = 1
- };
-
- /// Full matrix class.
- class FullMatrix
- {
- public:
-
- FullMatrix(uint d);
- FullMatrix(uint w, uint h);
- FullMatrix(const FullMatrix & m);
-
- const FullMatrix & operator=(const FullMatrix & m);
-
- uint width() const { return m_width; }
- uint height() const { return m_height; }
- bool isSquare() const { return m_width == m_height; }
-
- float getCoefficient(uint x, uint y) const;
-
- void setCoefficient(uint x, uint y, float f);
- void addCoefficient(uint x, uint y, float f);
- void mulCoefficient(uint x, uint y, float f);
-
- float dotRow(uint y, const FullVector & v) const;
- void madRow(uint y, float alpha, FullVector & v) const;
-
- protected:
-
- bool isValid() const {
- return m_array.size() == (m_width * m_height);
- }
-
- private:
-
- const uint m_width;
- const uint m_height;
- Array<float> m_array;
-
- };
-
- NVMATH_API void mult(const FullMatrix & M, const FullVector & x, FullVector & y);
- NVMATH_API void mult(Transpose TM, const FullMatrix & M, const FullVector & x, FullVector & y);
-
- // y = alpha*A*x + beta*y
- NVMATH_API void sgemv(float alpha, const FullMatrix & A, const FullVector & x, float beta, FullVector & y);
- NVMATH_API void sgemv(float alpha, Transpose TA, const FullMatrix & A, const FullVector & x, float beta, FullVector & y);
-
- NVMATH_API void mult(const FullMatrix & A, const FullMatrix & B, FullMatrix & C);
- NVMATH_API void mult(Transpose TA, const FullMatrix & A, Transpose TB, const FullMatrix & B, FullMatrix & C);
-
- // C = alpha*A*B + beta*C
- NVMATH_API void sgemm(float alpha, const FullMatrix & A, const FullMatrix & B, float beta, FullMatrix & C);
- NVMATH_API void sgemm(float alpha, Transpose TA, const FullMatrix & A, Transpose TB, const FullMatrix & B, float beta, FullMatrix & C);
-
-
- /**
- * Sparse matrix class. The matrix is assumed to be sparse and to have
- * very few non-zero elements, for this reason it's stored in indexed
- * format. To multiply column vectors efficiently, the matrix stores
- * the elements in indexed-column order, there is a list of indexed
- * elements for each row of the matrix. As with the FullVector the
- * dimension of the matrix is constant.
- **/
- class SparseMatrix
- {
- friend class FullMatrix;
- public:
-
- // An element of the sparse array.
- struct Coefficient {
- uint x; // column
- float v; // value
- };
-
-
- public:
-
- SparseMatrix(uint d);
- SparseMatrix(uint w, uint h);
- SparseMatrix(const SparseMatrix & m);
-
- const SparseMatrix & operator=(const SparseMatrix & m);
-
-
- uint width() const { return m_width; }
- uint height() const { return m_array.count(); }
- bool isSquare() const { return width() == height(); }
-
- float getCoefficient(uint x, uint y) const; // x is column, y is row
-
- void setCoefficient(uint x, uint y, float f);
- void addCoefficient(uint x, uint y, float f);
- void mulCoefficient(uint x, uint y, float f);
-
- float sumRow(uint y) const;
- float dotRow(uint y, const FullVector & v) const;
- void madRow(uint y, float alpha, FullVector & v) const;
-
- void clearRow(uint y);
- void scaleRow(uint y, float f);
- void normalizeRow(uint y);
-
- void clearColumn(uint x);
- void scaleColumn(uint x, float f);
-
- const Array<Coefficient> & getRow(uint y) const;
-
- bool isSymmetric() const;
-
- private:
-
- /// Number of columns.
- const uint m_width;
-
- /// Array of matrix elements.
- Array< Array<Coefficient> > m_array;
-
- };
-
- NVMATH_API void transpose(const SparseMatrix & A, SparseMatrix & B);
-
- NVMATH_API void mult(const SparseMatrix & M, const FullVector & x, FullVector & y);
- NVMATH_API void mult(Transpose TM, const SparseMatrix & M, const FullVector & x, FullVector & y);
-
- // y = alpha*A*x + beta*y
- NVMATH_API void sgemv(float alpha, const SparseMatrix & A, const FullVector & x, float beta, FullVector & y);
- NVMATH_API void sgemv(float alpha, Transpose TA, const SparseMatrix & A, const FullVector & x, float beta, FullVector & y);
-
- NVMATH_API void mult(const SparseMatrix & A, const SparseMatrix & B, SparseMatrix & C);
- NVMATH_API void mult(Transpose TA, const SparseMatrix & A, Transpose TB, const SparseMatrix & B, SparseMatrix & C);
-
- // C = alpha*A*B + beta*C
- NVMATH_API void sgemm(float alpha, const SparseMatrix & A, const SparseMatrix & B, float beta, SparseMatrix & C);
- NVMATH_API void sgemm(float alpha, Transpose TA, const SparseMatrix & A, Transpose TB, const SparseMatrix & B, float beta, SparseMatrix & C);
-
- // C = At * A
- NVMATH_API void sqm(const SparseMatrix & A, SparseMatrix & C);
-
-} // nv namespace
-
-
-#endif // NV_MATH_SPARSE_H
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