/*****************************************************************************
**
** MultiplyByDivideAndConquer
**
** For medium to medium-large (would you like fries with that) sized
** matrices A, B, and C of size MatrixSize * MatrixSize this function
** efficiently performs the operation
** C = A x B (if AdditiveMode == 0)
** C += A x B (if AdditiveMode != 0)
**
** Note MatrixSize must be divisible by 16.
**
** INPUT:
** C = (*C READ/WRITE) Address of top left element of matrix C.
** A = (*A IS READ ONLY) Address of top left element of matrix A.
** B = (*B IS READ ONLY) Address of top left element of matrix B.
** MatrixSize = Size of matrices (for n*n matrix, MatrixSize = n)
** RowWidthA = Number of elements in memory between A[x,y] and A[x,y+1]
** RowWidthB = Number of elements in memory between B[x,y] and B[x,y+1]
** RowWidthC = Number of elements in memory between C[x,y] and C[x,y+1]
** AdditiveMode = 0 if we want C = A x B, otherwise we'll do C += A x B
**
** OUTPUT:
** C (+)= A x B. (+ if AdditiveMode != 0)
**
*****************************************************************************/
void MultiplyByDivideAndConquer(REAL *C, REAL *A, REAL *B,
unsigned MatrixSize,
unsigned RowWidthC,
unsigned RowWidthA,
unsigned RowWidthB,
int AdditiveMode
)
{
#define A00 A
#define B00 B
#define C00 C
REAL *A01, *A10, *A11, *B01, *B10, *B11, *C01, *C10, *C11;
unsigned QuadrantSize = MatrixSize >> 1;
/* partition the matrix */
A01 = A00 + QuadrantSize;
A10 = A00 + RowWidthA * QuadrantSize;
A11 = A10 + QuadrantSize;
B01 = B00 + QuadrantSize;
B10 = B00 + RowWidthB * QuadrantSize;
B11 = B10 + QuadrantSize;
C01 = C00 + QuadrantSize;
C10 = C00 + RowWidthC * QuadrantSize;
C11 = C10 + QuadrantSize;
if (QuadrantSize > SizeAtWhichNaiveAlgorithmIsMoreEfficient) {
MultiplyByDivideAndConquer(C00, A00, B00, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB,
AdditiveMode);
MultiplyByDivideAndConquer(C01, A00, B01, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB,
AdditiveMode);
MultiplyByDivideAndConquer(C11, A10, B01, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB,
AdditiveMode);
MultiplyByDivideAndConquer(C10, A10, B00, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB,
AdditiveMode);
MultiplyByDivideAndConquer(C00, A01, B10, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB,
1);
MultiplyByDivideAndConquer(C01, A01, B11, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB,
1);
MultiplyByDivideAndConquer(C11, A11, B11, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB,
1);
MultiplyByDivideAndConquer(C10, A11, B10, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB,
1);
} else {
if (AdditiveMode) {
FastAdditiveNaiveMatrixMultiply(C00, A00, B00, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
FastAdditiveNaiveMatrixMultiply(C01, A00, B01, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
FastAdditiveNaiveMatrixMultiply(C11, A10, B01, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
FastAdditiveNaiveMatrixMultiply(C10, A10, B00, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
} else {
FastNaiveMatrixMultiply(C00, A00, B00, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
FastNaiveMatrixMultiply(C01, A00, B01, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
FastNaiveMatrixMultiply(C11, A10, B01, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
FastNaiveMatrixMultiply(C10, A10, B00, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
}
FastAdditiveNaiveMatrixMultiply(C00, A01, B10, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
FastAdditiveNaiveMatrixMultiply(C01, A01, B11, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
FastAdditiveNaiveMatrixMultiply(C11, A11, B11, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
FastAdditiveNaiveMatrixMultiply(C10, A11, B10, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
}
return;
}
/*****************************************************************************
**
** OptimizedStrassenMultiply
**
** For large matrices A, B, and C of size MatrixSize * MatrixSize this
** function performs the operation C = A x B efficiently.
**
** INPUT:
** C = (*C WRITE) Address of top left element of matrix C.
** A = (*A IS READ ONLY) Address of top left element of matrix A.
** B = (*B IS READ ONLY) Address of top left element of matrix B.
** MatrixSize = Size of matrices (for n*n matrix, MatrixSize = n)
** RowWidthA = Number of elements in memory between A[x,y] and A[x,y+1]
** RowWidthB = Number of elements in memory between B[x,y] and B[x,y+1]
** RowWidthC = Number of elements in memory between C[x,y] and C[x,y+1]
**
** OUTPUT:
** C = (*C WRITE) Matrix C contains A x B. (Initial value of *C undefined.)
**
*****************************************************************************/
VOID_TASK_7(OptimizedStrassenMultiply, REAL *, C, REAL *, A, REAL *, B,
unsigned, MatrixSize,
unsigned, RowWidthC,
unsigned, RowWidthA,
unsigned, RowWidthB
)
{
unsigned QuadrantSize = MatrixSize >> 1; /* MatixSize / 2 */
unsigned QuadrantSizeInBytes = sizeof(REAL) * QuadrantSize * QuadrantSize
+ 32;
unsigned Column, Row;
/************************************************************************
** For each matrix A, B, and C, we'll want pointers to each quandrant
** in the matrix. These quandrants will be addressed as follows:
** -- --
** | A11 A12 |
** | |
** | A21 A22 |
** -- --
************************************************************************/
REAL /* *A11, *B11, *C11, */ *A12, *B12, *C12,
*A21, *B21, *C21, *A22, *B22, *C22;
REAL *S1,*S2,*S3,*S4,*S5,*S6,*S7,*S8,*M2,*M5,*T1sMULT;
#define T2sMULT C22
#define NumberOfVariables 11
PTR TempMatrixOffset = 0;
PTR MatrixOffsetA = 0;
PTR MatrixOffsetB = 0;
char *Heap;
void *StartHeap;
/* Distance between the end of a matrix row and the start of the next row */
PTR RowIncrementA = ( RowWidthA - QuadrantSize ) << 3;
PTR RowIncrementB = ( RowWidthB - QuadrantSize ) << 3;
PTR RowIncrementC = ( RowWidthC - QuadrantSize ) << 3;
if (MatrixSize <= SizeAtWhichDivideAndConquerIsMoreEfficient) {
MultiplyByDivideAndConquer(C, A, B,
MatrixSize,
RowWidthC,
RowWidthA,
RowWidthB,
0);
return;
}
/* Initialize quandrant matrices */
#define A11 A
#define B11 B
#define C11 C
A12 = A11 + QuadrantSize;
B12 = B11 + QuadrantSize;
C12 = C11 + QuadrantSize;
A21 = A + (RowWidthA * QuadrantSize);
B21 = B + (RowWidthB * QuadrantSize);
C21 = C + (RowWidthC * QuadrantSize);
A22 = A21 + QuadrantSize;
B22 = B21 + QuadrantSize;
C22 = C21 + QuadrantSize;
/* Allocate Heap Space Here */
StartHeap = Heap = malloc(QuadrantSizeInBytes * NumberOfVariables);
/* ensure that heap is on cache boundary */
if ( ((PTR) Heap) & 31)
Heap = (char*) ( ((PTR) Heap) + 32 - ( ((PTR) Heap) & 31) );
/* Distribute the heap space over the variables */
S1 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
S2 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
S3 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
S4 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
S5 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
S6 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
S7 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
S8 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
M2 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
M5 = (REAL*) Heap; Heap += QuadrantSizeInBytes;
T1sMULT = (REAL*) Heap; Heap += QuadrantSizeInBytes;
/***************************************************************************
** Step through all columns row by row (vertically)
** (jumps in memory by RowWidth => bad locality)
** (but we want the best locality on the innermost loop)
***************************************************************************/
for (Row = 0; Row < QuadrantSize; Row++) {
/*************************************************************************
** Step through each row horizontally (addressing elements in each column)
** (jumps linearly througn memory => good locality)
*************************************************************************/
for (Column = 0; Column < QuadrantSize; Column++) {
/***********************************************************
** Within this loop, the following holds for MatrixOffset:
** MatrixOffset = (Row * RowWidth) + Column
** (note: that the unit of the offset is number of reals)
***********************************************************/
/* Element of Global Matrix, such as A, B, C */
#define E(Matrix) (* (REAL*) ( ((PTR) Matrix) + TempMatrixOffset ) )
#define EA(Matrix) (* (REAL*) ( ((PTR) Matrix) + MatrixOffsetA ) )
#define EB(Matrix) (* (REAL*) ( ((PTR) Matrix) + MatrixOffsetB ) )
/* FIXME - may pay to expand these out - got higher speed-ups below */
/* S4 = A12 - ( S2 = ( S1 = A21 + A22 ) - A11 ) */
E(S4) = EA(A12) - ( E(S2) = ( E(S1) = EA(A21) + EA(A22) ) - EA(A11) );
/* S8 = (S6 = B22 - ( S5 = B12 - B11 ) ) - B21 */
E(S8) = ( E(S6) = EB(B22) - ( E(S5) = EB(B12) - EB(B11) ) ) - EB(B21);
/* S3 = A11 - A21 */
E(S3) = EA(A11) - EA(A21);
/* S7 = B22 - B12 */
E(S7) = EB(B22) - EB(B12);
TempMatrixOffset += sizeof(REAL);
MatrixOffsetA += sizeof(REAL);
MatrixOffsetB += sizeof(REAL);
} /* end row loop*/
MatrixOffsetA += RowIncrementA;
MatrixOffsetB += RowIncrementB;
} /* end column loop */
/* M2 = A11 x B11 */
SPAWN(OptimizedStrassenMultiply, M2, A11, B11, QuadrantSize,
QuadrantSize, RowWidthA, RowWidthB);
/* M5 = S1 * S5 */
SPAWN(OptimizedStrassenMultiply, M5, S1, S5, QuadrantSize,
QuadrantSize, QuadrantSize, QuadrantSize);
/* Step 1 of T1 = S2 x S6 + M2 */
SPAWN(OptimizedStrassenMultiply, T1sMULT, S2, S6, QuadrantSize,
QuadrantSize, QuadrantSize, QuadrantSize);
/* Step 1 of T2 = T1 + S3 x S7 */
SPAWN(OptimizedStrassenMultiply, C22, S3, S7, QuadrantSize,
RowWidthC /*FIXME*/, QuadrantSize, QuadrantSize);
/* Step 1 of C11 = M2 + A12 * B21 */
SPAWN(OptimizedStrassenMultiply, C11, A12, B21, QuadrantSize,
RowWidthC, RowWidthA, RowWidthB);
/* Step 1 of C12 = S4 x B22 + T1 + M5 */
SPAWN(OptimizedStrassenMultiply, C12, S4, B22, QuadrantSize,
RowWidthC, QuadrantSize, RowWidthB);
/* Step 1 of C21 = T2 - A22 * S8 */
SPAWN(OptimizedStrassenMultiply, C21, A22, S8, QuadrantSize,
RowWidthC, RowWidthA, QuadrantSize);
/**********************************************
** Synchronization Point
**********************************************/
SYNC(OptimizedStrassenMultiply);
SYNC(OptimizedStrassenMultiply);
SYNC(OptimizedStrassenMultiply);
SYNC(OptimizedStrassenMultiply);
SYNC(OptimizedStrassenMultiply);
SYNC(OptimizedStrassenMultiply);
SYNC(OptimizedStrassenMultiply);
/***************************************************************************
** Step through all columns row by row (vertically)
** (jumps in memory by RowWidth => bad locality)
** (but we want the best locality on the innermost loop)
***************************************************************************/
for (Row = 0; Row < QuadrantSize; Row++) {
/*************************************************************************
** Step through each row horizontally (addressing elements in each column)
** (jumps linearly througn memory => good locality)
*************************************************************************/
for (Column = 0; Column < QuadrantSize; Column += 4) {
REAL LocalM5_0 = *(M5);
REAL LocalM5_1 = *(M5+1);
REAL LocalM5_2 = *(M5+2);
REAL LocalM5_3 = *(M5+3);
REAL LocalM2_0 = *(M2);
REAL LocalM2_1 = *(M2+1);
REAL LocalM2_2 = *(M2+2);
REAL LocalM2_3 = *(M2+3);
REAL T1_0 = *(T1sMULT) + LocalM2_0;
REAL T1_1 = *(T1sMULT+1) + LocalM2_1;
REAL T1_2 = *(T1sMULT+2) + LocalM2_2;
REAL T1_3 = *(T1sMULT+3) + LocalM2_3;
REAL T2_0 = *(C22) + T1_0;
REAL T2_1 = *(C22+1) + T1_1;
REAL T2_2 = *(C22+2) + T1_2;
REAL T2_3 = *(C22+3) + T1_3;
(*(C11)) += LocalM2_0;
(*(C11+1)) += LocalM2_1;
(*(C11+2)) += LocalM2_2;
(*(C11+3)) += LocalM2_3;
(*(C12)) += LocalM5_0 + T1_0;
(*(C12+1)) += LocalM5_1 + T1_1;
(*(C12+2)) += LocalM5_2 + T1_2;
(*(C12+3)) += LocalM5_3 + T1_3;
(*(C22)) = LocalM5_0 + T2_0;
(*(C22+1)) = LocalM5_1 + T2_1;
(*(C22+2)) = LocalM5_2 + T2_2;
(*(C22+3)) = LocalM5_3 + T2_3;
(*(C21 )) = (- *(C21 )) + T2_0;
(*(C21+1)) = (- *(C21+1)) + T2_1;
(*(C21+2)) = (- *(C21+2)) + T2_2;
(*(C21+3)) = (- *(C21+3)) + T2_3;
M5 += 4;
M2 += 4;
T1sMULT += 4;
C11 += 4;
C12 += 4;
C21 += 4;
C22 += 4;
}
C11 = (REAL*) ( ((PTR) C11 ) + RowIncrementC);
C12 = (REAL*) ( ((PTR) C12 ) + RowIncrementC);
C21 = (REAL*) ( ((PTR) C21 ) + RowIncrementC);
C22 = (REAL*) ( ((PTR) C22 ) + RowIncrementC);
}
free(StartHeap);
}
/*****************************************************************************
**
** OptimizedStrassenMultiply
**
** For large matrices A, B, and C of size MatrixSize * MatrixSize this
** function performs the operation C = A x B efficiently.
**
** INPUT:
** C = (*C WRITE) Address of top left element of matrix C.
** A = (*A IS READ ONLY) Address of top left element of matrix A.
** B = (*B IS READ ONLY) Address of top left element of matrix B.
** MatrixSize = Size of matrices (for n*n matrix, MatrixSize = n)
** RowWidthA = Number of elements in memory between A[x,y] and A[x,y+1]
** RowWidthB = Number of elements in memory between B[x,y] and B[x,y+1]
** RowWidthC = Number of elements in memory between C[x,y] and C[x,y+1]
**
** OUTPUT:
** C = (*C WRITE) Matrix C contains A x B. (Initial value of *C undefined.)
**
*****************************************************************************/
static void OptimizedStrassenMultiply_par(double *C, double *A, double *B,
unsigned MatrixSize, unsigned RowWidthC, unsigned RowWidthA,
unsigned RowWidthB, unsigned int Depth, unsigned int cutoff_depth,
unsigned cutoff_size)
{
unsigned QuadrantSize = MatrixSize >> 1; /* MatixSize / 2 */
unsigned QuadrantSizeInBytes = sizeof(double) * QuadrantSize * QuadrantSize;
unsigned Column, Row;
/************************************************************************
** For each matrix A, B, and C, we'll want pointers to each quandrant
** in the matrix. These quandrants will be addressed as follows:
** -- --
** | A A12 |
** | |
** | A21 A22 |
** -- --
************************************************************************/
double /* *A, *B, *C, */ *A12, *B12, *C12,
*A21, *B21, *C21, *A22, *B22, *C22;
double *S1,*S2,*S3,*S4,*S5,*S6,*S7,*S8,*M2,*M5,*T1sMULT;
#define T2sMULT C22
#define NumberOfVariables 11
char *Heap;
void *StartHeap;
if (MatrixSize <= cutoff_size) {
MultiplyByDivideAndConquer(C, A, B, MatrixSize, RowWidthC, RowWidthA, RowWidthB, 0);
return;
}
/* Initialize quandrant matrices */
A12 = A + QuadrantSize;
B12 = B + QuadrantSize;
C12 = C + QuadrantSize;
A21 = A + (RowWidthA * QuadrantSize);
B21 = B + (RowWidthB * QuadrantSize);
C21 = C + (RowWidthC * QuadrantSize);
A22 = A21 + QuadrantSize;
B22 = B21 + QuadrantSize;
C22 = C21 + QuadrantSize;
/* Allocate Heap Space Here */
StartHeap = Heap = malloc(QuadrantSizeInBytes * NumberOfVariables);
/* Distribute the heap space over the variables */
S1 = (double*) Heap; Heap += QuadrantSizeInBytes;
S2 = (double*) Heap; Heap += QuadrantSizeInBytes;
S3 = (double*) Heap; Heap += QuadrantSizeInBytes;
S4 = (double*) Heap; Heap += QuadrantSizeInBytes;
S5 = (double*) Heap; Heap += QuadrantSizeInBytes;
S6 = (double*) Heap; Heap += QuadrantSizeInBytes;
S7 = (double*) Heap; Heap += QuadrantSizeInBytes;
S8 = (double*) Heap; Heap += QuadrantSizeInBytes;
M2 = (double*) Heap; Heap += QuadrantSizeInBytes;
M5 = (double*) Heap; Heap += QuadrantSizeInBytes;
T1sMULT = (double*) Heap; Heap += QuadrantSizeInBytes;
if (Depth < cutoff_depth)
{
#pragma omp task depend(in: A21, A22) depend(out: S1) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column++)
S1[Row * QuadrantSize + Column] = A21[RowWidthA * Row + Column] + A22[RowWidthA * Row + Column];
#pragma omp task depend(in: S1, A) depend(out: S2) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column++)
S2[Row * QuadrantSize + Column] = S1[Row * QuadrantSize + Column] - A[RowWidthA * Row + Column];
#pragma omp task depend(in: A12, S2) depend(out: S4) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column++)
S4[Row * QuadrantSize + Column] = A12[Row * RowWidthA + Column] - S2[QuadrantSize * Row + Column];
#pragma omp task depend(in: B12, B) depend(out: S5) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column++)
S5[Row * QuadrantSize + Column] = B12[Row * RowWidthB + Column] - B[Row * RowWidthB + Column];
#pragma omp task depend(in: B22, S5) depend(out: S6) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column++)
S6[Row * QuadrantSize + Column] = B22[Row * RowWidthB + Column] - S5[Row * QuadrantSize + Column];
#pragma omp task depend(in: S6, B21) depend(out: S8) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column++)
S8[Row * QuadrantSize + Column] = S6[Row * QuadrantSize + Column] - B21[Row * RowWidthB + Column];
#pragma omp task depend(in: A, A21) depend(out: S3) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column++)
S3[Row * QuadrantSize + Column] = A[RowWidthA * Row + Column] - A21[RowWidthA * Row + Column];
#pragma omp task depend(in: B22, B12) depend(out: S7) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column++)
S7[Row * QuadrantSize + Column] = B22[Row * RowWidthB + Column] - B12[Row * RowWidthB + Column];
/* M2 = A x B */
#pragma omp task depend(in: A, B) depend(out: M2)
OptimizedStrassenMultiply_par(M2, A, B, QuadrantSize, QuadrantSize, RowWidthA, RowWidthB, Depth+1, cutoff_depth, cutoff_size);
/* M5 = S1 * S5 */
#pragma omp task untied depend(in: S1, S5) depend(out: M5)
OptimizedStrassenMultiply_par(M5, S1, S5, QuadrantSize, QuadrantSize, QuadrantSize, QuadrantSize, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of T1 = S2 x S6 + M2 */
#pragma omp task untied depend(in: S2, S6) depend(out: T1sMULT)
OptimizedStrassenMultiply_par(T1sMULT, S2, S6, QuadrantSize, QuadrantSize, QuadrantSize, QuadrantSize, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of T2 = T1 + S3 x S7 */
#pragma omp task untied depend(in: S3, S7) depend(out: C22)
OptimizedStrassenMultiply_par(C22, S3, S7, QuadrantSize, RowWidthC /*FIXME*/, QuadrantSize, QuadrantSize, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of C = M2 + A12 * B21 */
#pragma omp task untied depend(in: A12, B21) depend(out: C)
OptimizedStrassenMultiply_par(C, A12, B21, QuadrantSize, RowWidthC, RowWidthA, RowWidthB, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of C12 = S4 x B22 + T1 + M5 */
#pragma omp task untied depend(in: S4, B22) depend(out: C12)
OptimizedStrassenMultiply_par(C12, S4, B22, QuadrantSize, RowWidthC, QuadrantSize, RowWidthB, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of C21 = T2 - A22 * S8 */
#pragma omp task untied depend(in: A22, S8) depend(out: C21)
OptimizedStrassenMultiply_par(C21, A22, S8, QuadrantSize, RowWidthC, RowWidthA, QuadrantSize, Depth+1, cutoff_depth, cutoff_size);
#pragma omp task depend(inout: C) depend(in: M2) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column += 1)
C[RowWidthC * Row + Column] += M2[Row * QuadrantSize + Column];
#pragma omp task depend(inout: C12) depend(in: M5, T1sMULT, M2) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column += 1)
C12[RowWidthC * Row + Column] += M5[Row * QuadrantSize + Column] + T1sMULT[Row * QuadrantSize + Column] + M2[Row * QuadrantSize + Column];
#pragma omp task depend(inout: C21) depend(in: C22, T1sMULT, M2) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column += 1)
C21[RowWidthC * Row + Column] = -C21[RowWidthC * Row + Column] + C22[RowWidthC * Row + Column] + T1sMULT[Row * QuadrantSize + Column] + M2[Row * QuadrantSize + Column];
#pragma omp task depend(inout: C22) depend(in: M5, T1sMULT, M2) private(Row, Column)
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column += 1)
C22[RowWidthC * Row + Column] += M5[Row * QuadrantSize + Column] + T1sMULT[Row * QuadrantSize + Column] + M2[Row * QuadrantSize + Column];
#pragma omp taskwait
}
else
{
for (Row = 0; Row < QuadrantSize; Row++)
for (Column = 0; Column < QuadrantSize; Column++) {
S1[Row * QuadrantSize + Column] = A21[RowWidthA * Row + Column] + A22[RowWidthA * Row + Column];
S2[Row * QuadrantSize + Column] = S1[Row * QuadrantSize + Column] - A[RowWidthA * Row + Column];
S4[Row * QuadrantSize + Column] = A12[Row * RowWidthA + Column] - S2[QuadrantSize * Row + Column];
S5[Row * QuadrantSize + Column] = B12[Row * RowWidthB + Column] - B[Row * RowWidthB + Column];
S6[Row * QuadrantSize + Column] = B22[Row * RowWidthB + Column] - S5[Row * QuadrantSize + Column];
S8[Row * QuadrantSize + Column] = S6[Row * QuadrantSize + Column] - B21[Row * RowWidthB + Column];
S3[Row * QuadrantSize + Column] = A[RowWidthA * Row + Column] - A21[RowWidthA * Row + Column];
S7[Row * QuadrantSize + Column] = B22[Row * RowWidthB + Column] - B12[Row * RowWidthB + Column];
}
/* M2 = A x B */
OptimizedStrassenMultiply_par(M2, A, B, QuadrantSize, QuadrantSize, RowWidthA, RowWidthB, Depth+1, cutoff_depth, cutoff_size);
/* M5 = S1 * S5 */
OptimizedStrassenMultiply_par(M5, S1, S5, QuadrantSize, QuadrantSize, QuadrantSize, QuadrantSize, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of T1 = S2 x S6 + M2 */
OptimizedStrassenMultiply_par(T1sMULT, S2, S6, QuadrantSize, QuadrantSize, QuadrantSize, QuadrantSize, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of T2 = T1 + S3 x S7 */
OptimizedStrassenMultiply_par(C22, S3, S7, QuadrantSize, RowWidthC /*FIXME*/, QuadrantSize, QuadrantSize, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of C = M2 + A12 * B21 */
OptimizedStrassenMultiply_par(C, A12, B21, QuadrantSize, RowWidthC, RowWidthA, RowWidthB, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of C12 = S4 x B22 + T1 + M5 */
OptimizedStrassenMultiply_par(C12, S4, B22, QuadrantSize, RowWidthC, QuadrantSize, RowWidthB, Depth+1, cutoff_depth, cutoff_size);
/* Step 1 of C21 = T2 - A22 * S8 */
OptimizedStrassenMultiply_par(C21, A22, S8, QuadrantSize, RowWidthC, RowWidthA, QuadrantSize, Depth+1, cutoff_depth, cutoff_size);
for (Row = 0; Row < QuadrantSize; Row++) {
for (Column = 0; Column < QuadrantSize; Column += 1) {
C[RowWidthC * Row + Column] += M2[Row * QuadrantSize + Column];
C12[RowWidthC * Row + Column] += M5[Row * QuadrantSize + Column] + T1sMULT[Row * QuadrantSize + Column] + M2[Row * QuadrantSize + Column];
C21[RowWidthC * Row + Column] = -C21[RowWidthC * Row + Column] + C22[RowWidthC * Row + Column] + T1sMULT[Row * QuadrantSize + Column] + M2[Row * QuadrantSize + Column];
C22[RowWidthC * Row + Column] += M5[Row * QuadrantSize + Column] + T1sMULT[Row * QuadrantSize + Column] + M2[Row * QuadrantSize + Column];
}
}
}
free(StartHeap);
}
