dgemm {bigalgebra}  R Documentation 
This is function provides dgemm functionality, which DGEMM performs one of the matrixmatrix operations. C := ALPHA * op(A) * op(B) + BETA * C.
dgemm(
TRANSA = "N",
TRANSB = "N",
M = NULL,
N = NULL,
K = NULL,
ALPHA = 1,
A,
LDA = NULL,
B,
LDB = NULL,
BETA = 0,
C,
LDC = NULL,
COFF = 0
)
TRANSA 
a character. TRANSA specifies the form of op( A ) to be used in the matrix multiplication as follows:

TRANSB 
a character. TRANSB specifies the form of op( B ) to be used in the matrix multiplication as follows: #'

M 
an integer. M specifies the number of rows of the matrix op( A ) and of the matrix C. M must be at least zero. 
N 
an integer. N specifies the number of columns of the matrix op( B ) and of the matrix C. N must be at least zero. 
K 
an integer. K specifies the number of columns of the matrix op( A ) and the number of rows of the matrix op( B ). K must be at least zero. 
ALPHA 
a real number. Specifies the scalar alpha. 
A 
a matrix of dimension (LDA, ka), where ka is k when TRANSA = 'N' or 'n', and is m otherwise. Before entry with TRANSA = 'N' or 'n', the leading m by k part of the array A must contain the matrix A, otherwise the leading k by m part of the array A must contain the matrix A. 
LDA 
an integer. 
B 
a matrix of dimension ( LDB, kb ), where kb is n when TRANSB = 'N' or 'n', and is k otherwise. Before entry with TRANSB = 'N' or 'n', the leading k by n part of the array B must contain the matrix B, otherwise the leading n by k part of the array B must contain the matrix B. 
LDB 
an integer. 
BETA 
a real number. Specifies the scalar beta 
C 
a matrix of dimension ( LDC, N ). Before entry, the leading m by n part of the array C must contain the matrix C, except when beta is zero, in which case C need not be set on entry. On exit, the array C is overwritten by the m by n matrix ( alpha*op( A )*op( B ) + beta*C ). 
LDC 
an integer. 
COFF 
offset for C. 
Update C with the result.
require(bigmemory)
A = as.big.matrix(matrix(1, nrow=3, ncol=2))
B < big.matrix(2, 3, type="double", init=1,
dimnames=list(NULL, c("alpha", "beta")), shared=FALSE)
C = big.matrix(3, 3, type="double", init=1,
dimnames=list(NULL, c("alpha", "beta", "gamma")), shared=FALSE)
2*A[,]%*%B[,]+0.5*C[,]
E = dgemm(ALPHA=2.0, A=A, B=B, BETA=0.5, C=C)
E[,] # Same result
# The big.matrix file backings will be deleted when garbage collected.
rm(A,B,C,E)
gc()