DBM

Section can be repeated.

Benchmark and test the dbm routines [Edit on GitHub]

Keywords

ALPHA
ALWAYS_CHECKSUM
ASPARSITY
BETA
BSPARSITY
BS_K
BS_M
BS_N
CSPARSITY
FILTER_EPS
K
KEEPSPARSE
M
N
N_LOOP
TRANSA
TRANSB

Keyword descriptions

ALPHA: real = 1.00000000E+000 

Usage: ALPHA 2.0

Multiplication factor [Edit on GitHub]

ALWAYS_CHECKSUM: logical = F 

Lone keyword: T

Usage: ALWAYS_CHECKSUM

perform a checksum after each multiplication [Edit on GitHub]

ASPARSITY: real = 0.00000000E+000 

Usage: ASPARSITY 70

Sparsity of A matrix [Edit on GitHub]

BETA: real = 0.00000000E+000 

Usage: BETA 1.0

Product premultiplication factor [Edit on GitHub]

BSPARSITY: real = 0.00000000E+000 

Usage: ASPARSITY 80

Sparsity of B matrix [Edit on GitHub]

BS_K: integer = 1 13 2 15 

Usage: BS_K 1 13 2 5

Block sizes of inner dimension [Edit on GitHub]

BS_M: integer = 1 13 2 15 

Usage: BS_M 1 13 2 5

Row block sizes of C [Edit on GitHub]

BS_N: integer = 1 13 2 15 

Usage: BS_N 1 13 2 5

Column block sizes of C [Edit on GitHub]

CSPARSITY: real = 0.00000000E+000 

Usage: ASPARSITY 90

Sparsity of C matrix [Edit on GitHub]

FILTER_EPS: real = -1.00000000E+000 

Usage: FILTER_EPS 1.0

Threshold for on-the-fly and final filtering. [Edit on GitHub]

K: integer = 256 

Usage: A 1024

Inner dimension M [Edit on GitHub]

KEEPSPARSE: logical = F 

Lone keyword: T

Usage: KEEPSPARSE

Keep product sparse [Edit on GitHub]

M: integer = 256 

Usage: A 1024

Dimension 1 of C [Edit on GitHub]

N: integer = 256 

Usage: A 1024

Dimension 2 of C [Edit on GitHub]

N_LOOP: integer = 10 

Usage: N_LOOP 10

Number of operations being timed (useful for small matrices). [Edit on GitHub]

TRANSA: logical = F 

Lone keyword: T

Usage: TRANSA

Transpose matrix A [Edit on GitHub]

TRANSB: logical = F 

Lone keyword: T

Usage: TRANSB

Transpose matrix B [Edit on GitHub]