def prepare_matrices():
matrix_a = list()
matrix_b = list()
matrix_c = list()
for i in range(MATRIXSIZE):
a_row = list()
b_row = list()
c_row = list()
matrix_a.append(a_row)
matrix_b.append(b_row)
matrix_c.append(c_row)
for j in range(MATRIXSIZE):
a_block = Block()
b_block = Block()
c_block = Block()
a_row.append(a_block)
b_row.append(b_block)
c_row.append(c_block)
a_block.make_persistent()
b_block.make_persistent()
c_block.make_persistent()
a_block.initialize_random(BLOCKSIZE, BLOCKSIZE)
b_block.initialize_random(BLOCKSIZE, BLOCKSIZE)
c_block.initialize_zeros(BLOCKSIZE, BLOCKSIZE)
if INPUT_IN_NVRAM:
a_block.persist_to_nvram()
b_block.persist_to_nvram()
if EXEC_IN_NVRAM:
c_block.persist_to_nvram()
return matrix_a, matrix_b, matrix_c
def prepare_matrices():
matrix_a = list()
matrix_b = list()
matrix_c = list()
for i in range(MATRIXSIZE):
a_row = list()
b_row = list()
c_row = list()
matrix_a.append(a_row)
matrix_b.append(b_row)
matrix_c.append(c_row)
for j in range(MATRIXSIZE):
a_block = Block()
b_block = Block()
c_block = Block()
a_row.append(a_block)
b_row.append(b_block)
c_row.append(c_block)
a_block.make_persistent()
b_block.make_persistent()
c_block.make_persistent()
a_block.initialize_random(BLOCKSIZE, BLOCKSIZE)
b_block.initialize_random(BLOCKSIZE, BLOCKSIZE)
# c_block is not initialized, as the numpy matrix addition creates the structure
if INPUT_IN_NVRAM:
a_block.persist_to_nvram()
b_block.persist_to_nvram()
return matrix_a, matrix_b, matrix_c
