def update_distribution(circuit: Circuit, data: Data):
"""
update the distribution for each net
"""
for net in circuit.nets:
data.reset_net_distribution(net)
for cell in net.cells:
block_id = data.get_node_block_id(cell)
data.inc_net_distribution(net, block_id)
def move_node_another_block(cell: Cell, data: Data):
"""
move the max gain node to another block
"""
F = data.get_node_block_id(cell) # from block id
T = (F + 1) % 2 # to block id
# lock the node
data.lock_node(cell, T)
for net in cell.nets:
# check critical nets before the move
if data.get_net_distribution(net, T) == 0:
for nei in net.cells:
if data.is_node_unlocked(nei):
data.update_node_gain(nei, 1)
elif data.get_net_distribution(net, T) == 1:
for nei in net.cells:
if data.is_node_unlocked(nei) and data.get_node_block_id(
nei) == T:
data.update_node_gain(nei, -1)
# change the net distribution to reflect the move
data.dec_net_distribution(net, F)
data.inc_net_distribution(net, T)
# check the critical nets after the move
if data.get_net_distribution(net, F) == 0:
for nei in net.cells:
if data.is_node_unlocked(nei):
data.update_node_gain(nei, -1)
elif data.get_net_distribution(net, F) == 1:
for nei in net.cells:
if data.is_node_unlocked(nei) and data.get_node_block_id(
nei) == F:
data.update_node_gain(nei, 1)
data.update_cutsize_by_gain(cell)