import os
import time
import shutil
import sys
sys.path.append('./utils')
sys.path.append('../../FormatTranslators/src')
from math import sqrt
from FormatTranslators import Port
from FormatTranslators import Macro
from FormatTranslators import MacroPin
class Clustering:
def __init__(self, design, src_dir, fixed_file, step_threshold = 100.6, distance = 1000.0,
max_num_vertices = 1000000, net_size_threshold = 300,
Nparts = 500, setup_file = "setup.tcl", RePlace = True, placement_density = 0.7, GUI = True):
"""
parameter: design, help="design_name: ariane, MegaBoom_x2 ", type = str
parameter: src_dir, help="directory for source codes", type = str
parameter: fixed_file, help="fixed file generated by grouping", type = str
parameter: step_threshold, help = "threshold (x and y) to break clusters (in um)", type = float
parameter: distance, help="distance for merge clusters", type = float
parameter: max_num_vertices, help="threshold for smaller clusters", type = int
parameter: net_size_threshold, help="large net threshold", type = int
parameter: Nparts, help = "number of clusters (only for hmetis, default = 500)", type = int
parameter: setup_file, help = "setup file for openroad (default = setup.tcl)", type = str
parameter: RePlace, help = "Run RePlace for blob placement (default = True)", type = bool
parameter: placement_density, help = "Placement density for RePlace (default = 0.7)", type = float
parameter: GUI, help = "Run OpenROAD in GUI Mode (default = True)", type = bool
"""
# initialize parameters
self.design = design
self.src_dir = src_dir
self.fixed_file = fixed_file
self.step_threshold = step_threshold
self.distance = distance
self.max_num_vertices = max_num_vertices
self.net_size_threshold = net_size_threshold
self.Nparts = Nparts
self.setup_file = setup_file
self.RePlace = RePlace
self.placement_density = placement_density
self.GUI = GUI
### Print Information
print("[INFO] step_threshold : ", self.step_threshold)
print("[INFO] distance : ", self.distance)
print("[INFO] max_num_vertices : ", self.max_num_vertices)
# Specify the location of hmetis exe and openroad exe and other utilities
self.hmetis_exe = src_dir + "/utils/hmetis"
self.openroad_exe = src_dir + "/utils/openroad"
self.extract_hypergraph_file = src_dir + "/utils/extract_hypergraph.tcl"
self.create_clustered_netlist_def_file = src_dir + "/utils/create_clustered_netlist_def.tcl"
# set up temp report directory
rpt_dir = os.getcwd() + "/rtl_mp"
self.hypergraph_file = rpt_dir + "/" + design + ".hgr"
# the io_name_file includes the io location
self.io_name_file = self.hypergraph_file + ".io"
# the instance_name_file includes name, is_macro, bounding box of the instance
self.instance_name_file = self.hypergraph_file + ".instance"
self.hypergraph_fix_file = self.hypergraph_file + ".fix"
self.macro_pin_file = self.hypergraph_file + ".macro_pin"
self.outline_file = self.hypergraph_file + ".outline"
self.net_file = self.hypergraph_file + ".net"
# set up result directories
result_dir = "./results"
if not os.path.exists(result_dir):
os.mkdir(result_dir)
pbf_result_dir = result_dir + "/Protocol_buffer_format"
if not os.path.exists(pbf_result_dir):
os.mkdir(pbf_result_dir)
cadence_result_dir = result_dir + "/Cadence"
if not os.path.exists(cadence_result_dir):
os.mkdir(cadence_result_dir)
openroad_result_dir = result_dir + "/OpenROAD"
if not os.path.exists(openroad_result_dir):
os.mkdir(openroad_result_dir)
# for protocol buffer format
self.pbf_file = pbf_result_dir + "/" + self.design + ".pb.txt"
# for innovus command
self.cluster_file = cadence_result_dir + "/" + self.design
self.cluster_file += "_cluster_" + str(self.Nparts) + ".tcl"
self.solution_file = self.hypergraph_file + ".part." + str(self.Nparts) # defined by hemtis automatically
self.cluster_lef_file = openroad_result_dir + "/clusters.lef"
self.cluster_def_file = openroad_result_dir + "/clustered_netlist.def"
self.blob_def_file = openroad_result_dir + "/blob.def"
# netlist information
self.vertex_map = { } # instance_name, vertex_id
self.vertex_list = [ ] # instance_name (io_name)
self.nets = [] # nets
self.is_io_macro_list = [ ] # is io / macro (True or False)
self.num_ios = 0
self.vertex_pos = [ ] # bounding box of instances
self.solution_vector = [] # solution vector, cluster_id for each vertex
self.max_cluster_id = -1
self.vertices_in_cluster = { } # vertices in each cluster
self.cluster_pos = { } # store the coordinates of each cluster
self.soft_macros = [ ] # list of the std cell instances in each soft macro
###############################################################################
### Functions
###############################################################################
self.GenerateHypergraph() # Extract netlist information from lef/def/v
self.RemoveLargetNet() # Remove large nets
self.ConvertFixFile() # Convert fixed file
self.hMetisPartitioner() # Partition the hypergraph
self.BreakClusters() # Break clusters spreading apart
print("[INFO] After finishing BreakClusters(), ", end = "")
print("num_clusters = ", len(self.vertices_in_cluster))
self.MergeSmallClusters() # Merge small clusters with its neighbors
print("[INFO] After finishing MergeSmallClusters(), ", end = "")
self.GenerateSoftMacros()
ProBufFormat(self.io_name_file, self.macro_pin_file, \
self.instance_name_file, self.outline_file, \
self.net_file, self.soft_macros, \
self.pbf_file, self.net_size_threshold, 1.0)
self.CreateInvsCluster() # Generate Innovus Clustering Commands
self.CreateDef() # Generate clustered lef and def file
if (self.RePlace == True):
self.RunRePlace() # Generate blob placemment
shutil.rmtree(rpt_dir)
def GenerateHypergraph(self):
# Extract hypergraph from netlist
temp_file = os.getcwd() + "/extract_hypergraph.tcl"
cmd = "cp " + self.setup_file + " " + temp_file
os.system(cmd)
with open(self.extract_hypergraph_file) as f:
content = f.read().splitlines()
f.close()
f = open(temp_file, "a")
f.write("\n")
for line in content:
f.write(line + "\n")
f.close()
cmd = self.openroad_exe + " " + temp_file
os.system(cmd)
cmd = "rm " + temp_file
os.system(cmd)
# read io and instance information
vertex_id = 0
with open(self.io_name_file) as f:
content = f.read().splitlines()
f.close()
for line in content:
items = line.split()
io_name = items[0]
lx = float(items[1])
ly = float(items[2])
ux = float(items[3])
uy = float(items[4])
self.vertex_map[io_name] = vertex_id
self.vertex_list.append(io_name)
self.is_io_macro_list.append(True)
self.vertex_pos.append([lx, ly, ux, uy])
vertex_id += 1
self.num_ios = vertex_id
with open(self.instance_name_file) as f:
content = f.read().splitlines()
f.close()
for line in content:
items = line.split()
instance_name = items[0]
is_macro = int(items[1]) > 0
lx = float(items[2])
ly = float(items[3])
ux = float(items[4])
uy = float(items[5])
self.vertex_map[instance_name] = vertex_id
self.vertex_list.append(instance_name)
self.is_io_macro_list.append(is_macro)
self.vertex_pos.append([lx, ly, ux, uy])
vertex_id += 1
def RemoveLargetNet(self):
# Remove large nets from the hypergraph
with open(self.hypergraph_file) as f:
content = f.read().splitlines()
f.close()
items = content[0].split()
num_hyperedges = int(items[0])
num_vertices = int(items[1])
# update the net
hyperedges_list = []
for i in range(1, len(content)):
items = content[i].split()
if (len(items) < self.net_size_threshold):
hyperedges_list.append(content[i])
net = [int(item) - 1 for item in items]
self.nets.append(net)
f = open(self.hypergraph_file, "w")
line = str(len(hyperedges_list)) + " " + str(num_vertices) + "\n"
f.write(line)
for hyperedge in hyperedges_list:
f.write(hyperedge + "\n")
f.close()
def ConvertFixFile(self):
# Convert the grouping information to fix file which can used by hMetis
fixed_part = [-1 for i in range(len(self.vertex_list))]
with open(self.fixed_file) as f:
content = f.read().splitlines()
f.close()
# read the grouping information
for i in range(len(content)):
# i is the group_id
vertices = content[i].split(',')
for vertex in vertices:
fixed_part[self.vertex_map[vertex]] = i
f = open(self.hypergraph_fix_file, "w")
for part in fixed_part:
f.write(str(part) + "\n")
f.close()
def hMetisPartitioner(self):
# Partitioning the hypergraph using hmetis
# The parameter configuration is the same as Google Brain paper
# UBfactor = 5
# Nruns = 10
# CType = 5
# RType = 3
# Vcycle = 3
# The random seed is 0 by default (in our implementation)
# We use the hMetis C++ API to implement hMetis
cmd = self.hmetis_exe + " " + self.hypergraph_file + " " + self.hypergraph_fix_file + " "
cmd += str(self.Nparts) + " 5 10 5 3 3 0 0"
os.system(cmd)
# read solution vector
with open(self.solution_file) as f:
content = f.read().splitlines()
f.close()
for line in content:
self.solution_vector.append(int(line))
self.max_cluster_id = max(self.solution_vector)
# update vertices_in_cluster
for i in range(self.max_cluster_id + 1):
self.vertices_in_cluster[i] = []
for i in range(len(self.solution_vector)):
self.vertices_in_cluster[self.solution_vector[i]].append(i)
def GetBoundingBox(self, vertices_in_cluster):
# get the bounding box of the cluster
# initialization
cluster_lx = 1e20
cluster_ly = 1e20
cluster_ux = 0.0
cluster_uy = 0.0
for vertex in vertices_in_cluster:
if (self.is_io_macro_list[vertex] == False):
box = self.vertex_pos[vertex]
cluster_lx = min(cluster_lx, box[0])
cluster_ly = min(cluster_ly, box[1])
cluster_ux = max(cluster_ux, box[2])
cluster_uy = max(cluster_uy, box[3])
return cluster_lx, cluster_ly, cluster_ux, cluster_uy
def BreakLargeCluster(self, cluster_id):
# For a cluster with bounding box (lx, ly, ux, uy)
# if (ux - lx) > threshold or (uy - ly) > threshold, break the cluster
# When breaking the cluster, we set the use the center of cluster as the
# origin and threshold as step size to grid the bounding box
# All the instances in each grid cell (in terms of the center of the instance) forms a new cluster
cluster_lx, cluster_ly, cluster_ux, cluster_uy = self.GetBoundingBox(self.vertices_in_cluster[cluster_id])
if (((cluster_ux - cluster_lx) <= self.step_threshold)
and ((cluster_uy - cluster_ly) <= self.step_threshold)):
return None
cluster_x = (cluster_lx + cluster_ux) / 2.0
cluster_y = (cluster_ly + cluster_uy) / 2.0
num_x_grid = int((cluster_ux - cluster_x) / self.step_threshold)
num_y_grid = int((cluster_uy - cluster_y) / self.step_threshold)
temp_vertices_in_cluster = { }
for i in range((-1) * num_x_grid, num_x_grid + 1):
temp_vertices_in_cluster[i] = { }
for j in range((-1) * num_y_grid, num_y_grid + 1):
temp_vertices_in_cluster[i][j] = [ ]
for vertex in self.vertices_in_cluster[cluster_id]:
lx, ly, ux, uy = self.vertex_pos[vertex]
x = (lx + ux) / 2.0
y = (ly + uy) / 2.0
x_grid = int((x - cluster_x) / self.step_threshold)
y_grid = int((y - cluster_y) / self.step_threshold)
temp_vertices_in_cluster[i][j].append(vertex)
# update the solution vector and vertices_in_cluster
for x_grid, values in temp_vertices_in_cluster.items():
for y_grid, vertices in values.items():
# ignore the original cluster
if (((x_grid == 0) and (y_grid == 0)) or (len(vertices) == 0)):
pass
else:
self.max_cluster_id += 1
self.vertices_in_cluster[self.max_cluster_id] = [ ]
for vertex in vertices:
self.vertices_in_cluster[self.max_cluster_id].append(vertex)
self.solution_vector[vertex] = self.max_cluster_id
def BreakClusters(self):
# In this step, we break clusters which spread around the canvas.
clusters = list(self.vertices_in_cluster.keys())
for cluster in clusters:
self.BreakLargeCluster(cluster)
def IsNearNeighbor(self, cluster, neighbor):
dist = abs(self.cluster_pos[cluster][0] - self.cluster_pos[neighbor][0])
dist += abs(self.cluster_pos[cluster][1] - self.cluster_pos[neighbor][1])
if (dist <= self.distance):
return True
else:
return False
def AddClusterEdge(self, cluster_a, cluster_b):
if cluster_b not in self.cluster_adj[cluster_a]:
self.cluster_adj[cluster_a][cluster_b] = 1
else:
self.cluster_adj[cluster_a][cluster_b] += 1
def MergeSmallClusters(self):
# Merge small clusters to the most adjacent clusters
# within its neighbors (in terms of Manhattan distance)
#num_clusters = len(self.vertices_in_cluster)
while(True):
# check if there are possible clusters to be merged
#if (len(self.vertices_in_cluster) == num_clusters):
# return None
# merge small clusters
num_clusters = len(self.vertices_in_cluster)
small_clusters = []
self.cluster_pos = { }
self.cluster_adj = { }
for cluster_id, vertices in self.vertices_in_cluster.items():
cluster_lx, cluster_ly, cluster_ux, cluster_uy = self.GetBoundingBox(self.vertices_in_cluster[cluster_id])
self.cluster_pos[cluster_id] = [(cluster_ux + cluster_lx) / 2.0, (cluster_ly + cluster_uy) / 2.0]
self.cluster_adj[cluster_id] = { }
if (len(vertices) < self.max_num_vertices):
small_clusters.append(cluster_id)
# update cluster adjacency matrix
for net in self.nets:
cluster_net = []
for vertex in net:
cluster_id = self.solution_vector[vertex]
if cluster_id not in cluster_net:
cluster_net.append(cluster_id)
if (len(cluster_net) > 1):
for cluster_i in cluster_net:
for cluster_j in cluster_net:
if (cluster_i != cluster_j):
self.AddClusterEdge(cluster_i, cluster_j)
candidate_neighbors = { }
for cluster in small_clusters:
candidate_neighbors[cluster] = []
for cluster in small_clusters:
for neighbor in self.cluster_adj[cluster]:
if (self.IsNearNeighbor(cluster, neighbor) == True):
candidate_neighbors[cluster].append(neighbor)
### each time we only merge one cluster
small_cluster_id = -1
for small_cluster, neighbors in candidate_neighbors.items():
if (len(neighbors) > 0):
small_cluster_id = small_cluster
break
# No small clusters existing
if (small_cluster_id == -1):
return None
best_neighbor = -1
best_neighbor_nets = -1
for neighbor in candidate_neighbors[small_cluster_id]:
if (self.cluster_adj[small_cluster_id][neighbor] > best_neighbor_nets):
best_neighbor_nets = self.cluster_adj[small_cluster_id][neighbor]
best_neighbor = neighbor
# update solution vector
for vertex in self.vertices_in_cluster[small_cluster_id]:
self.solution_vector[vertex] = best_neighbor
self.vertices_in_cluster[best_neighbor].append(vertex)
del self.vertices_in_cluster[small_cluster_id]
def CreateInvsCluster(self):
# Create cluster commands for Innovus
f = open(self.cluster_file, "w")
line = "# This script was written and developed by ABKGroup students at UCSD.\n"
line += "# However, the underlying commands and reports are copyrighted by Cadence.\n"
line += "# We thank Cadence for granting permission to share our research to help \n"
line += "# promote and foster the next generation of innovators.\n"
line += "\n"
f.write(line)
# cluster_id starts with 0, so we have self.max_cluster_id + 1
for i in range(self.max_cluster_id + 1):
f.write("createInstGroup cluster" + str(i) + "\n")
for i in range(len(self.vertex_list)):
if (self.is_io_macro_list[i] == False):
instance_name = self.vertex_list[i]
cluster_id = self.solution_vector[i]
line = "addInstToInstGroup cluster" + str(cluster_id) + " " + instance_name + "\n"
f.write(line)
f.close()
def CreateDef(self):
# Create clustered netlist (in def format) Based on OpenROAD API
# Create the related openroad tcl file
file_name = os.getcwd() + "/create_def.tcl"
cmd = "cp " + self.setup_file + " " + file_name
os.system(cmd)
f = open(file_name, "a")
f.write("\n")
f.write("\n")
f.write("read_verilog $netlist\n")
f.write("link_design $top_design\n")
f.write("read_def $def_file -floorplan_initialize\n")
#f.write("read_def $def_file\n")
f.write("\n")
f.write("set db [ord::get_db]\n")
f.write("set block [[$db getChip] getBlock]\n")
f.write("set cluster_lef_file " + self.cluster_lef_file + "\n")
f.write("set cluster_def_file " + self.cluster_def_file + "\n")
f.write("\n")
f.write("\n")
for i in range(len(self.vertex_list)):
if (self.is_io_macro_list[i] == False):
instance_name = self.vertex_list[i]
cluster_id = self.solution_vector[i]
# fix the `\' and '[' in the names
new_instance_name = ""
for char in instance_name:
if (char == '\\') or (char == '[') or (char == ']'):
new_instance_name += '\\' + char
else:
new_instance_name += char
instance_name = new_instance_name
line = "set inst [$block findInst " + instance_name + " ]\n"
f.write(line)
f.write("set cluster_id " + str(cluster_id) + "\n")
f.write('set newProperty [odb::dbStringProperty_create $inst "cluster_id" $cluster_id]\n')
f.close()
with open(self.create_clustered_netlist_def_file) as f:
content = f.read().splitlines()
f.close()
f = open(file_name, "a")
f.write("\n")
for line in content:
f.write(line + "\n")
f.close()
cmd = self.openroad_exe + " " + file_name
os.system(cmd)
cmd = "rm " + file_name
os.system(cmd)
# Due to some bugs in OpenROAD, we have to manually remove the RESISTANCE section for all the via layers
with open(self.cluster_lef_file) as f:
content = f.read().splitlines()
f.close()
f = open(self.cluster_lef_file, "w")
i = 0
while(i < len(content)):
items = content[i].split()
if(len(items) == 2 and items[0] == "LAYER" and items[1][0:-1] == "via"):
while((len(items) == 2 and items[0] == "END") == False):
if(items[0] != "RESISTANCE"):
f.write(content[i] + "\n")
i = i + 1
items = content[i].split()
f.write(content[i] + "\n")
i = i + 1
else:
f.write(content[i] + "\n")
i = i + 1
f.close()
def RunRePlace(self):
# Run RePlace on the clustered netlist
# Create the related openroad tcl file
file_name = os.getcwd() + "/run_replace.tcl"
cmd = "cp " + self.setup_file + " " + file_name
os.system(cmd)
f = open(file_name, "a")
line = "read_lef " + self.cluster_lef_file + "\n"
line += "read_def " + self.cluster_def_file + "\n"
line += "set global_place_density " + str(self.placement_density) + "\n"
line += "set global_place_density_penalty 8e-5\n"
line += "global_placement -disable_routability_driven -density $global_place_density -init_density_penalty $global_place_density_penalty\n"
line += "write_def " + self.blob_def_file + "\n"
f.write(line)
if (self.GUI == False):
f.write("exit\n")
f.close()
cmd = self.openroad_exe + " -gui " + file_name
if (self.GUI == False):
cmd = self.openroad_exe + " " + file_name
os.system(cmd)
cmd = "rm " + file_name
os.system(cmd)
def GetNumClusters(self):
return len(self.vertices_in_cluster)
def GenerateSoftMacros(self):
for key, value in self.vertices_in_cluster.items():
soft_macro = []
for vertex_id in value:
if self.is_io_macro_list[vertex_id] == False:
soft_macro.append(self.vertex_list[vertex_id])
self.soft_macros.append(soft_macro)
# Generate Clustered Netlist in Protocol Buffer Format
class ProBufFormat:
def __init__(self, io_file, macro_pin_file, inst_file, outline_file,
net_file, soft_macros, pbf_file, net_size_threshold,
aspect_ratio):
self.io_file = io_file
self.macro_pin_file = macro_pin_file
self.inst_file = inst_file
self.outline_file = outline_file
self.net_file = net_file
self.soft_macros = soft_macros
self.pbf_file = pbf_file
self.net_size_threshold = net_size_threshold
self.aspect_ratio = aspect_ratio
self.insts = { } # map name to Port, Macro, Soft Macro
self.macro_pin_map = { } # map macro_pin to macro
self.macro_pin_offset = { } # map macro_pin_name to offset
self.std_cell_pos = { } # instance_name, bounding box
self.std_cell_map = { } # instance_name, soft macro name
self.ios = []
# circuit row information
self.fp_lx = 0.0
self.fp_ly = 0.0
self.fp_ux = 0.0
self.fp_uy = 0.0
self.ReadOutlineFile()
self.ReadIOFile()
self.ReadInstFile()
self.ReadMacroPinFile()
self.ReadNetFile()
self.Output()
# Read outline file
def ReadOutlineFile(self):
with open(self.outline_file) as f:
content = f.read().splitlines()
f.close()
items = content[0].split()
self.fp_lx = float(items[0])
self.fp_ly = float(items[1])
self.fp_ux = float(items[2])
self.fp_uy = float(items[3])
print('*'*80)
print("Outline Information")
print("[INFO] Core Size : ", self.fp_lx, self.fp_ly, self.fp_ux, self.fp_uy)
print("\n\n")
# Read IO file
def ReadIOFile(self):
with open(self.io_file) as f:
content = f.read().splitlines()
f.close()
for line in content:
items = line.split()
io_name = items[0]
lx = float(items[1])
ly = float(items[2])
ux = float(items[3])
uy = float(items[4])
side = "LEFT"
if (lx <= self.fp_lx):
side = "LEFT"
elif (ux >= self.fp_ux):
side = "RIGHT"
elif (uy >= self.fp_uy):
side = "TOP"
else:
side = "BOTTOM"
self.insts[io_name] = Port(io_name, (lx + ux) / 2.0, (ly + uy) / 2.0, side)
self.ios.append(io_name)
# Read instance file
def ReadInstFile(self):
with open(self.inst_file) as f:
content = f.read().splitlines()
f.close()
for line in content:
items = line.split()
inst_name = items[0]
block_flag = items[1]
lx = float(items[2])
ly = float(items[3])
ux = float(items[4])
uy = float(items[5])
orientation = items[6]
width = ux - lx
height = uy - ly
x = (lx + ux) / 2.0
y = (ly + uy) / 2.0
if block_flag == '1':
self.insts[inst_name] = Macro(inst_name, width, height, x, y, orientation)
else:
self.std_cell_pos[inst_name] = [lx, ly, ux, uy]
# Create Soft Macros
soft_macro_id = 0
for soft_macro in self.soft_macros:
macro_name = "Grp_" + str(soft_macro_id)
lx = 1e20
ly = 1e20
ux = 0.0
uy = 0.0
area = 0.0
for std_cell in soft_macro:
bbox = self.std_cell_pos[std_cell]
lx = min(lx, bbox[0])
ly = min(ly, bbox[1])
ux = max(ux, bbox[2])
uy = max(uy, bbox[3])
area += (bbox[2] - bbox[0]) * (bbox[3] - bbox[1])
self.std_cell_map[std_cell] = macro_name
x = (lx + ux) / 2.0
y = (ly + uy) / 2.0
height = sqrt(area * self.aspect_ratio)
width = area / height
self.insts[macro_name] = Macro(macro_name, width, height, x, y)
self.insts[macro_name].IsSoft()
soft_macro_id += 1
# Read Macro Pin file
def ReadMacroPinFile(self):
with open(self.macro_pin_file) as f:
content = f.read().splitlines()
f.close()
for line in content:
items = line.split()
pin_name = items[0] + '/' + items[1]
macro_name = items[0]
self.macro_pin_map[pin_name] = macro_name
x_offset = float(items[2])
y_offset = float(items[3])
self.macro_pin_offset[pin_name] = [x_offset, y_offset]
# Read Net file
def ReadNetFile(self):
with open(self.net_file) as f:
content = f.read().splitlines()
f.close()
adj_list = { }
for io in self.ios:
adj_list[io] = { }
for macro_pin in self.macro_pin_map.keys():
adj_list[macro_pin] = { }
for i in range(len(self.soft_macros)):
adj_list["Grp_" + str(i)] = { }
for line in content:
items = line.split()
num_pin = len(items) / 4
if (num_pin > self.net_size_threshold):
pass
else:
driver_name = items[2]
driver_pin_name = driver_name + '/' + items[0]
driver = None
if (driver_name in self.ios):
driver = driver_name
elif (driver_pin_name in self.macro_pin_offset):
driver = driver_pin_name
else:
driver = self.std_cell_map[driver_name]
sinks_name = []
for i in range(1, int(num_pin)):
inst_name = items[4 * i + 2]
pin_name = inst_name + '/' + items[4 * i]
if (inst_name in self.ios):
sinks_name.append(inst_name)
elif (pin_name in self.macro_pin_offset):
sinks_name.append(pin_name)
else:
sinks_name.append(self.std_cell_map[inst_name] + "/Input")
unique_sinks = []
for sink in sinks_name:
if sink not in unique_sinks:
unique_sinks.append(sink)
for sink in unique_sinks:
if sink not in adj_list[driver]:
adj_list[driver][sink] = 1
else:
adj_list[driver][sink] += 1
# Create Macro Pins
for io in self.ios:
self.insts[io].AddSinks(adj_list[io].keys())
for macro_pin in self.macro_pin_map.keys():
if (len(adj_list[macro_pin]) == 0):
offset = self.macro_pin_offset[macro_pin]
inst_name = self.macro_pin_map[macro_pin]
self.insts[inst_name].AddInputPin(MacroPin(macro_pin, inst_name, \
offset[0], offset[1]))
else:
offset = self.macro_pin_offset[macro_pin]
inst_name = self.macro_pin_map[macro_pin]
Pin = MacroPin(macro_pin, inst_name, offset[0], offset[1])
Pin.AddSinks(adj_list[macro_pin].keys())
self.insts[inst_name].AddOutputPin(Pin)
for i in range(len(self.soft_macros)):
# add input pin
inst_name = "Grp_" + str(i)
macro_pin = inst_name + "/Input"
self.insts[inst_name].AddInputPin(MacroPin(macro_pin, inst_name, 0.0, 0.0))
output_idx = 1
for key, weight in adj_list[inst_name].items():
macro_pin = inst_name + "/Output_" + str(output_idx)
output_idx += 1
Pin = MacroPin(macro_pin, inst_name, 0.0, 0.0)
Pin.AddSink(key)
if key not in self.ios or key not in self.macro_pin_map:
Pin.SpecifyWeight(weight)
self.insts[inst_name].AddOutputPin(Pin)
# Generate.pb.txt file
def Output(self):
f = open(self.pbf_file, "w")
for inst_name, inst in self.insts.items():
f.write(str(inst))
if (inst.GetType() == "MACRO"):
for macro_pin in inst.GetPins():
f.write(str(macro_pin))
f.close()