mirror of https://github.com/VLSIDA/OpenRAM.git
Fixed costs and view grid function so that we have better routes and less expansion.
This commit is contained in:
Matt Guthaus
parent
55ed6212a1
commit
96f1eb413e
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@ -11,36 +11,24 @@ class cell:
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self.blocked = False
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self.source = False
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self.target = False
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# -1 means it isn't visited yet
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self.min_cost = -1
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def get_color(self):
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r=g=b=0
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count=0
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# Blues are horizontal
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def get_type(self):
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if self.blocked:
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[r1,g1,b1] = ImageColor.getrgb("Green")
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r+=r1
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g+=g1
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b+=b1
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count+=1
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return "X"
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if self.source or self.target:
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[r1,g1,b1] = ImageColor.getrgb("Red")
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r+=r1
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g+=g1
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b+=b1
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count+=1
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if self.source:
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return "S"
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if self.target:
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return "T"
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if self.path:
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[r1,g1,b1] = ImageColor.getrgb("Blue")
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r+=r1
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g+=g1
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b+=b1
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count+=1
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if count>0:
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return [int(r/count),int(g/count),int(b/count)]
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else:
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return [255,255,255]
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return "P"
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# We can display the cost of the frontier
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if self.min_cost > 0:
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return str(self.min_cost)
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return "."
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@ -1,10 +1,11 @@
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import numpy as np
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from PIL import Image
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import string
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from itertools import tee
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import debug
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from vector3d import vector3d
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from cell import cell
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import os
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try:
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import Queue as Q # ver. < 3.0
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except ImportError:
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@ -19,81 +20,172 @@ class grid:
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def __init__(self):
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""" Create a routing map of width x height cells and 2 in the z-axis. """
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self.NONPREFERRED_COST = 5
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self.VIA_COST = 3
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# costs are relative to a unit grid
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# non-preferred cost allows an off-direction jog of 1 grid
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# rather than 2 vias + preferred direction (cost 5)
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self.VIA_COST = 2
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self.NONPREFERRED_COST = 4
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# list of the source/target grid coordinates
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self.source = []
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self.target = []
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self.blocked = []
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# let's leave the map sparse, cells are created on demand
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# let's leave the map sparse, cells are created on demand to reduce memory
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self.map={}
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# priority queue for the maze routing
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self.q = Q.PriorityQueue()
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def reinit(self):
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""" Reinitialize everything for a new route. """
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# def view(self,filename="test.png"):
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# """
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# View the data by creating an RGB array and mapping the data
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# structure to the RGB color palette.
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# """
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self.convert_path_to_blockages()
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# v_map = np.zeros((self.width,self.height,3), 'uint8')
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# mid_map = np.ones((10,self.height,3), 'uint8')
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# h_map = np.ones((self.width,self.height,3), 'uint8')
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self.convert_pins_to_blockages()
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# # We shouldn't have a path greater than 50% the HPWL
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# # so scale all visited indices by this value for colorization
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# for x in range(self.width):
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# for y in range(self.height):
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# h_map[x,y] = self.map[vector3d(x,y,0)].get_color()
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# v_map[x,y] = self.map[vector3d(x,y,1)].get_color()
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# # This is just for scale
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# if x==0 and y==0:
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# h_map[x,y] = [0,0,0]
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# v_map[x,y] = [0,0,0]
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# clear source and target pins
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self.source=[]
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self.target=[]
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# v_img = Image.fromarray(v_map, 'RGB').rotate(90)
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# #v_img.show()
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# mid_img = Image.fromarray(mid_map, 'RGB').rotate(90)
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# h_img = Image.fromarray(h_map, 'RGB').rotate(90)
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# #h_img.show()
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# clear the queue
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while (not self.q.empty()):
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self.q.get(False)
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# # concatenate them into a plot with the two layers
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# img = Image.new('RGB', (2*self.width+10, self.height))
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# img.paste(h_img, (0,0))
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# img.paste(mid_img, (self.width,0))
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# img.paste(v_img, (self.width+10,0))
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# #img.show()
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# img.save(filename)
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def view(self):
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"""
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View the data as text array.
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"""
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#os.system('clear')
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def set_property(self,ll,ur,z,name,value=True):
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xmin=-10
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xmax=25
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ymin=-10
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ymax=25
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for v in self.map.keys():
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xmin = min(xmin,v.x)
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xmax = max(xmax,v.x)
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ymin = min(ymin,v.y)
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ymax = max(ymax,v.y)
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xoffset=0
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if xmin < 0:
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xoffset=xmin
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yoffset=0
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if ymin < 0:
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yoffset=ymin
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v_map = {}
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h_map = {}
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fieldwidth = 3
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for h in self.map.keys():
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fieldwidth = max(fieldwidth,len(self.map[h].get_type()))
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for v in self.map.keys():
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fieldwidth = max(fieldwidth,len(self.map[v].get_type()))
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# for x in range(width):
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# for y in range(height):
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# v_map[x,y]="."
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# h_map[x,y]="."
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# h = vector3d(x+xoffset,y+yoffset,0)
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# v = vector3d(x+xoffset,y+yoffset,1)
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# if (h in self.map.keys()):
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# h_map[x,y] = self.map[h].get_type()
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# fieldwidth = max(fieldwidth,len(h_map[x,y]))
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# if (v in self.map.keys()):
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# v_map[x,y] = self.map[v].get_type()
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# fieldwidth = max(fieldwidth,len(v_map[x,y]))
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# display lower layer
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print '='*80
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print '='*80
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self.printgrid(0,xmin,xmax,ymin,ymax,fieldwidth)
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print '='*80
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self.printgrid(1,xmin,xmax,ymin,ymax,fieldwidth)
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print '='*80
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print '='*80
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raw_input("Press Enter to continue...")
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def printgrid(self,layer,xmin,xmax,ymin,ymax,fieldwidth):
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"""
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Display a text representation of a layer of the routing grid.
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"""
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print "".center(fieldwidth),
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for x in range(xmin,xmax+1):
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print str(x).center(fieldwidth),
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print ""
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for y in reversed(range(ymin,ymax+1)):
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print str(y).center(fieldwidth),
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for x in range(xmin,xmax+1):
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n = vector3d(x,y,layer)
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if n in self.map.keys():
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print self.map[n].get_type().center(fieldwidth),
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else:
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print ".".center(fieldwidth),
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print ""
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def add_blockage(self,ll,ur,z):
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debug.info(3,"Adding blockage ll={0} ur={1} z={2}".format(str(ll),str(ur),z))
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for x in range(int(ll[0]),int(ur[0])+1):
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for y in range(int(ll[1]),int(ur[1])+1):
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n = vector3d(x,y,z)
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self.add_map(n)
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setattr (self.map[n], name, True)
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if n not in getattr(self, name):
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getattr(self, name).append(n)
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self.map[n].blocked=True
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def add_blockage(self,ll,ur,z):
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debug.info(3,"Adding blockage ll={0} ur={1} z={2}".format(str(ll),str(ur),z))
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self.set_property(ll,ur,z,"blocked")
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def set_source(self,ll,ur,z):
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debug.info(1,"Adding source ll={0} ur={1} z={2}".format(str(ll),str(ur),z))
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self.set_property(ll,ur,z,"source")
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for x in range(int(ll[0]),int(ur[0])+1):
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for y in range(int(ll[1]),int(ur[1])+1):
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n = vector3d(x,y,z)
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self.add_map(n)
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self.map[n].source=True
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# Can't have a blocked target otherwise it's infeasible
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self.map[n].blocked=False
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self.source.append(n)
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def set_target(self,ll,ur,z):
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debug.info(1,"Adding target ll={0} ur={1} z={2}".format(str(ll),str(ur),z))
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self.set_property(ll,ur,z,"target")
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for x in range(int(ll[0]),int(ur[0])+1):
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for y in range(int(ll[1]),int(ur[1])+1):
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n = vector3d(x,y,z)
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self.add_map(n)
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self.map[n].target=True
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# Can't have a blocked target otherwise it's infeasible
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self.map[n].blocked=False
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self.target.append(n)
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def convert_pins_to_blockages(self):
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"""
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Convert all the pins to blockages and reset the pin sets.
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"""
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for p in self.map.values():
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if (p.source or p.target):
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p.blocked=True
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def convert_path_to_blockages(self):
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"""
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Convert the routed path to blockages and reset the path.
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"""
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for p in self.map.values():
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if (p.path):
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p.path=False
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p.blocked=True
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def set_path(self,path):
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"""
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Mark the path in the routing grid for visualization
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"""
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self.path=path
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for p in path:
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self.map[p].path=True
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@ -105,7 +197,7 @@ class grid:
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# We set a cost bound of 2.5 x the HPWL for run-time. This can be
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# over-ridden if the route fails due to pruning a feasible solution.
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if (cost_bound==0):
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cost_bound = 2.5*self.cost_to_target(self.source[0])
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cost_bound = self.cost_to_target(self.source[0])*self.NONPREFERRED_COST
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# Make sure the queue is empty if we run another route
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while not self.q.empty():
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@ -119,7 +211,8 @@ class grid:
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# Keep expanding and adding to the priority queue until we are done
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while not self.q.empty():
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(cost,path) = self.q.get()
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debug.info(2,"Expanding: cost=" + str(cost) + " " + str(path))
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debug.info(2,"Queue size: size=" + str(self.q.qsize()) + " " + str(cost))
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debug.info(3,"Expanding: cost=" + str(cost) + " " + str(path))
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# expand the last element
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neighbors = self.expand_dirs(path)
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@ -129,17 +222,25 @@ class grid:
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newpath = path + [n]
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if n not in self.map.keys():
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self.map[n]=cell()
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self.map[n].visited=True
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# check if we hit the target and are done
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if self.is_target(n):
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return (newpath,self.cost(newpath))
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else:
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# potential path cost + predicted cost
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cost = self.cost(newpath) + self.cost_to_target(n)
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elif not self.map[n].visited:
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# current path cost + predicted cost
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current_cost = self.cost(newpath)
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target_cost = self.cost_to_target(n)
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predicted_cost = current_cost + target_cost
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# only add the cost if it is less than our bound
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if (cost < cost_bound):
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self.q.put((cost,newpath))
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if (predicted_cost < cost_bound):
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if (self.map[n].min_cost==-1 or current_cost<self.map[n].min_cost):
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self.map[n].visited=True
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self.map[n].min_path = newpath
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self.map[n].min_cost = predicted_cost
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debug.info(3,"Enqueuing: cost=" + str(current_cost) + "+" + str(target_cost) + " " + str(newpath))
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# add the cost to get to this point if we haven't reached it yet
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self.q.put((predicted_cost,newpath))
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#self.view()
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debug.error("Unable to route path. Expand area?",-1)
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@ -209,29 +310,46 @@ class grid:
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Cost so far will be the length of the path.
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"""
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debug.info(4,"Initializing queue.")
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# uniquify the source (and target while we are at it)
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self.source = list(set(self.source))
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self.target = list(set(self.target))
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for s in self.source:
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cost = self.cost_to_target(s)
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debug.info(4,"Init: cost=" + str(cost) + " " + str([s]))
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self.q.put((cost,[s]))
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def hpwl(self, src, dest):
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"""
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Return half perimeter wire length from point to another.
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Either point can have positive or negative coordinates.
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Include the via penalty if there is one.
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"""
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hpwl = max(abs(src.x-dest.x),abs(dest.x-src.x))
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hpwl += max(abs(src.y-dest.y),abs(dest.y-src.y))
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hpwl += max(abs(src.z-dest.z),abs(dest.z-src.z))
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if src.x!=dest.x or src.y!=dest.y:
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hpwl += self.VIA_COST
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return hpwl
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def cost_to_target(self,source):
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"""
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Find the cheapest HPWL distance to any target point
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Find the cheapest HPWL distance to any target point ignoring
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blockages for A* search.
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"""
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cost = source.hpwl(self.target[0])
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cost = self.hpwl(source,self.target[0])
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for t in self.target:
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cost = min(source.hpwl(t),cost)
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cost = min(self.hpwl(source,t),cost)
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return cost
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def cost(self,path):
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"""
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The cost of the path is the length plus a penalty for the number
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of vias.
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We assume that non-preferred direction is penalized 2x.
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of vias. We assume that non-preferred direction is penalized.
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"""
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# Ignore the source pin layer change, FIXME?
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def pairwise(iterable):
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"s -> (s0,s1), (s1,s2), (s2, s3), ..."
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@ -239,6 +357,7 @@ class grid:
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next(b, None)
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return zip(a, b)
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plist = pairwise(path)
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cost = 0
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for p0,p1 in plist:
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@ -118,6 +118,7 @@ class router:
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for layer in self.layers:
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self.write_obstacle(self.top_name)
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def clear_pins(self):
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"""
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Reset the source and destination pins to start a new routing.
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@ -126,8 +127,13 @@ class router:
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Clear other pins from blockages?
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"""
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self.source = []
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self.dest = []
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self.pin_names = []
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self.pin_shapes = {}
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self.pin_layers = {}
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self.all_pin_shapes = []
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self.rg.reinit()
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def route(self, layers, src, dest):
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@ -136,7 +142,11 @@ class router:
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the simplified rectilinear path.
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"""
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# Clear the pins if we have previously routed
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self.clear_pins()
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if (hasattr(self,'rg')):
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self.num=self.num+1
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self.clear_pins()
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else:
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self.num=0
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# Set up layers and track sizes
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self.set_layers(layers)
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@ -152,15 +162,15 @@ class router:
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self.find_blockages()
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#self.rg.view("preroute.png")
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self.rg.view()
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# returns the path in tracks
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(self.path,cost) = self.rg.route()
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debug.info(1,"Found path: cost={0} ".format(cost))
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debug.info(2,str(self.path))
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self.set_path(self.path)
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self.rg.view()
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#self.rg.view("postroute.png")
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return
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def add_route(self,cell):
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@ -197,6 +207,7 @@ class router:
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c=contact(self.layers, (1, 1))
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via_offset = vector(-0.5*c.width,-0.5*c.height)
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cell.add_via(self.layers,abs_path[0]+via_offset)
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# Check if a via is needed at the end point
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if (contracted_path[-1].z!=self.target_pin_layer):
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# offset this by 1/2 the via size
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@ -55,14 +55,15 @@ class two_nets_test(unittest.TestCase):
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layer_stack =("metal1","via1","metal2")
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r.route(layer_stack,src="A",dest="B")
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||||
r.add_route(self)
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||||
#self.gds_write("temp1.gds")
|
||||
|
||||
#r.route(layer_stack,src="C",dest="D")
|
||||
#r.add_route(self)
|
||||
r.route(layer_stack,src="C",dest="D")
|
||||
r.add_route(self)
|
||||
#self.gds_write("temp2.gds")
|
||||
|
||||
|
||||
|
||||
r = routing("test1", "05_two_nets_test")
|
||||
r.gds_write("temp.gds")
|
||||
self.local_check(r)
|
||||
|
||||
# fails if there are any DRC errors on any cells
|
||||
|
|
|
|||
|
|
@ -136,10 +136,3 @@ class vector3d():
|
|||
""" Min of both values """
|
||||
return vector3d(min(self.x,other.x),min(self.y,other.y),min(self.z,other.z))
|
||||
|
||||
def hpwl(self, other):
|
||||
""" Return half perimeter wire length from point to another.
|
||||
Either point can have positive or negative coordinates. """
|
||||
hpwl = max(abs(self.x-other.x),abs(other.x-self.x))
|
||||
hpwl += max(abs(self.y-other.y),abs(other.y-self.y))
|
||||
hpwl += max(abs(self.z-other.z),abs(other.z-self.z))
|
||||
return hpwl
|
||||
|
|
|
|||
Loading…
Reference in New Issue