mirror of https://github.com/VLSIDA/OpenRAM.git
Change analyze_pins to a heuristic algorithm less than O(n^2)
This commit is contained in:
Matt Guthaus
parent
a96f492d0a
commit
dfb2cf3cbd
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@ -46,12 +46,13 @@ class router(router_tech):
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### The pin data structures
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# A map of pin names to a set of pin_layout structures
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# (i.e. pins with a given label)
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self.pins = {}
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# This is a set of all pins (ignoring names) so that can quickly not create blockages for pins
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# (They will be blocked based on the names we are routing)
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# (They will be blocked when we are routing other nets based on their name.)
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self.all_pins = set()
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# A map of pin names to a list of pin groups
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# The labeled pins above categorized into pin groups that are touching/connected.
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self.pin_groups = {}
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### The blockage data structures
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@ -673,37 +674,109 @@ class router(router_tech):
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def analyze_pins(self, pin_name):
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"""
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Analyze the shapes of a pin and combine them into groups which are connected.
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Analyze the shapes of a pin and combine them into pin_groups which are connected.
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"""
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debug.info(2,"Analyzing pin groups for {}.".format(pin_name))
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pin_set = self.pins[pin_name]
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# Put each pin in an equivalence class of it's own
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equiv_classes = [set([x]) for x in pin_set]
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def combine_classes(equiv_classes):
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for class1 in equiv_classes:
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for class2 in equiv_classes:
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if class1 == class2:
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continue
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# Compare each pin in each class,
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# and if any overlap, update equiv_classes to include the combined the class
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for p1 in class1:
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for p2 in class2:
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if p1.overlaps(p2):
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combined_class = class1 | class2
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equiv_classes.remove(class1)
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equiv_classes.remove(class2)
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equiv_classes.append(combined_class)
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return(equiv_classes)
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return(equiv_classes)
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# This will be a list of pin tuples that overlap
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overlap_list = []
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old_length = math.inf
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while (len(equiv_classes)<old_length):
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old_length = len(equiv_classes)
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equiv_classes = combine_classes(equiv_classes)
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# Sort the rectangles into a list with lower/upper y coordinates
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bottom_y_coordinates = [(x.by(), x, "bottom") for x in pin_set]
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top_y_coordinates = [(x.uy(), x, "top") for x in pin_set]
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y_coordinates = bottom_y_coordinates + top_y_coordinates
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y_coordinates.sort(key=lambda x: x[0])
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self.pin_groups[pin_name] = [pin_group(name=pin_name, pin_set=x, router=self) for x in equiv_classes]
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# Map the pins to the lower indices
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bottom_index_map = {x[1]:i for i,x in enumerate(y_coordinates) if x[2]=="bottom"}
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top_index_map = {x[1]:i for i,x in enumerate(y_coordinates) if x[2]=="bottom"}
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# Sort the pin list by x coordinate
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pin_list = list(pin_set)
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pin_list.sort(key=lambda x: x.lx())
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# for shapes in x order
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for pin in pin_list:
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# start at pin's lower y coordinate
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bottom_index = bottom_index_map[pin]
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compared_pins = set()
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for i in range(bottom_index,len(y_coordinates)):
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compare_pin = y_coordinates[i][1]
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# Don't overlap yourself
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if pin==compare_pin:
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continue
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# Done when we encounter any shape above the pin
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if compare_pin.by() > pin.uy():
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break
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# Don't double compare the same pin twice
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if compare_pin in compared_pins:
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continue
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compared_pins.add(compare_pin)
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# If we overlap, add them to the list
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if pin.overlaps(compare_pin):
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overlap_list.append((pin,compare_pin))
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# Initial unique group assignments
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group_id = {}
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gid = 1
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for pin in pin_list:
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group_id[pin] = gid
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gid += 1
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for p in overlap_list:
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(p1,p2) = p
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for pin in pin_list:
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if group_id[pin] == group_id[p2]:
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group_id[pin] = group_id[p1]
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# For each pin add it to it's group
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group_map = {}
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for pin in pin_list:
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gid = group_id[pin]
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if gid not in group_map.keys():
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group_map[gid] = pin_group(name=pin_name, pin_set=[], router=self)
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group = group_map[gid]
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# We always add it to the first set since they are touching
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group.pins[0].add(pin)
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self.pin_groups[pin_name] = group_map.values()
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# This is the old O(n^2) implementation
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# def analyze_pins(self, pin_name):
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# """
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# Analyze the shapes of a pin and combine them into pin_groups which are connected.
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# """
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# debug.info(2,"Analyzing pin groups for {}.".format(pin_name))
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# pin_set = self.pins[pin_name]
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# # Put each pin in an equivalence class of it's own
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# equiv_classes = [set([x]) for x in pin_set]
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# def combine_classes(equiv_classes):
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# for class1 in equiv_classes:
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# for class2 in equiv_classes:
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# if class1 == class2:
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# continue
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# # Compare each pin in each class,
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# # and if any overlap, update equiv_classes to include the combined the class
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# for p1 in class1:
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# for p2 in class2:
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# if p1.overlaps(p2):
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# combined_class = class1 | class2
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# equiv_classes.remove(class1)
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# equiv_classes.remove(class2)
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# equiv_classes.append(combined_class)
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# return(equiv_classes)
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# return(equiv_classes)
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# old_length = math.inf
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# while (len(equiv_classes)<old_length):
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# old_length = len(equiv_classes)
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# equiv_classes = combine_classes(equiv_classes)
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# self.pin_groups[pin_name] = [pin_group(name=pin_name, pin_set=x, router=self) for x in equiv_classes]
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def convert_pins(self, pin_name):
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"""
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