Пример #1
0
	# here comes the actual decomposition algorithm which returns just an array of arrays/integers and a array of integers with the cut position within the tree
	lutstruc, cutHeights = resultTree.doNaiveDecomp(k, weight_dic_int, setOfLdMy)


	print "\nChosen %s-LUT structure:" %k
	print lutstruc

else:
	# smarter decomposition with the help of a gain for each level here:
		cutHeights = resultTree.doSmartDecomp(k, weight_dic_int, setOfLdMy)

print "\nCut positions:"
print cutHeights


ultimativeArray = bdd.encodeCutNodes(resultTree,cutHeights)
outputCore = bdd.getBLIF(ultimativeArray, resultTree)






#------write BLIF file ------------------------------------------
print "\n... creating BLIF file"

outputName = f.name.split('/')[-1].split('.')[0]+ '_%s_feasible' %k

outputContent = ".model " + outputName + "\n.inputs" 
for inVar in range(1,inputs+1):
        outputContent += " x%s" %inVar
Пример #2
0
def mainProcedure(inputfile, k, actSifting, plotGraph):
    f = open(inputfile, "r")
    content = f.readlines()
    f.close()
    print inputfile

    # ------- splitting header / boundset / freeset  ---------------------

    content2 = []
    equations = []

    for line in content:
        content2.append(line.split(" "))

    for line in content2:

        if line[0] == ".i":
            inputs = int(line[1][:-1])

        if line[0] == ".o":
            outputs = int(line[1][:-1])

        if line[0][0] != "." and len(line) >= 2:
            equations.append([line[0], line[1][:-1]])

            # ------- create minterms from blif equations  ---------------------

    outputs = 1  # comment if all outputs shall computed !!!!!
    maxtermArray = []
    variableOrderArray = []

    for i in range(outputs):
        maxtermArray.append(bf.Maxterm(i))  # i is index, increment for each output

    for output in range(outputs):  # for each output
        equations_ONset = []  # only ON set equations
        equations_NumberOfCares = []  # gives a number for each line, which indicates how many 0s or 1s are included

        for line in equations:

            if line[1][output] == "1":  # select the line with an 1 at the end to create the minterm

                equations_ONset.append(line[0])
                tempCareCounter = 0
                for position in range(inputs):
                    if line[0][position] == "0" or line[0][position] == "1":
                        tempCareCounter += 1
                equations_NumberOfCares.append(float(tempCareCounter))

                # ------- sort inputs depending on variable weights ----------------
        weight_dic = {}  # dictionary in the form of {'x1': 0.7337, 'x2': 0.1234, ... }
        numberOfLines = float(len(equations_ONset))

        # all values to zero
        for i in range(inputs):
            weight_dic["x" + str(i + 1)] = 0
            # update weigth for each variable
        for i in range(inputs):
            for index, line in enumerate(equations_ONset):
                if line[i] == "0" or line[i] == "1":
                    weight_dic["x" + str(i + 1)] += 1.0 / equations_NumberOfCares[index] * 1.0 / numberOfLines

                    # sort weight_dic
        weight_dic = sorted(
            weight_dic.items(), key=itemgetter(1)
        )  # notice that dictionary becomes a list of tuples now

        # weight list becomes a list of variable indeces in sorted order [9, 3, ...]
        weight_dic_int = []
        for var in weight_dic:
            weight_dic_int.append(int(var[0][1:]))
            # lowest value at the beginning -> must be reversed
        weight_dic_int.reverse()

        # add the initial order to an array
        variableOrderArray.append(weight_dic_int)

        # finally build	 the maxterm
        for line in equations_ONset:
            maxtermArray[output].addMinterm(bf.buildMinterm(line))

            # -------- building tree -----------------------------------------

    print "\n... creating tree",
    resultTree = bdd.doShannon(maxtermArray[0], 1, inputs, weight_dic_int)  # must be done for every output !!!!

    print "\n\n... creating QRBDD"
    resultTree.makeQRBDD()

    print "\n... updating level"
    bdd.updateLevel(resultTree)
    if actSifting == 1:
        print "\n\n... sifting tree"
        bdd.doSifting(resultTree)

        # update the variable order after sifting:
    weight_dic_int = bdd.getVariableOrder(resultTree, [])

    print "\nNumber of Nodes:", bdd.countNodes(resultTree)

    # --------create LUT structure ------------------------------------

    # create ld(my) for every level (actually it is not ld(my), because every ld(my)=0 becomes ld(my)=1)
    print "\n... calculating 'my' for each level"
    setOfLdMy = []
    for levels in range(1, inputs):
        ldmy = int(math.ceil(math.log(bdd.getMy(resultTree, levels + 1), 2)))
        # ldmy get modify if ldmy=0 -> necessary for doNaiveDecomp function
        if ldmy == 0:
            ldmy = 1
        setOfLdMy.append(ldmy)

        # naive or smart decomposition?
    print "\n... creating LUT structure"

    # here comes the actual decomposition algorithm which returns just an array of arrays/integers and a array of integers with the cut position within the tree
    lutstruc, cutHeights = resultTree.doNaiveDecomp(k, weight_dic_int, setOfLdMy)

    print "\nCut positions:"
    print cutHeights

    ultimativeArray = bdd.encodeCutNodes(resultTree, cutHeights)
    outputCore = bdd.getBLIF(ultimativeArray, resultTree)

    # ------write BLIF file ------------------------------------------
    print "\n... creating BLIF file"

    outputName = f.name.split("/")[-1].split(".")[0] + "_%s_feasible" % k

    outputContent = ".model " + outputName + "\n.inputs"
    for inVar in range(1, inputs + 1):
        outputContent += " x%s" % inVar
    outputContent += "\n.outputs y\n\n" + outputCore

    print "\n########## BLIF #########\n\n" + outputContent
    print "#########################"

    outputFile = open(outputName + ".blif", "w")
    outputFile.write(outputContent)
    outputFile.close()

    # ------- PLOT --------------------------------------------------
    if plotGraph == 1:
        print "\n... plotting tree"
        resultTree.dotPrint2()

    print "\nDone. Result saved in " + outputName + ".\n"

    exit(1)