forked from Github_Repos/cvw
major revisions to ppaAnalyze
synths as namedtuples, plotting pulls from csv, support for multiple techs
This commit is contained in:
Madeleine Masser-Frye
parent
81a869c921
commit
5311c0c9eb
@ -1,28 +1,39 @@
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#!/usr/bin/python3
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# Madeleine Masser-Frye mmasserfrye@hmc.edu 5/22
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from distutils.log import error
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from operator import index
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from statistics import median
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import subprocess
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import statistics
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import csv
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import re
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import matplotlib.pyplot as plt
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import matplotlib.lines as lines
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import numpy as np
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from collections import namedtuple
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def getData(tech, mod=None, width=None):
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''' returns a list of lists
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each list contains results of one synthesis that matches the input specs
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def synthsfromcsv(filename):
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with open(filename, newline='') as csvfile:
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csvreader = csv.reader(csvfile)
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global allSynths
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allSynths = list(csvreader)
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for i in range(len(allSynths)):
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for j in range(len(allSynths[0])):
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try: allSynths[i][j] = int(allSynths[i][j])
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except:
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try: allSynths[i][j] = float(allSynths[i][j])
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except: pass
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allSynths[i] = Synth(*allSynths[i])
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def synthsintocsv(mod=None, width=None):
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''' writes a CSV with one line for every available synthesis
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each line contains the module, tech, width, target freq, and resulting metrics
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'''
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specStr = ''
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if mod != None:
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specStr = mod
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if width != None:
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specStr += ('_'+str(width))
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specStr += '*{}*'.format(tech)
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specStr += '*'
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bashCommand = "grep 'Critical Path Length' runs/ppa_{}/reports/*qor*".format(specStr)
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outputCPL = subprocess.check_output(['bash','-c', bashCommand])
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@ -41,8 +52,12 @@ def getData(tech, mod=None, width=None):
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wm = re.compile('ppa_\w*_\d*_qor')
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da = re.compile('\d*\.\d{6}')
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p = re.compile('\d+\.\d+[e-]*\d+')
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t = re.compile('[a-zA-Z0-9]+nm')
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file = open("ppaData.csv", "w")
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writer = csv.writer(file)
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writer.writerow(['Module', 'Tech', 'Width', 'Target Freq', 'Delay', 'Area', 'L Power (nW)', 'D energy (mJ)'])
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allSynths = []
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for i in range(len(linesCPL)):
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line = linesCPL[i]
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mwm = wm.findall(line)[0][4:-4].split('_')
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@ -51,78 +66,60 @@ def getData(tech, mod=None, width=None):
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area = float(da.findall(linesDA[i])[0])
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mod = mwm[0]
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width = int(mwm[1])
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tech = t.findall(line)[0][:-2]
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try: #fix
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power = p.findall(linesP[i])
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lpower = float(power[2])
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denergy = float(power[1])*delay
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except:
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lpower = 0
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denergy = 0
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power = p.findall(linesP[i])
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lpower = float(power[2])
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denergy = float(power[1])*delay
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oneSynth = [mod, width, freq, delay, area, lpower, denergy]
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allSynths += [oneSynth]
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return allSynths
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writer.writerow([mod, tech, width, freq, delay, area, lpower, denergy])
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file.close()
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def getVals(tech, module, var, freq=None):
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''' for a specified tech, module, and variable/metric
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returns a list of widths and the corresponding values for that metric with the appropriate units
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returns a list of values for that metric in ascending width order with the appropriate units
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works at a specified target frequency or if none is given, uses the synthesis with the min delay for each width
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'''
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allSynths = getData(tech, mod=module)
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if (var == 'delay'):
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ind = 3
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units = " (ns)"
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elif (var == 'area'):
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ind = 4
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units = " (sq microns)"
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scale = 2
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elif (var == 'lpower'):
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ind = 5
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units = " (nW)"
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elif (var == 'denergy'):
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ind = 6
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units = " (pJ)"
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else:
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error
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widths = []
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global widths
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metric = []
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widthL = []
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if (freq != None):
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for oneSynth in allSynths:
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if (oneSynth[2] == freq):
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widths += [oneSynth[1]]
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metric += [oneSynth[ind]]
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if (oneSynth.freq == freq) & (oneSynth.tech == tech) & (oneSynth.module == module):
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widthL += [oneSynth.width]
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osdict = oneSynth._asdict()
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metric += [osdict[var]]
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metric = [x for _, x in sorted(zip(widthL, metric))] # ordering
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else:
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widths = [8, 16, 32, 64, 128]
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for w in widths:
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m = 10000 # large number to start
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m = 100000 # large number to start
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for oneSynth in allSynths:
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if (oneSynth[1] == w):
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if (oneSynth[3] < m):
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m = oneSynth[3]
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met = oneSynth[ind]
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if (oneSynth.width == w) & (oneSynth.tech == tech) & (oneSynth.module == module):
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if (oneSynth.delay < m):
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m = oneSynth.delay
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osdict = oneSynth._asdict()
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met = osdict[var]
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metric += [met]
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if ('flop' in module) & (var == 'area'):
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metric = [m/2 for m in metric] # since two flops in each module
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return widths, metric, units
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return metric, units
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def writeCSV(tech):
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''' writes a CSV with one line for every available synthesis for a specified tech
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each line contains the module, width, target freq, and resulting metrics
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'''
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allSynths = getData(tech)
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file = open("ppaData.csv", "w")
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writer = csv.writer(file)
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writer.writerow(['Module', 'Width', 'Target Freq', 'Delay', 'Area', 'L Power (nW)', 'D energy (mJ)'])
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for one in allSynths:
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writer.writerow(one)
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file.close()
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def genLegend(fits, coefs, r2, tech):
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def genLegend(fits, coefs, r2, techcolor):
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''' generates a list of two legend elements
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labels line with fit equation and dots with tech and r squared of the fit
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'''
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@ -147,7 +144,7 @@ def genLegend(fits, coefs, r2, tech):
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eq += " + " + coefsr[ind] + "*Nlog2(N)"
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ind += 1
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c = 'blue' if (tech == 'sky90') else 'green'
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tech, c = techcolor
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legend_elements = [lines.Line2D([0], [0], color=c, label=eq),
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lines.Line2D([0], [0], color=c, ls='', marker='o', label=tech +' $R^2$='+ str(round(r2, 4)))]
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return legend_elements
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@ -167,14 +164,17 @@ def oneMetricPlot(module, var, freq=None, ax=None, fits='clsgn'):
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singlePlot = False
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fullLeg = []
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for tech in ['sky90', 'tsmc28']:
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c = 'blue' if (tech == 'sky90') else 'green'
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widths, metric, units = getVals(tech, module, var, freq=freq)
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xp, pred, leg = regress(widths, metric, tech, fits)
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fullLeg += leg
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global techcolors
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global widths
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for combo in techcolors:
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tech, c = combo
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metric, units = getVals(tech, module, var, freq=freq)
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if len(metric) == 5:
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xp, pred, leg = regress(widths, metric, combo, fits)
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fullLeg += leg
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ax.scatter(widths, metric, color=c)
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ax.plot(xp, pred, color=c)
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ax.scatter(widths, metric, color=c)
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ax.plot(xp, pred, color=c)
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ax.legend(handles=fullLeg)
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@ -183,10 +183,11 @@ def oneMetricPlot(module, var, freq=None, ax=None, fits='clsgn'):
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ax.set_ylabel(str.title(var) + units)
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if singlePlot:
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ax.set_title(module + " (target " + str(freq) + "MHz)")
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titleStr = " (target " + str(freq)+ "MHz)" if freq != None else " (min delay)"
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ax.set_title(module + titleStr)
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plt.show()
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def regress(widths, var, tech, fits='clsgn'):
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def regress(widths, var, techcolor, fits='clsgn'):
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''' fits a curve to the given points
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returns lists of x and y values to plot that curve and legend elements with the equation
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'''
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@ -215,12 +216,13 @@ def regress(widths, var, tech, fits='clsgn'):
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n = [func(x) for func in funcArr]
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pred += [sum(np.multiply(coefs, n))]
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leg = genLegend(fits, coefs, r2, tech)
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leg = genLegend(fits, coefs, r2, techcolor)
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return xp, pred, leg
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def makeCoefTable(tech):
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''' writes CSV with each line containing the coefficients for a regression fit
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''' not currently in use, may salvage later
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writes CSV with each line containing the coefficients for a regression fit
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to a particular combination of module, metric, and target frequency
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'''
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file = open("ppaFitting.csv", "w")
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@ -231,7 +233,8 @@ def makeCoefTable(tech):
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for comb in [['delay', 5000], ['area', 5000], ['area', 10]]:
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var = comb[0]
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freq = comb[1]
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widths, metric, units = getVals(tech, mod, freq, var)
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metric, units = getVals(tech, mod, freq, var)
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global widths
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coefs, r2, funcArr = regress(widths, metric)
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row = [mod] + comb + np.ndarray.tolist(coefs) + [r2]
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writer.writerow(row)
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@ -280,15 +283,14 @@ def noOutliers(freqs, delays, areas):
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def freqPlot(tech, mod, width):
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''' plots delay, area, area*delay, and area*delay^2 for syntheses with specified tech, module, width
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'''
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allSynths = getData(tech, mod=mod, width=width)
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global allSynths
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freqsL, delaysL, areasL = ([[], []] for i in range(3))
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for oneSynth in allSynths:
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if (mod == oneSynth[0]) & (width == oneSynth[1]):
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ind = (1000/oneSynth[3] < oneSynth[2]) # when delay is within target clock period
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freqsL[ind] += [oneSynth[2]]
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delaysL[ind] += [oneSynth[3]]
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areasL[ind] += [oneSynth[4]]
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if (mod == oneSynth.module) & (width == oneSynth.width) & (tech == oneSynth.tech):
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ind = (1000/oneSynth.delay < oneSynth.freq) # when delay is within target clock period
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freqsL[ind] += [oneSynth.freq]
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delaysL[ind] += [oneSynth.delay]
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areasL[ind] += [oneSynth.area]
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f, (ax1, ax2, ax3, ax4, ax5) = plt.subplots(5, 1, sharex=True)
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@ -347,13 +349,14 @@ def plotPPA(mod, freq=None):
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plt.suptitle(mod + titleStr)
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plt.show()
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Synth = namedtuple("Synth", "module tech width freq delay area lpower denergy")
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techcolors = [['sky90', 'green'], ['tsmc28', 'blue']]
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widths = [8, 16, 32, 64, 128]
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synthsintocsv()
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# writeCSV()
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synthsfromcsv('ppaData.csv') # your csv here!
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# look at comparaotro 32
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# for x in ['add', 'mult', 'comparator', 'alu', 'csa']:
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# for y in [8, 16, 32, 64, 128]:
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# freqPlot('sky90', x, y)
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freqPlot('sky90', 'mult', 32)
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### examples
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# oneMetricPlot('add', 'delay')
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#freqPlot('sky90', 'add', 8)
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#plotPPA('add')
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2024
synthDC/ppaData.csv
2024
synthDC/ppaData.csv
File diff suppressed because it is too large
Load Diff
@ -44,30 +44,30 @@ def getData():
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allSynths = getData()
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arr = [-40, -20, -8, -6, -4, -2, 0, 2, 4, 6, 8, 12, 20, 40]
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widths = [8, 16, 32, 64, 128]
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widths = [16, 8, 32, 64, 128]
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modules = ['add']
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tech = 'tsmc28'
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LoT = []
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# # # initial sweep to get estimate of min delay
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freqs = [10000, 15000, 20000]
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for module in modules:
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for width in widths:
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for freq in freqs:
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LoT += [[module, width, tech, freq]]
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# freqs = [25000, 35000]
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# for module in modules:
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# for width in widths:
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# for freq in freqs:
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# LoT += [[module, width, tech, freq]]
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# # thorough sweep based on estimate of min delay
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# for m in modules:
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# for w in widths:
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# delays = []
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# for oneSynth in allSynths:
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# if (oneSynth[0] == m) & (oneSynth[1] == w):
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# delays += [oneSynth[3]]
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# try: f = 1000/min(delays)
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# except: print(m)
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# for freq in [str(round(f+f*x/100)) for x in arr]:
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# LoT += [[m, w, tech, freq]]
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for m in modules:
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for w in widths:
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delays = []
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for oneSynth in allSynths:
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if (oneSynth[0] == m) & (oneSynth[1] == w):
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delays += [oneSynth[3]]
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try: f = 1000/min(delays)
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except: print(m)
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for freq in [str(round(f+f*x/100)) for x in arr]:
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LoT += [[m, w, tech, freq]]
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deleteRedundant(LoT)
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pool = Pool()
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