adapted shifter in ppa.sv for widths beside 32 and 64

modified plotting and regression in ppaAnalyze.py

pipelined/src/ppa/ppa.sv

@@ -281,20 +281,21 @@ module ppa_shifter #(parameter WIDTH=32) (
   // For RV64, 32 and 64-bit shifts are needed, with sign extension.
 
   // funnel shifter input (see CMOS VLSI Design 4e Section 11.8.1, note Table 11.11 shift types wrong)
-  if (WIDTH == 64) begin:shifter  // RV64 fix what about 128
+  if (WIDTH == 64 | WIDTH ==128) begin:shifter  // RV64 or 128
     always_comb  // funnel mux
       if (W64) begin // 32-bit shifts
         if (Right)
-          if (Arith) z = {64'b0, {31{A[31]}}, A[31:0]};
+          if (Arith) z = {{WIDTH{1'b0}}, {WIDTH/2 -1{A[WIDTH/2 -1]}}, A[WIDTH/2 -1:0]};
-          else       z = {95'b0, A[31:0]};
+          else       z = {{WIDTH*3/2-1{1'b0}}, A[WIDTH/2 -1:0]};
-        else         z = {32'b0, A[31:0], 63'b0};
+        else         z = {{WIDTH/2{1'b0}}, A[WIDTH/2 -1:0], {WIDTH-1{1'b0}}};
       end else begin
         if (Right)
-          if (Arith) z = {{63{A[63]}}, A};
+          if (Arith) z = {{WIDTH-1{A[WIDTH-1]}}, A};
-          else       z = {63'b0, A};
+          else       z = {{WIDTH-1{1'b0}}, A};
-        else         z = {A, 63'b0};         
+        else         z = {A, {WIDTH-1{1'b0}}};         
       end
-  end else begin:shifter // RV32, 
+      assign amttrunc = W64  ? {1'b0, Amt[$clog2(WIDTH)-2:0]} : Amt; // 32 or 64-bit shift 
+  end else begin:shifter // RV32 or less
     always_comb  // funnel mux
       if (Right) 
         if (Arith) z = {{WIDTH-1{A[WIDTH-1]}}, A};
@@ -302,7 +303,7 @@ module ppa_shifter #(parameter WIDTH=32) (
       else         z = {A, {WIDTH-1{1'b0}}};
     assign amttrunc = Amt; // shift amount
   end 
-    assign amttrunc = (W64 & WIDTH==64) ? {1'b0, Amt[4:0]} : Amt; // 32 or 64-bit shift fix
+    
 
   // opposite offset for right shfits
   assign offset = Right ? amttrunc : ~amttrunc;

synthDC/ppaAnalyze.py

@@ -3,6 +3,7 @@ import subprocess
 import csv
 import re
 import matplotlib.pyplot as plt
+import matplotlib.lines as lines
 import numpy as np
 
 def getData():
@@ -32,6 +33,23 @@ def getData():
 
     return allSynths
 
+def getVals(module, freq, var):
+    global allSynths
+    if (var == 'delay'):
+        ind = 3 
+        units = " (ps)"
+    else:
+        ind = 4
+        units = " (square microns)"
+
+    widths = []
+    ivar = []
+    for oneSynth in allSynths:
+        if (oneSynth[0] == module) & (oneSynth[2] == freq):
+            widths += [oneSynth[1]]
+            ivar += [oneSynth[ind]]
+    return widths, ivar, units
+
 def writeCSV(allSynths):
     file = open("ppaData.csv", "w")
     writer = csv.writer(file)
@@ -42,6 +60,17 @@ def writeCSV(allSynths):
 
     file.close()
 
+def polyfitR2(x, y, deg):
+    ''' from internet, check math'''
+    z = np.polyfit(x, y, deg)
+    p = np.poly1d(z)
+    yhat = p(x)                         # or [p(z) for z in x]    
+    ybar = np.sum(y)/len(y)          # or sum(y)/len(y)    
+    ssreg = np.sum((yhat-ybar)**2)   # or sum([ (yihat - ybar)**2 for yihat in yhat])    
+    sstot = np.sum((y - ybar)**2)    # or sum([ (yi - ybar)**2 for yi in y])    
+    r2 = ssreg / sstot    
+    return p, r2
+
 def plotPPA(module, freq, var):
     '''
     module: string module name
@@ -49,47 +78,82 @@ def plotPPA(module, freq, var):
     var: string 'delay' or 'area'
     plots chosen variable vs width for all matching syntheses with regression
     '''
-    global allSynths
-    ind = 3 if (var == 'delay') else 4
-    widths = []
-    ivar = []
-    for oneSynth in allSynths:
-        if (oneSynth[0] == module) & (oneSynth[2] == freq):
 
-            widths += [oneSynth[1]]
+    # A = np.vstack([x, np.ones(len(x))]).T
-            ivar += [oneSynth[ind]]
+    # mcresid = np.linalg.lstsq(A, y, rcond=None)
+    # m, c = mcresid[0]
+    # resid = mcresid[1]
+    # r2 = 1 - resid / (y.size * y.var())
+    # p, r2p = polyfitR2(x, y, 2)
+    # zlog = np.polyfit(np.log(x), y, 1)
+    # plog = np.poly1d(zlog)
+    # xplog = np.log(xp)
+    # _ = plt.plot(x, m*x + c, 'r', label='Linear fit R^2='+ str(r2)[1:7])
+    # _ = plt.plot(xp, p(xp), label='Quadratic fit R^2='+ str(r2p)[:6])
+    # _ = plt.plot(xp, plog(xplog), label = 'Log fit')
 
-    x = np.array(widths, dtype=np.int)
+    widths, ivar, units = getVals(module, freq, var)
-    y = np.array(ivar, dtype=np.float)
+    coefs, r2 = regress(widths, ivar)
 
-    A = np.vstack([x, np.ones(len(x))]).T
+    xp = np.linspace(8, 140, 200)
-    m, c = np.linalg.lstsq(A, y, rcond=None)[0]
+    pred = [coefs[0] + x*coefs[1] + np.log(x)*coefs[2] + x*np.log(x)*coefs[3] for x in xp]
 
-    z = np.polyfit(x, y, 2)
+    r2p = round(r2[0], 4)
-    p = np.poly1d(z)
+    rcoefs = [round(c, 3) for c in coefs]
 
-    zlog = np.polyfit(np.log(x), y, 1)
+    l = "{} + {}*N + {}*log(N) + {}*Nlog(N)".format(*rcoefs) 
-    plog = np.poly1d(zlog)
+    legend_elements = [lines.Line2D([0], [0], color='steelblue', label=module),
+                       lines.Line2D([0], [0], color='orange', label=l),
+                       lines.Line2D([0], [0], ls='', label=' R^2='+ str(r2p))]
 
-    xp = np.linspace(0, 140, 200)
+    _ = plt.plot(widths, ivar, 'o', label=module, markersize=10)
-    xplog = np.log(xp)
+    _ = plt.plot(xp, pred)
-
+    _ = plt.legend(handles=legend_elements)
-    _ = plt.plot(x, y, 'o', label=module, markersize=10)
-    _ = plt.plot(x, m*x + c, 'r', label='Linear fit')
-    _ = plt.plot(xp, p(xp), label='Quadratic fit')
-    _ = plt.plot(xp, plog(xplog), label = 'Log fit')
-    _ = plt.legend()
     _ = plt.xlabel("Width (bits)")
-    _ = plt.ylabel(str.title(var))
+    _ = plt.ylabel(str.title(var) + units)
-    _ = plt.title("Target frequency " + str(freq))
+    _ = plt.title("Target frequency " + str(freq) + "MHz")
     plt.show()
-#fix square microns, picosec, end plots at 8 to stop negs, add equation to plots and R2
+
-# try linear term with delay as well (w and wo)
+def makePlots(mod):
+    plotPPA(mod, 5000, 'delay')
+    plotPPA(mod, 5000, 'area')
+    plotPPA(mod, 10, 'area')
+
+def regress(widths, var):
+
+    mat = []
+    for w in widths:
+        row = [1, w, np.log(w), w*np.log(w)]
+        mat += [row]
+    
+    y = np.array(var, dtype=np.float)
+    coefsResid = np.linalg.lstsq(mat, y, rcond=None)
+    coefs = coefsResid[0]
+    resid = coefsResid[1] 
+    r2 = 1 - resid / (y.size * y.var())
+    return coefs, r2
+
+def makeCoefTable():
+    file = open("ppaFitting.csv", "w")
+    writer = csv.writer(file)
+    writer.writerow(['Module', 'Variable', 'Freq', '1', 'N', 'log(N)', 'Nlog(N)', 'R^2'])
+
+    for mod in ['add', 'mult', 'comparator']:
+        for comb in [['delay', 5000], ['area', 5000], ['area', 10]]:
+            var = comb[0]
+            freq = comb[1]
+            widths, ivar, units = getVals(mod, freq, var)
+            coefs, r2 = regress(widths, ivar)
+            row = [mod] + comb + np.ndarray.tolist(coefs) + [r2[0]]
+            writer.writerow(row)
+
+    file.close()
 
 allSynths = getData()
 
 writeCSV(allSynths)
 
-plotPPA('mult', 5000, 'delay')
+makePlots('shifter')
-plotPPA('mult', 5000, 'area')
+
-plotPPA('mult', 10, 'area')
+# makeCoefTable()
+

synthDC/ppaFitting.csv

@@ -0,0 +1,10 @@
+Module,Variable,Freq,1,N,log(N),Nlog(N),R^2
+add,delay,5000,0.23935453005464438,0.015973094945355207,-0.058207695467226296,-0.002593789781151714,0.9902532112478974
+add,area,5000,-1032.1274349672115,64.4386855922132,374.6678949053879,-3.2579193244904823,0.9999180068922152
+add,area,10,-13.720004131149423,14.699999256147343,3.6067390521177815e-06,9.312480709428003e-08,1.0
+mult,delay,5000,-0.21755360109289562,-0.00033127390710363004,0.36865114245083547,0.0004100845872014472,0.9999815499619515
+mult,area,5000,-29928.193338752997,-11370.538120558254,39122.3984379376,2592.313970431163,0.9998454828501703
+mult,area,10,-24112.991162714883,-8735.874000034026,30452.017533199683,1892.3032427172166,0.9999575675635335
+comparator,delay,5000,0.18302939890710385,-0.001793523907103751,0.00950014684425352,0.0004195522734073458,0.9999387049502957
+comparator,area,5000,1831.2076391201958,303.59984869227907,-1617.4342555852443,-44.475154143873425,0.9990603962758624
+comparator,area,10,-0.23027509289593326,18.299023530396347,-8.48304611908023,-0.4881808064440773,0.9999674500675539

synthDC/ppaSynth.py

@@ -14,12 +14,11 @@ def deleteRedundant(LoT):
         bashCommand = synthStr.format(*synth)
         outputCPL = subprocess.check_output(['bash','-c', bashCommand])
 
-widths = ['128']
+widths = ['8', '16', '32', '64', '128']
-modules = ['mult']
+modules = ['shifter']
-freqs = ['5000']
+freqs = ['10', '5000']
 tech = 'sky90'
 
-#to run: add 8 10, shifter 8 16 (check .sv!)
 
 LoT = []
 for module in modules: