util: Enable DRAM sweep to print power and efficiency

This patch enhances the functionality of the DRAM sweep script to not
only plot the bandwidth utilisation, but also total power and power
efficiency. To do so, a command-line switch is added, and a bit more
data extracted from the stats.

diff --git a/util/dram_sweep_plot.py b/util/dram_sweep_plot.py
index a57de3d1cf2ad043dad8dccec9cebf10ebdeb871..347986b2029c1d6fc39ba41b3de2152964b126aa 100755 (executable)
--- a/util/dram_sweep_plot.py
+++ b/util/dram_sweep_plot.py
@@ -57,18 +57,28 @@ import re
 # generated by the config/dram/sweep.py script
 def main():
 
-    if len(sys.argv) != 2:
-        print "Usage: ", sys.argv[0], " <simout directory>"
+    if len(sys.argv) != 3:
+        print "Usage: ", sys.argv[0], "-u|p|e <simout directory>"
         exit(-1)
 
+    if len(sys.argv[1]) != 2 or sys.argv[1][0] != '-' or \
+            not sys.argv[1][1] in "upe":
+        print "Choose -u (utilisation), -p (total power), or -e " \
+            "(power efficiency)"
+        exit(-1)
+
+    # Choose the appropriate mode, either utilisation, total power, or
+    # efficiency
+    mode = sys.argv[1][1]
+
     try:
-        stats = open(sys.argv[1] + '/stats.txt', 'r')
+        stats = open(sys.argv[2] + '/stats.txt', 'r')
     except IOError:
         print "Failed to open ", sys.argv[1] + '/stats.txt', " for reading"
         exit(-1)
 
     try:
-        simout = open(sys.argv[1] + '/simout', 'r')
+        simout = open(sys.argv[2] + '/simout', 'r')
     except IOError:
         print "Failed to open ", sys.argv[1] + '/simout', " for reading"
         exit(-1)
@@ -92,29 +102,57 @@ def main():
         print "Failed to establish sweep details, ensure simout is up-to-date"
         exit(-1)
 
+    # Now parse the stats
+    peak_bw = []
+    bus_util = []
+    avg_pwr = []
+
+    for line in stats:
+        match = re.match(".*busUtil\s+(\d+\.\d+)\s+#.*", line)
+        if match:
+            bus_util.append(float(match.groups(0)[0]))
+
+        match = re.match(".*peakBW\s+(\d+\.\d+)\s+#.*", line)
+        if match:
+            peak_bw.append(float(match.groups(0)[0]))
 
-    # Collect the bus utilisation as our Z-axis, we do this in a 2D
+        match = re.match(".*averagePower\s+(\d+\.\d+)\s+#.*", line)
+        if match:
+            avg_pwr.append(float(match.groups(0)[0]))
+    stats.close()
+
+
+    # Sanity check
+    if not (len(peak_bw) == len(bus_util) and len(bus_util) == len(avg_pwr)):
+        print "Peak bandwidth, bus utilisation, and average power do not match"
+        exit(-1)
+
+    # Collect the selected metric as our Z-axis, we do this in a 2D
     # grid corresponding to each iteration over the various stride
     # sizes.
     z = []
     zs = []
     i = 0
 
-    # Now parse the stats
-    for line in stats:
-        match = re.match(".*busUtil\s+(\d+\.\d+)\s+#.*", line)
-        if match:
-            bus_util = float(match.groups(0)[0])
-            z.append(bus_util)
-            i += 1
-            # If we have completed a sweep over the stride sizes,
-            # start anew
-            if i == max_size / burst_size:
-                zs.append(z)
-                z = []
-                i = 0
-
-    stats.close()
+    for j in range(len(peak_bw)):
+        if mode == 'u':
+            z.append(bus_util[j])
+        elif mode == 'p':
+            z.append(avg_pwr[j])
+        elif mode == 'e':
+            # avg_pwr is in mW, peak_bw in MiByte/s, bus_util in percent
+            z.append(avg_pwr[j] / (bus_util[j] / 100.0 * peak_bw[j] / 1000.0))
+        else:
+            print "Unexpected mode %s" % mode
+            exit(-1)
+
+        i += 1
+        # If we have completed a sweep over the stride sizes,
+        # start anew
+        if i == max_size / burst_size:
+            zs.append(z)
+            z = []
+            i = 0
 
     # We should have a 2D grid with as many columns as banks
     if len(zs) != banks:
@@ -140,7 +178,13 @@ def main():
 
     ax.set_xlabel('Bytes per activate')
     ax.set_ylabel('Banks')
-    ax.set_zlabel('Efficiency (%)')
+
+    if mode == 'u':
+        ax.set_zlabel('Utilisation (%)')
+    elif mode == 'p':
+        ax.set_zlabel('Power (mW)')
+    elif mode == 'e':
+        ax.set_zlabel('Power efficiency (mW / GByte / s)')
 
     # Add a colorbar
     fig.colorbar(surf, shrink=0.5, pad=.1, aspect=10)