Added strong scaling analysis

gen/perf.py

+import sys
+sys.path.append('../')
+import matplotlib.pyplot as plt
+
+from netflow import *
+
+from time import perf_counter
+        
+def main():
+    if len(sys.argv) != 4:
+        raise AssertionError("Usage: python3 generate.py <n1> <n2> <n3>")
+    
+    basenet = netflow.load_network_from('../netflow/network/network.h5')
+    print("Network statistics:")
+    print("Throats: %d" % len(basenet.throats))
+    pore_throat_counts = [len(pore.throats) for pore in basenet.pores]
+    print("Max. number of throats per pore: %d" % max(pore_throat_counts))
+    print("Min. number of throats per pore: %d" % min(pore_throat_counts))
+    print("Avg. number of throats per pore: %f" % (sum(pore_throat_counts) / len(pore_throat_counts)))
+    
+    target  = [int(sys.argv[1]), int(sys.argv[2]), int(sys.argv[3])]
+    print("Target size: {}".format(target))
+    cutoff  = 0.5 * max([basenet.ub[i] - basenet.lb[i] \
+                        for i in range(len(basenet.ub))])
+    
+    i = 0
+    max_ = 5
+    
+    speedups = []
+    threads = []
+    times = []
+    while (i <= max_):
+        nthreads = 1 << i
+        print(nthreads)
+        
+        start = perf_counter()
+        dendro = netflow.generate_dendrogram(basenet=basenet, targetsize=target, \
+                                        cutoff=cutoff, sd=42, nthreads=nthreads, mute=True)
+        end = perf_counter()
+        elapsed = end - start
+        
+        print("Generated network statistics:")
+        print("Throats: %d" % len(dendro.throats))
+        print("Pores:   %d" % len(dendro.pores))
+        
+        threads.append(nthreads)
+        times.append(elapsed)
+        
+        speedups.append(times[0] / times[i])
+        i += 1
+        
+    plt.figure()
+    plt.title(r"Strong Scaling for targetsize {}".format(target))
+    plt.xlabel(r"#processes")
+    plt.ylabel(r"Speedup")
+    plt.plot(threads, speedups, '--bo')
+    plt.savefig('plots/strong_scaling.png')
+    
+if __name__ == '__main__':
+    main()

gen/perf.sh

+#!/bin/bash
+bsub -n 48 -W 00:30 -R fullnode python3 perf.py 4 4 4

netflow/netgen.py

@@ -226,9 +226,6 @@ class CellList:
         n = len(pores)
         
         for poreIdx in pores:
-            
-            if tid == 0:
-                print(f"progress {((poreIdx+1) / n)*100.:.1f}%", end="\r", flush=True)
                 
             candidates = self.find_candidates(poreIdx)
             
@@ -237,7 +234,7 @@ class CellList:
                 lt = self.throatL[throatIdx]
                 
                 # Find best match among candidates
-                matchIdx, matchLen = min(candidates.items(), key=lambda il: abs(il[1] - lt))
+                matchIdx, _ = min(candidates.items(), key=lambda il: abs(il[1] - lt))
                 # Remove match from candidates
                 del candidates[matchIdx]
                 # Put best match index in poreThroatTable
@@ -995,6 +992,8 @@ def generate_dendrogram(basenet: Network, targetsize: List[int], \
     # Free memory associated with cellList (not needed anymore)
     del cellList
     
+    # DEBUG
+    """
     percent = k / (k + len(throats)) * 100.
     print("\b"*24 + "{0:d} throats in total, {1:d} unrealised ({2:.1f}%)".\
         format(len(throats), k, percent))
@@ -1002,7 +1001,7 @@ def generate_dendrogram(basenet: Network, targetsize: List[int], \
     print("Avg. throat length difference: %e" % avg_throat_diff)
     print("Relative to Lmax: %.1f%%" % (avg_throat_diff / basenet.Lmax * 100.))
     print("Percentage where match was fully-connected: %.1f%%" % (n_already_taken / total * 100.))
-    
+    """
     # assemble and return network
     network = Network(lb=[0.0 for k in range(d)],
         ub=L, Lmax=basenet.Lmax, label='from_' + basenet.label)