source: inundation/pypar/pytiming @ 1855

Last change on this file since 1855 was 1851, checked in by ole, 19 years ago

Removed strict dependency on RandomArray?

File size: 6.6 KB
Line 
1#!/usr/bin/env python
2
3# Timing of MPI module for Python and estimation of latency and bandwidth
4#
5# Send numerical array in a ring from processor 0 to 1 etc back to 0
6# Perform timings and compare different sending strategies
7#
8# OMN, OCT 2001
9
10import time, sys, pypar, Numeric
11
12# The send/recv routines
13#
14import pypar
15
16#from mpiext import send_array, receive_array  #most direct methods
17#Not available in final install - use bypass form for now
18
19#--------------------------------------------------------------
20
21method = 2   # Use
22             # 0: automatically allocated buffers
23             # 1: user-supplied buffers
24             # 2: Use bypass - let pypar use direct mpi_ext call
25             # 3 (not there): direct call to mpiext (with buffers),
26             #    only fractionally better than bypass
27                 
28vanilla = False  # Force use of vanilla format (1)
29consistency_check = False # Check correctness
30
31
32#--------------------------------------------------------------
33# linfit
34#
35def linfit(x, y):
36  """Fit a and b to the model y = ax + b. Return a,b,variance
37  """
38 
39  Sx = Sy = SSoN = SxoN = norm = varest = 0.0
40  N = len(x)
41  assert len(y) == N, "x and y must have same length"
42 
43  for i in range(N):
44    #print("x,y = %f, %f\n",x[i],y[i])
45    Sx  = Sx + x[i]
46    Sy  = Sy + y[i]
47 
48  SxoN = Sx/N
49 
50  a = 0.0 
51  for i in range(N):
52    t    = x[i] - SxoN
53    SSoN = SSoN + t*t
54    a    = a + t*y[i]
55
56
57  a = a/SSoN            # a = (N Sxy - SxSy)/(NSxx - Sx^2) */
58  b = (Sy - Sx*a)/N
59 
60  # Quality - variance estimate \sum_i r_i^2 /(m-n)
61  for i in range(N): 
62    norm = norm + float(x[i])*x[i]
63    res = y[i] - a*x[i] - b
64    varest = varest + res*res
65
66  varest = varest/norm/(N-2)
67  return a, b, varest
68
69
70
71
72#--------------------------------------------------------------
73# Main program
74#
75MAXI  = 10         # Number of blocks
76MAXM  = 500000     # Largest block
77BLOCK = MAXM/MAXI  # Block size
78
79repeats = 10
80msgid = 0
81vanilla = 0 #Select vanilla mode (slower but general)
82
83numprocs = pypar.size()
84myid = pypar.rank()
85processor_name = pypar.Get_processor_name()
86
87if myid == 0:
88  # Main process - Create message, pass on, verify correctness and log timing
89  #
90  print "MAXM = %d, number of processors = %d" %(MAXM, numprocs)
91  print "Measurements are repeated %d times for reliability" %repeats
92
93if numprocs < 2:
94  print "Program needs at least two processors - aborting\n"
95  pypar.Abort()
96   
97pypar.Barrier() #Synchronize all before timing   
98print "I am process %d on %s" %(myid,processor_name)
99
100
101#Initialise data and timings
102#
103
104try:
105  from RandomArray import uniform, seed
106  seed(17, 53)
107  A = uniform(0.0,100.0,MAXM)
108except:
109  print 'problem with RandomArray'
110  from Numeric import ones, Float
111  A = ones( MAXM, Float )
112 
113elsize = A.itemsize()
114#print elsize
115
116noelem  = [0]*MAXI
117bytes   = [0]*MAXI         
118avgtime = [0.0]*MAXI         
119mintime = [ 1000000.0]*MAXI     
120maxtime = [-1000000.0]*MAXI           
121
122
123
124
125if myid == 0:   
126  # Determine timer overhead
127  cpuOH = 1.0;
128  for k in range(repeats):   # Repeat to get reliable timings
129    t1 = pypar.Wtime()
130    t2 = pypar.Wtime()
131    if t2-t1 < cpuOH: cpuOH = t2-t1
132   
133  print "Timing overhead is %f seconds.\n" %cpuOH         
134
135     
136# Pass msg circularly   
137for k in range(repeats):
138  if myid == 0:
139    print "Run %d of %d" %(k+1,repeats)
140   
141  for i in range(MAXI):
142    m=BLOCK*i+1       
143   
144    noelem[i] = m
145   
146    pypar.Barrier() # Synchronize
147   
148    if myid == 0:
149      #
150      # Main process
151      #
152      t1 = pypar.Wtime()
153
154      if method==0:
155        pypar.send(A[:m], destination=1, tag=msgid, vanilla=vanilla)
156        C = pypar.receive(numprocs-1, tag=msgid, vanilla=vanilla)
157      elif method == 1: 
158        pypar.send(A[:m], use_buffer=True, destination=1,
159                   tag=msgid, vanilla=vanilla)
160        C = pypar.receive(numprocs-1, buffer=A[:m], tag=msgid, vanilla=vanilla)
161      elif method==2:
162        pypar.send(A[:m], use_buffer=True, destination=1,
163                   tag=msgid, vanilla=vanilla, bypass=True)
164        C = pypar.receive(numprocs-1, buffer=A[:m], tag=msgid,
165                          vanilla=vanilla, bypass=True)
166      else:
167        raise 'Unknown method'
168        #send_array(A[:m], 1, msgid)   
169        #stat = receive_array(A[:m], numprocs-1, msgid)
170        #C = A[:m]
171       
172      t2 = pypar.Wtime() - t1 - cpuOH
173      t2 = t2/numprocs
174      avgtime[i] = avgtime[i] + t2
175      if t2 < mintime[i]: mintime[i] = t2
176      if t2 > maxtime[i]: maxtime[i] = t2
177
178      # Uncomment to verify integrity of data
179      # However, this may affect accuracy of timings for some reason.
180      #
181      if consistency_check:
182        assert Numeric.alltrue(C == A[:m])
183    else:
184      #
185      # Parallel process - get msg and pass it on
186      #
187
188      if method==0:
189        C = pypar.receive(myid-1, tag=msgid, vanilla=vanilla)
190        pypar.send(A[:m], destination=(myid+1)%numprocs,
191                   tag=msgid, vanilla=vanilla)
192      elif method==1: 
193        C = pypar.receive(myid-1, buffer=A[:m], tag=msgid, vanilla=vanilla)
194        pypar.send(A[:m], use_buffer=True, destination=(myid+1)%numprocs,
195                   tag=msgid, vanilla=vanilla)                       
196      elif method==2:
197        # Use pypar bypass
198        C = pypar.receive(myid-1, buffer=A[:m], tag=msgid,
199                          vanilla=vanilla, bypass=True)
200        pypar.send(A[:m], use_buffer=True, destination=(myid+1)%numprocs,
201                   tag=msgid, vanilla=vanilla, bypass=True)
202      else:
203        raise 'Unknown method'
204        # Use direct mpiext call
205        #stat = receive_array(A[:m], myid-1, msgid)               
206        #send_array(A[:m], (myid+1)%numprocs, msgid)
207
208
209# Output stats
210#
211if myid == 0:
212  print "Bytes transferred   time (micro seconds)"
213  print "                    min        avg        max "     
214  print "----------------------------------------------"
215     
216  for i in range(MAXI):
217    avgtime[i] = avgtime[i]/repeats*1.0e6 #Average micro seconds
218    mintime[i] = mintime[i]*1.0e6         #Min micro seconds       
219    maxtime[i] = maxtime[i]*1.0e6         #Min micro seconds             
220         
221    m = noelem[i]
222    bytes[i] = elsize*noelem[i]       
223     
224    print "%10d    %10d %10d %10d" %(bytes[i], mintime[i], avgtime[i], maxtime[i]) 
225
226
227  Tbw, Tlat, varest = linfit(bytes, mintime)
228  print "\nLinear regression on best timings (t = t_l + t_b * bytes):\n",
229  print "  t_b = %f\n  t_l = %f" %(Tbw,Tlat)
230  print "  Estimated relative variance = %.9f\n" %varest
231       
232  print "Estimated bandwith (1/t_b):  %.3f Mb/s" %(1.0/Tbw)   
233  print "Estimated latency:           %d micro s" %int(mintime[0]-bytes[0]*Tbw) 
234
235   
236pypar.Finalize()
237
238
239
240
241 
242 
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