def check_fence_and_lock(gatype): if 0 == me: print '> Checking ga.fence and ga.lock', g_a = create_global_array(gatype) ga.zero(g_a) if not ga.create_mutexes(1): ga.error('ga.create_mutexes failed') if n < 2: ga.error('insufficient n to test ga.fence', n) ga.lock(0) a = ga.get(g_a) # get original values a[:,0] += 1 # add my contribution # need to use fence to assure that coms complete before leaving # critical section ga.init_fence() ga.put(g_a, a) ga.fence() ga.unlock(0) if not ga.destroy_mutexes(): ga.error('mutex not destroyed') ga.sync() if 0 == me: a = ga.get(g_a) if not np.all(a[:,0] == nproc): ga.error('fence failed') if 0 == me: print 'OK'
def check_zero(gatype): if 0 == me: print '> Checking zero ...', g_a = create_global_array(gatype) ga.zero(g_a) a = ga.get(g_a) if not np.all(a == 0): ga.error('ga.zero failed') if 0 == me: print 'OK' ga.destroy(g_a)
def test2D(): n = 1024 buf = np.zeros((n,n), dtype=np.float64) chunk = np.asarray([1,3,4,9,16,24,30,48,64,91,128,171,256,353,440,512]) g_a = ga.create(ga.C_DBL, (n,n), 'a') if 0 == g_a: ga.error('ga.create failed') buf[:] = 0.01 ga.zero(g_a) if 0 == me: print (' Performance of GA get, put & acc' ' for square sections of array[%d,%d]' % (n,n)) lo,hi = ga.distribution(g_a, me) # local ops TestPutGetAcc(g_a, n, chunk, buf, lo, hi, True) # remote ops TestPutGetAcc(g_a, n, chunk, buf, lo, hi, False)
def test2D(): n = 1024 buf = np.zeros((n, n), dtype=np.float64) chunk = np.asarray( [1, 3, 4, 9, 16, 24, 30, 48, 64, 91, 128, 171, 256, 353, 440, 512]) g_a = ga.create(ga.C_DBL, (n, n), 'a') if 0 == g_a: ga.error('ga.create failed') buf[:] = 0.01 ga.zero(g_a) if 0 == me: print( ' Performance of GA get, put & acc' ' for square sections of array[%d,%d]' % (n, n)) lo, hi = ga.distribution(g_a, me) # local ops TestPutGetAcc(g_a, n, chunk, buf, lo, hi, True) # remote ops TestPutGetAcc(g_a, n, chunk, buf, lo, hi, False)
def test1D(): n = 1024*1024 buf = np.zeros(n/4, dtype=np.float64) chunk = np.asarray([1,9,16,81,256,576,900,2304,4096,8281, 16384,29241,65536,124609,193600,262144]) g_a = ga.create(ga.C_DBL, (n,), 'a') if 0 == g_a: ga.error('ga.create failed') buf[:] = 0.01 ga.zero(g_a) if 0 == me: print '' print '' print '' print (' Performance of GA get, put & acc' ' for 1-dimensional sections of array[%d]' % n) lo,hi = ga.distribution(g_a, me) # local ops TestPutGetAcc1(g_a, n, chunk, buf, lo, hi, True) # remote ops TestPutGetAcc1(g_a, n, chunk, buf, lo, hi, False)
def check_accumulate_overlap(gatype): if 0 == me: print '> Checking overlapping accumulate ...', g_a = create_global_array(gatype) ga.zero(g_a) ga.acc(g_a, [1], (n/2,n/2), (n/2+1,n/2+1), 1) ga.sync() if MIRROR: if 0 == iproc: x = abs(ga.get(g_a, (n/2,n/2), (n/2+1,n/2+1))[0,0] - lprocs) if not 0 == x: ga.error('overlapping accumulate failed -- expected %s got %s'%( x, lprocs)) else: if 0 == me: x = abs(ga.get(g_a, (n/2,n/2), (n/2+1,n/2+1))[0,0] - nproc) if not 0 == x: ga.error('overlapping accumulate failed -- expected %s got %s'%( x, nproc)) if 0 == me: print 'OK' ga.destroy(g_a)
def test1D(): n = 1024 * 1024 buf = np.zeros(n / 4, dtype=np.float64) chunk = np.asarray([ 1, 9, 16, 81, 256, 576, 900, 2304, 4096, 8281, 16384, 29241, 65536, 124609, 193600, 262144 ]) g_a = ga.create(ga.C_DBL, (n, ), 'a') if 0 == g_a: ga.error('ga.create failed') buf[:] = 0.01 ga.zero(g_a) if 0 == me: print '' print '' print '' print( ' Performance of GA get, put & acc' ' for 1-dimensional sections of array[%d]' % n) lo, hi = ga.distribution(g_a, me) # local ops TestPutGetAcc1(g_a, n, chunk, buf, lo, hi, True) # remote ops TestPutGetAcc1(g_a, n, chunk, buf, lo, hi, False)
nprocs = ga.nnodes() myrank = ga.nodeid() g_pi = ga.create(ga.C_DBL, [1]) one_time = False if len(sys.argv) == 2: n = int(sys.argv[1]) one_time = True while True: if not one_time: if myrank == 0: n = get_n() n = ga.brdcst(n) else: n = ga.brdcst(0) if n == 0: break ga.zero(g_pi) mypi = comp_pi(n, myrank, nprocs) ga.acc(g_pi, mypi) ga.sync() if myrank == 0: pi = ga.get(g_pi)[0] prn_pi(pi, PI) if one_time: break ga.destroy(g_pi)
v = np.dot(a, b) val = int(np.abs(np.sum(c - v)) > 0.0001) val = ga.gop_add(val) return val == 0 if __name__ == '__main__': if nproc > MULTIPLIER**3: if 0 == me: print "You must use less than %s processors" % (MULTIPLIER**3 + 1) else: g_a = ga.create(ga.C_DBL, [N, N]) g_b = ga.create(ga.C_DBL, [N, N]) g_c = ga.create(ga.C_DBL, [N, N]) g_counter = ga.create(ga.C_INT, [1]) ga.zero(g_counter) # put some fake data into input arrays A and B if me == 0: ga.put(g_a, np.random.random(N * N)) ga.put(g_b, np.random.random(N * N)) ga.sync() if me == 0: print "srumma...", srumma(g_a, g_b, g_c, CHUNK_SIZE, MULTIPLIER, g_counter) if me == 0: print "done" if me == 0: print "verifying using ga.gemm...", ok = verify_using_ga(g_a, g_b, g_c) if me == 0: if ok:
def main(): # TODO there's got to be a loopless, more pythonic way to do this ii = 0 for i in range(num1*num1): ii += 1 if ii > num1: ii = 0 h0[i] = ii # compute times assuming 500 mflops and 5 second target time # ntimes = max(3.0, 5.0/(4.0-9*num**3)) ntimes = 5 for ii in range(howmany): num_m = nums_m[ii] num_n = nums_n[ii] num_k = nums_k[ii] a = 0.5/(num_m*num_n) if num_m > nummax or num_n > nummax or num_k > nummax: ga.error('Insufficient memory: check nummax') if BLOCK_CYCLIC: block_size = [128,128] g_c = ga.create_handle() ga.set_data(g_c, (num_m,num_n), ga.C_DBL) ga.set_array_name(g_c, 'g_c') ga.set_block_cyclic(g_c, block_size) if not ga.allocate(g_c): ga.error('create failed') block_size = [128,128] g_b = ga.create_handle() ga.set_data(g_b, (num_k,num_n), ga.C_DBL) ga.set_array_name(g_b, 'g_b') ga.set_block_cyclic(g_b, block_size) if not ga.allocate(g_b): ga.error('create failed') block_size = [128,128] g_a = ga.create_handle() ga.set_data(g_a, (num_m,num_k), ga.C_DBL) ga.set_array_name(g_a, 'g_a') ga.set_block_cyclic(g_a, block_size) if not ga.allocate(g_a): ga.error('create failed') else: g_a = ga.create(ga.C_DBL, (num_m,num_k), 'g_a') g_b = ga.create(ga.C_DBL, (num_k,num_n), 'g_b') g_c = ga.create(ga.C_DBL, (num_m,num_n), 'g_c') for handle in [g_a,g_b,g_c]: if 0 == handle: ga.error('create failed') # initialize matrices A and B if 0 == me: load_ga(g_a, h0, num_m, num_k) load_ga(g_b, h0, num_k, num_n) ga.zero(g_c) ga.sync() if 0 == me: print '\nMatrix Multiplication C = A[%d,%d] x B[%d,%d]\n' % ( num_m, num_k, num_k, num_n) print ' %4s %12s %12s %7s %7s'%( "Run#", "Time (seconds)", "mflops/proc", "A trans", "B trans") avg_t[:] = 0 avg_mf[:] = 0 for itime in range(ntimes): for i in range(ntrans): ga.sync() ta = transa[i] tb = transb[i] t1 = time.time() ga.gemm(ta,tb,num_m,num_n,num_k,1,g_a,g_b,0,g_c) t1 = time.time() - t1 if 0 == me: mf = 2*num_m*num_n*num_k/t1*10**-6/nproc avg_t[i] += t1 avg_mf[i] += mf print ' %4d %12.4f %12.1f %7s %7s'%( itime+1, t1, mf, ta, tb) if VERIFY and itime == 0: verify_ga_gemm(ta, tb, num_m, num_n, num_k, 1.0, g_a, g_b, 0.0, g_c) if 0 == me: print '' for i in range(ntrans): print 'Average: %12.4f seconds %12.1f mflops/proc %s %s'%( avg_t[i]/ntimes, avg_mf[i]/ntimes, transa[i], transb[i]) if VERIFY: print 'All ga.gemms are verified...O.K.'
def convergence_test_L2(g_a, g_b): # compute L2 norm of change # subtract g_b from g_a, results stored in g_b ga.add(g_a, g_b, g_b, beta=-1) # compute elementwise dot product (i.e. treats N-d arrays as vectors) value = ga.dot(g_b, g_b) if DEBUG: print_sync(value) return value < EPSILON # create GA, distribute entire rows g_a = ga.create_ghosts(ga.C_FLOAT, (dim,dim), (1,1), chunk=(0,dim)) # create a duplicate GA for the convergence test g_b = ga.duplicate(g_a) ga.zero(g_a) (rlo,clo),(rhi,chi) = ga.distribution(g_a) def set_boundary_conditions_put(g_a): # process 0 initializes global array # this would only set the initial conditions since we are putting an entire # zeros array with the outer elements changed if rank == 0: a = np.zeros((dim,dim), dtype=np.float32) a[0,:] = 100 #top row a[:,0] = 75 #left column a[:,a.shape[0] - 1] = 50 #right column ga.put(g_a, a) ga.sync() def set_boundary_conditions_access(g_a):
c = ga.get(g_c) v = np.dot(a,b) val = int(np.abs(np.sum(c-v))>0.0001) val = ga.gop_add(val) return val == 0 if __name__ == '__main__': if nproc > MULTIPLIER**3: if 0 == me: print "You must use less than %s processors" % (MULTIPLIER**3+1) else: g_a = ga.create(ga.C_DBL, [N,N]) g_b = ga.create(ga.C_DBL, [N,N]) g_c = ga.create(ga.C_DBL, [N,N]) g_counter = ga.create(ga.C_INT, [1]) ga.zero(g_counter) # put some fake data into input arrays A and B if me == 0: ga.put(g_a, np.random.random(N*N)) ga.put(g_b, np.random.random(N*N)) ga.sync() if me == 0: print "srumma...", srumma(g_a, g_b, g_c, CHUNK_SIZE, MULTIPLIER, g_counter) if me == 0: print "done" if me == 0: print "verifying using ga.gemm...", ok = verify_using_ga(g_a, g_b, g_c) if me == 0: if ok: