Beispiel #1
0
def create_global_array(gatype):
    if NEW_API:
        g_a = ga.create_handle()
        ga.set_data(g_a, [n,n], gatype)
        ga.set_array_name(g_a, 'a')
        if USE_RESTRICTED:
            num_restricted = nproc/2 or 1
            restricted_list = np.arange(num_restricted) + num_restricted/2
            ga.set_restricted(g_a, restricted_list)
        if BLOCK_CYCLIC:
            if USE_SCALAPACK_DISTR:
                if nproc % 2 == 0:
                    ga.error('Available procs must be divisible by 2',nproc)
                ga.set_block_cyclic_proc_grid(g_a, block_size, proc_grid)
            else:
                ga.set_block_cyclic(g_a, block_size)
        if MIRROR:
            p_mirror = ga.pgroup_get_mirror()
            ga.set_pgroup(g_a, p_mirror)
        ga.allocate(g_a)
    else:
        if MIRROR:
            p_mirror = ga.pgroup_get_mirror()
            ga.create_config(gatype, (n,n), 'a', None, p_mirror)
        else:
            g_a = ga.create(gatype, (n,n), 'a')
    if 0 == g_a:
        ga.error('ga.create failed')
    if MIRROR:
        lproc = me - ga.cluster_procid(inode, 0)
        lo,hi = ga.distribution(g_a, lproc)
    else:
        lo,hi = ga.distribution(g_a, me)
    ga.sync()
    return g_a
Beispiel #2
0
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.'
Beispiel #3
0
def main():
    if 0 == me:
        if MIRROR:
            print ' Performing tests on Mirrored Arrays'
        print ' GA initialized'

    # note that MA is not used, so no need to initialize it
    # "import ga" registers malloc/free as memory allocators internally

    #if nproc-1 == me:
    if 0 == me:
        print 'using %d process(es) %d custer nodes' % (
                nproc, ga.cluster_nnodes())
        print 'process %d is on node %d with %d processes' % (
                me, ga.cluster_nodeid(), ga.cluster_nprocs(-1))

    # create array to force staggering of memory and uneven distribution
    # of pointers
    dim1 = MEM_INC
    mapc = [0]*nproc
    for i in range(nproc):
        mapc[i] = MEM_INC*i
        dim1 += MEM_INC*i
    g_s = ga.create_handle()
    ga.set_data(g_s, [dim1], ga.C_INT)
    ga.set_array_name(g_s, 's')
    ga.set_irreg_distr(g_s, mapc, [nproc])

    if MIRROR:
        if 0 == me:
            print '\nTESTING MIRRORED ARRAYS\n'

    # check support for single precision arrays
    if 0 == me:
        print '\nCHECKING SINGLE PRECISION\n'
    check_float()

    # check support for double precision arrays
    if 0 == me:
        print '\nCHECKING DOUBLE PRECISION\n'
    check_double()

    # check support for single precision complex arrays
    if 0 == me:
        print '\nCHECKING SINGLE COMPLEX\n'
    check_complex_float()

    # check support for double precision complex arrays
    if 0 == me:
        print '\nCHECKING DOUBLE COMPLEX\n'
    check_complex_double()

    # check support for integer arrays
    if 0 == me:
        print '\nCHECKING INT\n'
    check_int()

    # check support for long integer arrays
    if 0 == me:
        print '\nCHECKING LONG INT\n'
    check_long()

    if 0 == me:
        print '\nCHECKING Wrappers to Message Passing Collective ops\n'
    check_wrappers()

    # check if memory limits are enforced
    #check_mem(ma_heap*ga.nnodes())

    if 0 == me: ga.print_stats()
    if 0 == me: print ' '
    if 0 == me: print 'All tests successful'