Skip to content
Snippets Groups Projects
Select Git revision
  • 397c60fb29769e11c59773a9ca2c0c0b21bc93a9
  • main default
  • tests
3 results

download_server.py

Blame
    • tools.py 4.17 KiB
    1
    2
    3
    4
    5
    6
    7
    8
    9
    10
    11
    12
    13
    14
    15
    16
    17
    18
    19
    20
    21
    22
    23
    24
    25
    26
    27
    28
    29
    30
    31
    32
    33
    34
    35
    36
    37
    38
    39
    40
    41
    42
    43
    44
    45
    46
    47
    48
    49
    50
    51
    52
    53
    54
    55
    56
    57
    58
    59
    60
    61
    62
    63
    64
    65
    66
    67
    68
    69
    70
    71
    72
    73
    74
    75
    76
    77
    78
    79
    80
    81
    82
    83
    84
    85
    86
    87
    88
    89
    90
    91
    92
    93
    94
    95
    96
    97
    98
    99
    100
    101
    102
    103
    104
    105
    106
    107
    108
    109
    110
    111
    112
    113
    114
    115
    116
    117
    118
    119
    120
    121
    122
    123
    124 
    

    

    

    import argparse
import re
import math

#--------------------------------------------------------------------------
# Cmd line parsing 
#--------------------------------------------------------------------------

def cmdLineParsing():
    n1 = 256
    n2 = 256
    n3 = 256
    nb_threads = 8
    reps = 100
    cbx = 32
    cby = 32
    cbz = 32

    parser = argparse.ArgumentParser()
    parser.add_argument("--n1", help="n1", default=n1, type=int)
    parser.add_argument("--n2", help="n1", default=n2, type=int)
    parser.add_argument("--n3", help="n1", default=n3, type=int)
    parser.add_argument("--thds", help="Number of threads", default=nb_threads, type=int)
    parser.add_argument("--reps", help="Number of reps", default=reps, type=int)
    parser.add_argument("--cbx", help="n1 Thread block size", default=cbx, type=int)
    parser.add_argument("--cby", help="n2 Thread block size", default=cby, type=int)
    parser.add_argument("--cbz", help="n3 Thread block size", default=cbz, type=int)

    args = parser.parse_args()

    return args.n1, args.n2, args.n3, args.thds, args.reps, args.cbx, args.cby, args.cbz


#-----------------------------------------------------------------
# Extracting function
#-----------------------------------------------------------------

def commandLineExtract(commandLineOutput):
    """Extract time, throughput and GFlops from the mpirun execution

    Args:
        commandLineOutput (string): Corresponds to the command line output of the exeFile execution

    Returns:
        list[float]: List of executions times
        list[float]: List of executions throughputs
        list[float]: List of executions Gflops
        list[list]:
            list[float]: [time, throughput, gflop] Executions caracteristics

    """

    # Initialize outputs
    times = []
    throughputs = []
    gflops = []
    byRun = []

    # Setup for one execution
    run = []

    # Extract caracteristics
    for line in str(commandLineOutput.stdout,'utf-8').split('\n'):
        # Extract time
        if "time" in line:
            # Find float in line
            time = float(re.findall("\d+\.\d+", line)[0])
            times.append(time)
            run.append(time)

        # Extract troughput speed
        if "throughput" in line:
            # Find float in line
            throughput = float(re.findall("\d+\.\d+", line)[0])
            throughputs.append(throughput)
            run.append(throughput)

        if "flops" in line:
            # Find GFlops in line
            gflop = float(re.findall("\d+\.\d+", line)[0])
            gflops.append(gflop)
            run.append(gflop)
            byRun.append(run)

            # Reset execution caracteristics
            run = []

    return times, throughputs, gflops, byRun


#-----------------------------------------------------------------
# Add pheromones function
#-----------------------------------------------------------------

def add_pheromones(tau, paths, costs, Q, n1_size, n2_size, n3_size, n_cbx, n_cby):
    """Computing of the pheromon matrix and the cost of each path.

    Args:
        tau (np.array): Pheromon matrix
        paths (np.array): Array of the paths taken by the ants: paths[i]=(cb_x//16,cb_y,cb_z)
        costs (np.array): Column array containing the costs.
        Q (float): quantity of pheromones added by an ant on an edge
        n1_size (int): First dimension of the problem
        n2_size (int): Second dimension of the problem
        n3_size (int): Third dimension of problem
        n_cbx (int): First dimension of the cache
        n_cby (int): Second dimension of the cache

    Returns:
        (np.array): the updated pheromon matrix
    """

    for i in range(len(costs)):
        p = paths[i, :]
        cost = costs[i, 0]
        tau[0,p[0]] += Q*(-1)*cost
        tau[p[0], p[1] + n1_size] += Q*(-1)*cost
        tau[p[1] + n1_size, p[2] + n1_size + n2_size] += Q*(-1)*cost
        tau[p[2] + n1_size + n2_size, p[3] + n1_size + n2_size + n3_size] += Q*(-1)*cost
        tau[p[3] + n1_size + n2_size + n3_size, p[4] + n1_size + n2_size + n3_size + n_cbx] += Q*(-1)*cost
        tau[p[4] + n1_size + n2_size + n3_size + n_cbx, p[5] + n1_size + n2_size + n3_size + n_cbx + n_cby] += Q*(-1)*cost

    return tau