ParaMonte Fortran 2.0.0
Parallel Monte Carlo and Machine Learning Library
See the latest version documentation.
pm_arrayShuffle Module Reference

This module contains procedures and generic interfaces for shuffling arrays of various types. More...

Data Types

interface  getShuffled
 Perform an unbiased random shuffling of the input array, known as the Knuth or Fisher-Yates shuffle, and generate and return the new reshuffled array. More...
 
interface  setShuffled
 Perform an unbiased random shuffling of the input array, known as the Knuth or Fisher-Yates shuffle. More...
 

Variables

character(*, SK), parameter MODULE_NAME = "@pm_arrayShuffle"
 

Detailed Description

This module contains procedures and generic interfaces for shuffling arrays of various types.

Benchmarks:


Benchmark :: The runtime performance of getShuffled vs. setShuffled

1program benchmark
2
3 use pm_kind, only: IK, LK, RK, SK
4 use iso_fortran_env, only: error_unit
5 use pm_bench, only: bench_type
6
7 implicit none
8
9 integer(IK) :: i
10 integer(IK) :: isize
11 integer(IK) :: fileUnit
12 integer(IK) , parameter :: NSIZE = 15_IK
13 integer(IK) , parameter :: NBENCH = 2_IK
14 integer(IK) :: arraySize(NSIZE)
15 real(RK) :: dummy = 0._RK
16 real(RK) , allocatable :: Array(:)
17 type(bench_type) :: bench(NBENCH)
18
19 bench(1) = bench_type(name = SK_"setShuffled", exec = setShuffled, overhead = setOverhead)
20 bench(2) = bench_type(name = SK_"getShuffled", exec = getShuffled, overhead = setOverhead)
21
22 arraySize = [( 2_IK**isize, isize = 1_IK, NSIZE )]
23
24 write(*,"(*(g0,:,' '))")
25 write(*,"(*(g0,:,' '))") "setShuffled() vs. getShuffled()"
26 write(*,"(*(g0,:,' '))")
27
28 open(newunit = fileUnit, file = "main.out", status = "replace")
29
30 write(fileUnit, "(*(g0,:,','))") "arraySize", (bench(i)%name, i = 1, NBENCH)
31
32 loopOverArraySize: do isize = 1, NSIZE
33
34 write(*,"(*(g0,:,' '))") "Benchmarking with size", arraySize(isize)
35
36 allocate(Array(arraySize(isize)))
37 call random_number(Array)
38 do i = 1, NBENCH
39 bench(i)%timing = bench(i)%getTiming(minsec = 0.07_RK)
40 end do
41 deallocate(Array)
42
43 write(fileUnit,"(*(g0,:,','))") arraySize(isize), (bench(i)%timing%mean, i = 1, NBENCH)
44
45 end do loopOverArraySize
46 write(*,"(*(g0,:,' '))") dummy
47 write(*,"(*(g0,:,' '))")
48
49 close(fileUnit)
50
51contains
52
53 !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
54 ! procedure wrappers.
55 !%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
56
57 subroutine setOverhead()
58 call finalize()
59 end subroutine
60
61 subroutine finalize()
62 dummy = dummy + Array(1)
63 end subroutine
64
65 subroutine setShuffled()
66 block
68 call setShuffled(Array)
69 call finalize()
70 end block
71 end subroutine
72
73 subroutine getShuffled()
74 block
76 Array = getShuffled(Array)
77 call finalize()
78 end block
79 end subroutine
80
81end program benchmark
Perform an unbiased random shuffling of the input array, known as the Knuth or Fisher-Yates shuffle,...
Perform an unbiased random shuffling of the input array, known as the Knuth or Fisher-Yates shuffle.
Generate and return an object of type timing_type containing the benchmark timing information and sta...
Definition: pm_bench.F90:574
This module contains procedures and generic interfaces for shuffling arrays of various types.
This module contains abstract interfaces and types that facilitate benchmarking of different procedur...
Definition: pm_bench.F90:41
This module defines the relevant Fortran kind type-parameters frequently used in the ParaMonte librar...
Definition: pm_kind.F90:268
integer, parameter RK
The default real kind in the ParaMonte library: real64 in Fortran, c_double in C-Fortran Interoperati...
Definition: pm_kind.F90:543
integer, parameter LK
The default logical kind in the ParaMonte library: kind(.true.) in Fortran, kind(....
Definition: pm_kind.F90:541
integer, parameter IK
The default integer kind in the ParaMonte library: int32 in Fortran, c_int32_t in C-Fortran Interoper...
Definition: pm_kind.F90:540
integer, parameter SK
The default character kind in the ParaMonte library: kind("a") in Fortran, c_char in C-Fortran Intero...
Definition: pm_kind.F90:539
This is the class for creating benchmark and performance-profiling objects.
Definition: pm_bench.F90:386

Example Unix compile command via Intel ifort compiler
1#!/usr/bin/env sh
2rm main.exe
3ifort -fpp -standard-semantics -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
4./main.exe

Example Windows Batch compile command via Intel ifort compiler
1del main.exe
2set PATH=..\..\..\lib;%PATH%
3ifort /fpp /standard-semantics /O3 /I:..\..\..\include main.F90 ..\..\..\lib\libparamonte*.lib /exe:main.exe
4main.exe

Example Unix / MinGW compile command via GNU gfortran compiler
1#!/usr/bin/env sh
2rm main.exe
3gfortran -cpp -ffree-line-length-none -O3 -Wl,-rpath,../../../lib -I../../../inc main.F90 ../../../lib/libparamonte* -o main.exe
4./main.exe

Postprocessing of the benchmark output
1#!/usr/bin/env python
2
3import matplotlib.pyplot as plt
4import pandas as pd
5import numpy as np
6
7fontsize = 14
8
9methods = ["setShuffled", "getShuffled"]
10
11df = pd.read_csv("main.out")
12
13
16
17ax = plt.figure(figsize = 1.25 * np.array([6.4,4.6]), dpi = 200)
18ax = plt.subplot()
19
20for method in methods:
21 plt.plot( df["arraySize"].values
22 , df[method].values
23 , linewidth = 2
24 )
25
26plt.xticks(fontsize = fontsize)
27plt.yticks(fontsize = fontsize)
28ax.set_xlabel("Array Size", fontsize = fontsize)
29ax.set_ylabel("Runtime [ seconds ]", fontsize = fontsize)
30ax.set_title("setShuffled() vs. getShuffled().\nLower is better.", fontsize = fontsize)
31ax.set_xscale("log")
32ax.set_yscale("log")
33plt.minorticks_on()
34plt.grid(visible = True, which = "both", axis = "both", color = "0.85", linestyle = "-")
35ax.tick_params(axis = "y", which = "minor")
36ax.tick_params(axis = "x", which = "minor")
37ax.legend ( methods
38 #, loc='center left'
39 #, bbox_to_anchor=(1, 0.5)
40 , fontsize = fontsize
41 )
42
43plt.tight_layout()
44plt.savefig("benchmark.getShuffled_vs_setShuffled.runtime.png")
45
46
49
50ax = plt.figure(figsize = 1.25 * np.array([6.4,4.6]), dpi = 200)
51ax = plt.subplot()
52
53plt.plot( df["arraySize"].values
54 , np.ones(len(df["arraySize"].values))
55 #, linestyle = "--"
56 , linewidth = 2
57 )
58plt.plot( df["arraySize"].values
59 , df["getShuffled"].values / df["setShuffled"].values
60 , linewidth = 2
61 )
62
63plt.xticks(fontsize = fontsize)
64plt.yticks(fontsize = fontsize)
65ax.set_xlabel("Array Size", fontsize = fontsize)
66ax.set_ylabel("Runtime compared to setShuffled()", fontsize = fontsize)
67ax.set_title("getShuffled() to setShuffled() Runtime Ratio.\nLower means faster. Lower than 1 means faster than setShuffled().", fontsize = fontsize)
68ax.set_xscale("log")
69#ax.set_yscale("log")
70plt.minorticks_on()
71plt.grid(visible = True, which = "both", axis = "both", color = "0.85", linestyle = "-")
72ax.tick_params(axis = "y", which = "minor")
73ax.tick_params(axis = "x", which = "minor")
74ax.legend ( ["setShuffled()", "getShuffled()", "Direct Method"]
75 #, bbox_to_anchor = (1, 0.5)
76 #, loc = "center left"
77 , fontsize = fontsize
78 )
79
80plt.tight_layout()
81plt.savefig("benchmark.getShuffled_vs_setShuffled.runtime.ratio.png")

Visualization of the benchmark output

Benchmark moral
  1. The procedures under the generic interface getShuffled are functions while the procedures under the generic interface setShuffled are subroutines.
    The current implementation of the functional interface requires making a copy of the input array that is subsequently passed to the subroutine interface for random shuffling.
    As such, the observed performance degradation is expected.
    Note that an extra copy of the output array to the user-specified object is also needed, making the functional interface two-copies more expensive than the subroutine interface.
See also
pm_arrayRemap
pm_arrayChange
pm_arrayChoice
pm_arrayShuffle
pm_distUnif
Test:
test_pm_arrayShuffle


Final Remarks


If you believe this algorithm or its documentation can be improved, we appreciate your contribution and help to edit this page's documentation and source file on GitHub.
For details on the naming abbreviations, see this page.
For details on the naming conventions, see this page.
This software is distributed under the MIT license with additional terms outlined below.

  1. If you use any parts or concepts from this library to any extent, please acknowledge the usage by citing the relevant publications of the ParaMonte library.
  2. If you regenerate any parts/ideas from this library in a programming environment other than those currently supported by this ParaMonte library (i.e., other than C, C++, Fortran, MATLAB, Python, R), please also ask the end users to cite this original ParaMonte library.

This software is available to the public under a highly permissive license.
Help us justify its continued development and maintenance by acknowledging its benefit to society, distributing it, and contributing to it.

Author:
Amir Shahmoradi, September 1, 2017, 12:20 AM, Institute for Computational Engineering and Sciences (ICES), The University of Texas Austin

Variable Documentation

◆ MODULE_NAME

character(*,SK), parameter pm_arrayShuffle::MODULE_NAME = "@pm_arrayShuffle"

Definition at line 67 of file pm_arrayShuffle.F90.