Examples

1. simple

This program demonstrates the use of sprng on one processor without explicit initialization.

Note that we have included the SPRNG header file We have also defined the macro SIMPLE_SPRNG before including the SPRNG header file in order to invoke the simple interface.

When sprng is called the first time, it initializes a default stream using default parameters, since no explicit initialization has been performed. It then returns double precision random numbers in [0,1).

Code:

Simple Interface Default/Pointer
Checking Interface
C FORTRAN Not Available

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o simple-simple simple-simple.c -L../lib -llcg

Note: -64 indicates the 64 bit compilation available on the Power Challenge.

cc is the C compiler.

Output: 

sprng/EXAMPLES:sif% simple-simple
 Printing 3 random numbers in [0,1):
0.580114
0.740295
0.892874

2. sprng

This program demonstrates the use of sprng, isprng, init_sprng and print_sprng on one process.

Note that we have included the SPRNG header file.

First we initialize a random number stream. The value of the seed is defined to be 985456376. We call print_sprng immediately after initialization so that we can record the particular stream we obtained, for later reference.

sprng is next called to return double precision random numbers in [0,1) and then isprng is called to return random integers in [0,231).

Code:

Simple Interface Default/Pointer
Checking Interface
C FORTRAN C C++ FORTRAN

Compilation: Example compilation on the SGI Power Challenge

f77 -DPOINTER_SIZE=8 -64 -I../include -o sprngf sprngf.F -L../lib -llcg

Note: -DPOINTER_SIZE=8 indicates that the pointer size is 8 bytes, rather than the default 4 bytes assumed by SPRNG.

f77 is the FORTRAN 77 compiler.

Output: 

sprng/EXAMPLES:sif% sprngf
 Print information about new stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

 Printing 3 random numbers in [0,1):
0.707488
0.664048
0.005616
 Printing 3 random integers in [0,2^31):
      1873949618
      1484742006
       602016304

3. sprng_mpi

This program demonstrates the use of sprng with multiple processes.

Note that we have included the SPRNG and MPI header files at the beginning.

First we initialize MPI.

We then initialize a random number stream. The value of the seed is defined to be 985456376. We call print_sprng immediately after initialization so that we can record the particular stream we obtained, for later reference.

sprng is next called to return double precision random numbers in [0,1).

Code:

Simple Interface Default/Pointer
Checking Interface
C C++ FORTRAN C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

CC -64 -I../include -o sprng-simple_mpi sprng-simple_mpi.C -L../lib -llcg -L/usr/lib64 -lmpi

Note: CC is the C++ compiler.

Output: 

sprng/EXAMPLES:sif% mpirun -np 2 sprng-simple_mpi
Process 0, print information about stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

Process 0, random number 1: 0.70748766363408
Process 0, random number 2: 0.66404841879710
Process 0, random number 3: 0.00561565119362
Process 1, print information about stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863259
        multiplier = 44485709377909

Process 1, random number 1: 0.99144237784703
Process 1, random number 2: 0.15098918187292
Process 1, random number 3: 0.09757740755008

Note that the order in which the output is printed may differ.

4. fsprng_mpi

This program demonstrates the use of the single precision version of sprng with one stream per process.

Note that we have included the SPRNG and MPI header files sprng.h and mpi.h respectively at the beginning. Before including the SPRNG header file, we have defined the macro FLOAT_GEN, which results in single precision random numbers being generated by calls to sprng.

First we initialize MPI.

We then initialize a random number stream. The value of the seed is defined to be 985456376. We call print_sprng immediately after initialization so that we can record the particular stream we obtained, for later reference.

sprng is next called to return single precision random numbers in [0,1).

Code:

Simple Interface Default/Pointer
Checking Interface
C FORTRAN C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

f90 -DPOINTER_SIZE=8 -64 -I../include -o fsprngf_mpi fsprngf_mpi.F -L../lib -llcg -L/usr/lib64 -lmpi

Note: f90 is the FORTRAN 90 compiler.

Output: 

sprng/EXAMPLES:sif% mpirun -np 2 fsprngf_mpi
Process 0: Print information about stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

Process 0, random number 1: 0.707488
Process 0, random number 2: 0.664048
Process 0, random number 3: 0.005616
Process 1: Print information about stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863259
        multiplier = 44485709377909

Process 1, random number 1: 0.991442
Process 1, random number 2: 0.150989
Process 1, random number 3: 0.097577

Note that the order in which the output is printed may differ.

5. seed

This program demonstrates the use of make_sprng_seed on one processor.

Note that we have included the SPRNG header file at the beginning.

First we initialize a random number stream. The value of a seed is obtained from a call to make_sprng_seed and is based on system date and time information. We call print_sprng immediately after initialization so that we can record the particular stream we obtained, for later reference.

sprng is next called to return double precision random numbers in [0,1).

Code:

Simple Interface Default/Pointer
Checking Interface
C FORTRAN C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o seed-simple seed-simple.c -L../lib -llcg

Output: 

sprng/EXAMPLES:sif% seed-simple
 Printing information about new stream

Linear Congruential Generator

        seed = 178783069, prime = 11863279
        multiplier = 44485709377909

 Printing 3 random numbers in [0,1):
0.856970
0.110647
0.795213

6. seed_mpi

This program demonstrates the use of make_sprng_seed with the MPI version of SPRNG in order to obtain the same seed in each process.

Note that we have included the SPRNG and MPI header files at the beginning. Before including the SPRNG header file, we have defined the macro USE_MPI, which enables SPRNG to make MPI calls to ensure that the same seed is obtained on each process.

First we initialize MPI.

We then initialize a random number stream. The value of the seed is obtained from a call to make_sprng_seed. This function makes MPI calls to ensure that the same seed is returned in each process, assuming that the MPI version of SPRNG has been installed. We call print_sprng immediately after initialization so that we can record the particular stream we obtained, for later reference.

sprng is next called to return double precision random numbers in [0,1).

Code:

Simple Interface Default/Pointer
Checking Interface
C FORTRAN C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o seed-simple_mpi seed-simple_mpi.c -L../lib -llcg -L/usr/lib64 -lmpi

Output: 

sprng/EXAMPLES:sif% mpirun -np 2 seed-simple_mpi
Process 0: seed =        837321565
Process 1: seed =        837321565
Process 0: Print information about stream:

Linear Congruential Generator

        seed = 837321565, prime = 11863279
        multiplier = 44485709377909

process 0, random number 1: 0.732603
process 0, random number 2: 0.753095
process 0, random number 3: 0.084726
Process 1: Print information about stream:

Linear Congruential Generator

        seed = 837321565, prime = 11863259
        multiplier = 44485709377909

process 1, random number 1: 0.200456
process 1, random number 2: 0.445652
process 1, random number 3: 0.576297

Note that the order in which the output is printed may differ.

7. checkpoint

This program demonstrates the use of pack_sprng and unpack_sprng for check-pointing. This program prints a few random numbers and then stores the state of the computation in a file. If users wish to continue their computations from the previous state, then they can have this program read the state of the computations from this file. The user is first prompted for the name of the output file. Then the user is asked for the name of the input file. If the user wishes to start a new run, then he should enter 9 at this stage, in which case the program initializes a random number stream instead of reading it from a file.

Note that we have included the SPRNG header file sprng.h at the beginning.

First we initialize a random number stream, if this is a new run. The value of the seed is defined to be 985456376. We call print_sprng immediately after initialization so that we can record the particular stream we obtained, for later reference.

If this is the continuation of a previous run, then we read in the state of a stream from the input file, and unpack it to obtain a random number stream.

sprng is next called to return double precision random numbers in [0,1).

Finally, we pack the state of the stream into an array and store the contents of this array into the output file.

Code:

Simple Interface Default/Pointer
Checking Interface
C FORTRAN C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o checkpoint-simple checkpoint-simple.c -L../lib -llcg

Output: 

sprng/EXAMPLES:sif% checkpoint
Enter name of file to store final state of the stream:
temp
Enter name of file to read from:
        (enter 9 for a new run)
9
 Printing 5 random numbers in [0,1): 
1  0.707488
2  0.664048
3  0.005616
4  0.872626
5  0.691387
sprng/EXAMPLES:sif% checkpoint
Enter name of file to store final state of the stream:
temp
Enter name of file to read from:
        (enter 9 for a new run)
temp
 Printing 5 random numbers in [0,1): 
1  0.280336
2  0.005228
3  0.533545
4  0.710482
5  0.891603

8. message_mpi

This program demonstrates the use of pack_sprng and unpack_sprng for passing the state of a stream from one processor to another.

Note that we have included the SPRNG and MPI header files at the beginning.

First we initialize MPI.

We then initialize a random number stream on process 0. The value of the seed is defined to be 985456376. We call print_sprng immediately after initialization so that we can record the particular stream we obtained, for later reference.

sprng is next called by process 0 to return double precision random numbers in [0,1).

Process 0 then packs the state of the stream into an array and sends it to process 1, which unpacks it and prints a few more random numbers from that stream. In this process, the original default stream on process 1 is over-written by the unpacked stream.

Code:

Simple Interface Default/Pointer
Checking Interface
C FORTRAN C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o message-simple_mpi message-simple_mpi.c -L../lib -llcg -L/usr/lib64 -lmpi

Output: 

sprng/EXAMPLES:sif% mpirun -np 2 message-simple_mpi
Process 0: Print information about stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

Process 0: Print 2 random numbers in [0,1):
Process 0: 0.707488
Process 0: 0.664048
 Process 0 sends stream to process 1
 Process 1 has received the packed stream
Process 1: Print information about stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

 Process 1 prints 2 numbers from received stream:
Process 1: 0.005616
Process 1: 0.872626

Note that the order in which the output is printed may differ.

9. 2streams_mpi

This program demonstrates the use of multiple streams on each process.

Note that we have included the SPRNG and MPI header files at the beginning.

First we initialize MPI and determine the number of processes and the rank of the local process.

We then initialize a random number stream. The value of the seed is defined to be 985456376. We shall have two streams per process, but is only one of these streams will be distinct. The other stream will be identical on each process. This is useful in situations in which we would like all the processes to take the same decision based on a random number. Thus the number of distinct streams is one more than the total number of processor, resulting in nstreams = nprocs + 1. For the distinct stream on each process, we initialize it with stream number as the rank of the local process, myid. The common stream is initialized with the stream number nprocs.

sprng is next called for each stream. It returns a double precision random numbers in [0,1) with the stream ID as its argument.

Finally, we free the memory used to store the states of the two streams by calls to free_sprng.

Code:

Simple Interface Default/Pointer
Checking Interface
Not Available C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o 2streams_mpi 2streams_mpi.c -L../lib -llcg -L/usr/lib64 -lmpi

Output: 

sprng/EXAMPLES:sif% mpirun -np 2 2streams_mpi
Process 0: Print information about new stream

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

Process 0: This stream is identical on all processes

Linear Congruential Generator

        seed = 985456376, prime = 11863253
        multiplier = 44485709377909

Process 0, random number (distinct stream) 1: 0.707488
Process 0, random number (distinct stream) 2: 0.664048
Process 0, random number (shared stream) 1: 0.700906
Process 0, random number (shared stream) 2: 0.602204
Process 1: Print information about new stream

Linear Congruential Generator

        seed = 985456376, prime = 11863259
        multiplier = 44485709377909

Process 1: This stream is identical on all processes

Linear Congruential Generator

        seed = 985456376, prime = 11863253
        multiplier = 44485709377909

Process 1, random number (distinct stream) 1: 0.991442
Process 1, random number (distinct stream) 2: 0.150989
Process 1, random number (shared stream) 1: 0.700906
Process 1, random number (shared stream) 2: 0.602204

Note that the order in which the output is printed may differ.

10. spawn

This program demonstrates the use of spawn_sprng.

Note that we have included the SPRNG header file at the beginning.

First we initialize a random number stream. The value of the seed is defined to be 985456376. Since there is only one stream, the number of streams nstreams = 1 and the stream number streamnum = 0. stream stores the returned ID of the initialized stream. We call print_sprng immediately after initialization so that we can record the particular stream we obtained, for later reference.

sprng is next called to return double precision random numbers in [0,1), with the stream ID as its argument.

We next spawn two streams from stream. Their ID's are stored in an array allocated by sprng. The variable new points to this array. We print information about the newly spawned streams, and then print a few random numbers from the second stream spawned.

Finally, we free the memory used to store the states of the streams by calls to free_sprng.

Code:

Simple Interface Default/Pointer
Checking Interface
Not Available C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o spawn spawn.c -L../lib -llcg

Output: 

sprng/EXAMPLES:sif% spawn
 Print information about stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

 Printing 2 random numbers in [0,1):
0.707488
0.664048
 Spawned two streams
 Information on first spawned stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863259
        multiplier = 44485709377909

 Information on second spawned stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863253
        multiplier = 44485709377909

 Printing 2 random numbers from second spawned stream:
0.700906
0.602204

11. invalid_ID

This program demonstrates the handling of invalid pointers in the interface with pointer checking.

Note that we have included the SPRNG header file sprng.h at the beginning. We have also defined the macro CHECK_POINTERS before including the SPRNG header file in order to invoke the interface with pointer checking.

First we initialize a random number stream. The value of the seed is defined to be 985456376. Since there is only one stream, the number of streams nstreams = 1 and the stream number streamnum = 0. stream stores the returned ID of the initialized stream. We call print_sprng immediately after initialization so that we can record the particular stream we obtained, for later reference.

sprng is next called to return double precision random numbers in [0,1), with the stream ID as its argument.

Finally, we free the memory used to store the state of the stream by a call to free_sprng.

we then try to use the freed stream again, which is an incorrect usage. sprng returns -1.0 due to the invalid stream being passed as an argument.

Code:

Simple Interface Pointer
Checking Interface
Not Available C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o invalid_ID invalid_ID.c -L../lib -llcg

Output: 

sprng/EXAMPLES:sif% invalid_ID
Print information about random number stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

Printing 3 random numbers in [0,1):
0.707488
0.664048
0.005616
Expect a SPRNG error message on the use of an invalid stream ID
ERROR: Invalid generator ID 10014ed8
sprng returns -1.000000 on being given an invalid stream ID

Note that the incorrect ID, 10017258, may vary.

12. convert

This program demonstrates converting user code to call SPRNG instead of the original random number generator myrandom.

Note that we have included the SPRNG header file at the beginning. We have also defined the macro SIMPLE_SPRNG before including the SPRNG header file in order to invoke the simple interface. We define the macro myrandom to sprng after including the SPRNG header. This replaces the former function call by calls to SPRNG instead.

We then add statements to initialize SPRNG.

Code:

Simple Interface Default/Pointer
Checking Interface
C FORTRAN Not Available

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include convert.c -L../lib -llcg

Note: In the code provided with SPRNG, users need to define the macro CONVERT in order to get this converted code.

Output: 

sprng/EXAMPLES:sif% a.out
Print information about random number stream:

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

Printing 3 random numbers in [0,1):
0.707488
0.664048
0.005616

13. subroutine

This program demonstrates the use of SPRNG in subroutines in FORTRAN programs.

Note that we have included the SPRNG header file sprng_f.h at the beginning. We have also included this header file in the subroutine sub1. If we wished to define a macro for use by SPRNG, we need only do it once in any file, before the first time a SPRNG header is included.

Subroutine sub1 is then called, which makes calls to sprng.

Code:

Simple Interface Default/Pointer
Checking Interface
Not Available FORTRAN

Compilation: Example compilation on the SGI Power Challenge

f77 -64 -I../include -DPOINTER_SIZE=8 subroutinef.F -L../lib -llcg

Output: 

sprng/EXAMPLES:sif% a.out
 Printing information about new stream

Linear Congruential Generator

        seed = 985456376, prime = 11863279
        multiplier = 44485709377909

 Printing 3 double precision numbers in [0,1): 
     1   0.7074876636340832
     2   0.6640484187971047
     3   0.0056156511936152

14. pi-simple

This is a serial program that demonstrates the use of several SPRNG features in a simple example application involving the computation of PI through a Monte Carlo method. We generate random points on a square of side 2 which circumscribes a circle of unit radius. We determine the proportion of points that fall within this circle. Since the ratio of the area of the circle to the area of the square is PI/4, the estimated value of PI is four times the proportion of points that lie within the circle.

The user specifies the number of samples to be generated on the square. The final state of the computations is stored in a file specified by the user. The user can restart the computations by reading from this file in subsequent runs. The user should also specify whether the current run is a new one (in which case a new random number stream is initialized) or an old one (in which case the state of the random number stream is read from a file).

Note that we have included the SPRNG header file at the beginning. We have also defined the macro SIMPLE_SPRNG before including the SPRNG header file in order to invoke the simple interface.

The function initialize is then called to take suitable actions based on the information input by the user. A new run involves initializing a random number stream. In a continuation of a previous run, the state of the random number stream is read from a file whose name is input by the user. The final state of the computations is also written into this file. The user should also input the number of samples to be generated in this run. In a new run, make_sprng_seed is called to produce a seed based on system date and time information.

Next the function count_in_circle is called, which generates points on a square of side 2. The number of points that fall on a circle of unit radius inscribed within this square is returned by this function.

We then estimate PI as four times the proportion of points that fall within the circle inscribed in the square.

Finally we call the function save_state to save the state of the random number stream, the cumulative number of sample points generated in all the runs, and the cumulative number of sample points that lie within the inscribed circle in all the runs.

Code:

C FORTRAN

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o pi-simple pi-simple.c -L../lib -llcg

Output: 

sprng/EXAMPLES:sif% pi-simple
Enter 9 for a new run, or 2 for the continuation of an old run:
9
Enter name of file to store final state of the stream:
temp
Enter number of new samples:
10000

Linear Congruential Generator

        seed = 437891907, prime = 11863279
        multiplier = 44485709377909

pi is estimated as 3.1227999999999998 from 10000 samples.
        Error = 0.0187927, standard error = 0.0164218
sprng/EXAMPLES:sif% pi-simple
Enter 9 for a new run, or 2 for the continuation of an old run:
2
Enter name of file to store final state of the stream:
temp
Enter number of new samples:
5000
pi is estimated as 3.1165333333333334 from 15000 samples.
        Error = 0.0250593, standard error = 0.0134084
Note: Results may vary due to the use of a random seed.

15. pi-simple_mpi

This is a parallel version of is a parallel version of pi-simple in which we divide the work of generating the samples among the available processes.

First we initialize MPI and call the function initialize to initialize a random number stream. If this is the continuation of a previously checkpointed run, then process 0 reads the previous state and passes to to each process.

Next we divide the number of samples to be generated among all the processes and then call the function count_in_circle as in the sequential case. We then sum the number of points that fall within the circle across all the processes by a call to MPI_REDUCE and estimate PI as four times the proportion of points that fall within this circle inscribed in the square.

Finally we call the function save_state to save the state of the random number stream, the cumulative number of sample points generated in all the runs, and the cumulative number of sample points that lie within the inscribed circle in all the runs. Each process passes the state of its stream to process 0, which then saves it to a file.

Code:

C

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o pi-simple pi-simple.c -L../lib -llcg

Compilation: Example compilation on the SGI Power Challenge

cc -64 -I../include -o pi-simple_mpi pi-simple_mpi.c -L../lib -llcg -L/usr/lib64 -lmpi

Output: 

sprng/EXAMPLES:sif% mpirun -np 2 pi-simple_mpi 
Enter 9 for a new run, or 2 for the continuation of an old run:
9
Enter name of file to store final state of the stream:
temp
Enter number of new samples:
5000

Linear Congruential Generator

Linear Congruential Generator

        seed = 42578755, prime = 11863279
        multiplier = 44485709377909


        seed = 42578755, prime = 11863259
        multiplier = 44485709377909

pi is estimated as 3.1568000000000001 from 5000 samples.
        Error = 0.0152073, standard error = 0.023224
Note: Results may vary due to the use of a random seed.

Ashok Srinivasan
ashoks@ncsa.uiuc.edu
Last modified: 1 Apr, 1997