+++ /dev/null
-average_example
+++ /dev/null
-<!--#set var="root_directory" value="../../.." --><!--#include virtual="$root_directory/shared/header.shtml"-->
-
-<h1>Average Example</h1>
-
-<p>Computing the average and standard deviation of a set of numbers is
-a simple task. Yet doing it in parallel provides a good introduction
-to message passing programming using MPI.</p>
-
-<p>The data set <a href="src/data">data</a> is some noisy data set.
-The file contains "x" and a "y" coordinates of points that you can
-display with plot_data. We seek the average and standard deviation of
-the "y" column.</p>
-
-<p>The code <a href="src/average.c">average.c</a> solves this problem
-using a serial algorithm. Note the use of <code>malloc</code>
-and <code>free</code> to reserve and release memory space. This allows
-writing a flexible and general code.</p>
-
-<p>A parallel implementation of the solution could use an algorithm in
-which the data is divided among all the processes. This illustrates
-one of the advantage of using a parallel architecture in that the
-memory requirement per node is much less than in a serial
-implementation of the code. Or that the agregate memory of the
-parallel computer is tipically much larger than the memory of a single
-computer, allowing larger problems to be solved.</p>
-
-<p>The algorithm of a parallel implementation is illustrated in a
-simplified <a href="Average_Flowchart.pdf">flowchart</a>. Note the
-following:</p>
-<ul>
- <li>All the processes contain a chunk of data.</li>
- <li>The number of numbers in each process is adjusted dynamically
- according to the size of the data set and the number of
- processes.</li>
- <li>Each process uses <code>malloc</code> to reserve an appropriate
- size memory chunk for the local data.</li>
- <li>The wall time saving is acomplished via performing local sums in
- the different processes (not an issue in this very simple/fast
- calculation).</li>
- <li>A parallel implmentation of an algorithm tipically requires
- thinking in terms of real time programming — i.e., what each
- process does as a function of time.</li>
-</ul>
-
-<p>A parallel code should be written by the student. It requires a
-careful buildup and testing of the statements.</p>
-
-<!--#include virtual="$root_directory/shared/footer.shtml"-->
process.</dd>
<dt><a href="../../src/MPI2_message_passing/hop_again_again.c">hop_again_again.c</a></dt>
<dd>Each node sends a message to left and right neighbors in a ring
- fashion again-and-again</dd>
+ fashion again-and-again.</dd>
<dt><a href="../../src/MPI2_message_passing/ring.c">ring.c</a></dt>
- <dd>Non-blocking communication example</dd>
+ <dd>Non-blocking communication example.</dd>
</dl>
<h3 id="time">Communication time</h3>
time.</dd>
</dl>
+<h2 id="average">Average Example</h2>
+
+<p>Computing the average and standard deviation of a set of numbers is
+a simple task. Yet doing it in parallel provides a good introduction
+to message passing programming using MPI.</p>
+
+The following averaging example is bundled in
+<a href="../../src/average/average.tar.gz">average.tar.gz</a>.
+
+<p>Consider a noisy data set <code>data</code> generated
+by <a href="../../src/average/generate_random.c">generate_random.c</a>.
+The file contains <i>x</i> and a <i>y</i> coordinates of points that
+you can display with <code>gnuplot</code>. We seek the average and
+standard deviation of the <i>y</i> column.</p>
+
+<p>The code <a href="../../src/average.c">average.c</a> solves this
+problem using a serial algorithm. Note the use of <code>malloc</code>
+and <code>free</code> to reserve and release memory space. This allows
+for flexible and general code.</p>
+
+<p>A parallel implementation of the solution could use an algorithm in
+which the data is divided among all the processes. This illustrates
+one of the advantage of using a parallel architecture in that the
+memory requirement per node is much less than in a serial
+implementation of the code. Or that the agregate memory of the
+parallel computer is tipically much larger than the memory of a single
+computer, allowing larger problems to be solved.</p>
+
+<p>The algorithm of a parallel implementation is illustrated in a
+simplified <a href="../../src/flowchart.pdf">flowchart</a>. Note the
+following:</p>
+<ul>
+ <li>All the processes contain a chunk of data.</li>
+ <li>The number of numbers in each process is adjusted dynamically
+ according to the size of the data set and the number of
+ processes.</li>
+ <li>Each process uses <code>malloc</code> to reserve an appropriate
+ size memory chunk for the local data.</li>
+ <li>The wall time saving is acomplished via performing local sums in
+ the different processes (not an issue in this very simple/fast
+ calculation).</li>
+ <li>A parallel implmentation of an algorithm tipically requires
+ thinking in terms of real time programming — i.e., what each process
+ does as a function of time.</li>
+</ul>
+
+<p>The reader is encouraged to write their own parallel
+implementation. Be careful and think things through!</p>
+
<!--#include virtual="$root_directory/shared/footer.shtml"-->
Usage
-----
-MPI configuration
-~~~~~~~~~~~~~~~~~
-
-You should only have to do this once for each host, but since this is
-your first MPI program, you probably haven't done it yet. From
-
- $ man mpd
-
-we have:
-
- "A file named .mpd.conf file must be present in the user's home
- directory with read and write access only for the user, and must
- contain at least a line with MPD_SECRETWORD=<secretword>"
-
-so create the file with a random secret word:
-
- $ touch ~/.mpd.conf
- $ chmod 600 ~/.mpd.conf
- $ echo "MPD_SECRETWORD=$(cat /dev/urandom | tr -d -c A-Z-a-z-0-9 | head -c 60)" ~/.mpd.conf
-
-Running MPI programs
-~~~~~~~~~~~~~~~~~~~~
-
-Create a list of possible hosts `mpd.hosts`, for example
-
- xphy1.physics.xterm.net
- xphy2.physics.xterm.net
- ...
-
Start the Message Passing Daemons with
$ mpdboot -f mpd.hosts
--- /dev/null
+# General Environment
+
+RM = /bin/rm
+DATA_SIZE = 131071 # the 6th Mersenne prime
+DATA = data
+
+# Non-MPI Environment
+
+CC = /usr/bin/gcc
+CFLAGS =
+LD = $(CC)
+LDFLAGS = -lm
+EXECS = average generate_random
+
+# MPI Environment
+
+MPI_CC = /usr/bin/mpicc
+MPI_CFLAGS =
+MPI_LD = $(MPI_CC)
+MPI_LDFLAGS = -lm
+MPI_EXECS = average_parallel
+
+# Top level targets
+
+all: $(EXECS) $(MPI_EXECS) $(DATA)
+
+clean:
+ $(RM) -f *.o $(EXECS) $(DATA)
+
+# Non-MPI rules
+
+data : generate_random
+ ./$< $(DATA_SIZE) > $@
+
+$(EXECS:%=%.o) : %.o : %.c
+ $(CC) -c $(CFLAGS) -o $@ $^
+
+$(EXECS) : % : %.o
+ $(LD) $(LDFLAGS) -o $@ $^
+
+# MPI rules
+
+$(MPI_EXECS:%=%.o) : %.o : %.c
+ $(MPI_CC) -c $(CFLAGS) -o $@ $^
+
+$(MPI_EXECS) : % : %.o
+ $(MPI_LD) $(LDFLAGS) -o $@ $^
+
+# Interesting Makefile sections
+# 4.12.1 Syntax of Static Pattern Rules
+# 6.3.1 Substitution References
--- /dev/null
+average
+=======
+
+Compute the average and standard deviation of a set of numbers using
+both serial and parallel algorithms.
+
+Manifest
+--------
+
+================== ==============================================
+README This file.
+Makefile Automate building and cleanup.
+generate_random.c Generate random data for the 'data' file.
+read_file.c/.h Shared code defining read_data().
+average.c Serial average / std. dev. calculation.
+average_parallel.c Serial average / std. dev. calculation.
+flowchart.pdf Diagram of control flow in average_parallel.c.
+================== ==============================================
+
+Build
+-----
+
+Just run
+
+ $ make
+
+which also builds a random data file 'data'.
+
+Usage
+-----
+
+Serial code
+
+ $ ./average data
+
+Parallel code
+
+ $ mpdboot -f mpd.hosts
+ $ mpiexec -n 4 ./average_parallel data
+ $ mpdallexit
-//
-// average and standard deviation of a set of numbers
-//
-// Michel Vallieres
+/* Serial average and standard deviation of a set of numbers
+ *
+ * usage: average data_file
+ *
+ * Arguments:
+ * data_file path to a data file as output by 'generate_random'
+ */
-#include <stdio.h>
-#include <math.h>
-#include <stdlib.h>
+/* Michel Vallieres */
-int main( int *argc, char *argv[] )
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+
+
+int read_data(const char *file_name, int *pN, double **pData);
+
+
+int main(int argc, char *argv[])
{
+ int N, i;
+ double *data, average, diff, std_dev;
+ char *file_name = "data";
+
+ // parse arguments
+ if (argc > 1)
+ file_name = argv[1];
+
+ // setup
+ if (read_data(file_name, &N, &data) != EXIT_SUCCESS)
+ return EXIT_FAILURE;
+
+ printf("computing\n");
+
+ // average
+ average = 0.0;
+ for (i=0; i < N; i++)
+ average += data[i];
+ printf("sum: %f\n", average);
+ average /= N;
+ printf("average: %f\n", average);
+
+ // standard deviation
+ std_dev = 0.0;
+ for (i=0; i < N; i++)
+ {
+ diff = data[i] - average;
+ std_dev += diff * diff;
+ }
+ std_dev = sqrt(std_dev / (N-1));
+ printf("standard deviation: %f\n", std_dev);
+
+ // cleanup and exit
+ free(data);
+ return EXIT_SUCCESS;
+}
+
+/* Read in data from a file, discarding the x data. */
+int read_data(const char *file_name, int *pN, double **pData) {
FILE *fp;
- int N, k;
- double *x, average, std_dev, dumb, sum;
+ int i;
+ double x, y;
+
+ // open the file
+ if ((fp = fopen(file_name, "r")) == NULL)
+ {
+ fprintf(stderr, "error in opening data file %s\n", file_name);
+ return EXIT_FAILURE;
+ }
- // title
- printf( "\n Average code \n\n" );
+ // read the size of the data file
+ fscanf(fp, "# %d", pN);
- // open file
- if ( ( fp = fopen( "data", "r" ) ) == NULL )
+ // allocate memory for the data
+ *pData = (double *)malloc(sizeof(double)* *pN);
+ if (*pData == NULL)
{
- printf( "error in opening data file\n" );
- exit(1);
+ fprintf(stderr, "could not allocate %d bytes\n", sizeof(double)* *pN);
+ return EXIT_FAILURE;
}
- // value of N
- fscanf( fp, " %d ", &N );
- printf( " Number pf points: %d \n", N );
- // make space in memory for x
- x = (double *)malloc( sizeof(double)*N );
- // read in x
- for ( k=0 ; k<N ; k++ )
- fscanf( fp, " %lf %lf ", &dumb, &x[k] );
- // close file
- fclose ( fp );
-
- // average
- average = 0.0;
- for ( k=0 ; k<N ; k++ )
- average = average + x[k];
- average = average / (double)(N);
- printf( " Average: %f \n", average );
-
- //standard deviation
- sum = 0.0;
- for ( k=0 ; k<N ; k++ )
- sum = sum + ( x[k]-average ) * ( x[k]-average );
- std_dev = sqrt( sum / (double)(N-1) );
- printf( " Standard deviation: %f \n\n", std_dev );
-
- // free memory
- free(x);
- exit(0);
+
+ // read in the data
+ printf("reading %d points\n", *pN);
+ for (i=0; i < *pN ; i++)
+ {
+ fscanf(fp, "%lf %lf", &x, &y);
+ (*pData)[i] = y;
+ }
+
+ // close the file
+ fclose (fp);
+ return EXIT_SUCCESS;
}
-//
-// average and standard deviation of a set of numbers
-//
-// Michel Vallieres
-// Spring 2002
+/* Parallel average and standard deviation of a set of numbers
+ *
+ * usage: mpiexec ... average_parallel data_file
+ *
+ * Arguments:
+ * data_file path to a data file as output by 'generate_random'
+ */
-#include <stdio.h>
-#include <stdlib.h>
-#include <mpi.h>
+/* Michel Vallieres
+ * Spring 2002 */
-int main( int argc, char *argv[] )
+#include <stdio.h>
+#include <stdlib.h>
+#include <math.h>
+#include <mpi.h>
+
+#define TAG_NUMBER 100
+#define TAG_DATA 101
+#define TAG_SUM 102
+#define TAG_AVERAGE 103
+#define TAG_STD_DEV 104
+
+
+int master(int argc, char *argv[], int rank, int size);
+int slave(int rank);
+
+int main(int argc, char *argv[])
{
- FILE *fp;
- int N, k;
- double *x, average, std_dev, dumb, sum, local_sum;
- int process, my_rank, size;
- int N_local;
- MPI_Status recv_status;
+ int rank, size;
MPI_Init(&argc, &argv);
- MPI_Comm_rank(MPI_COMM_WORLD, &my_rank);
+ MPI_Comm_rank(MPI_COMM_WORLD, &rank);
MPI_Comm_size(MPI_COMM_WORLD, &size);
- // NODE 0
-
- if ( my_rank == 0 )
+ if (size == 1)
{
- // title
- printf( "\n Average code \n\n" );
- // open file
- if ( ( fp = fopen( "data", "r" ) ) == NULL )
- {
- printf( "error in opening data file\n" );
- exit(1);
- }
- // value of N
- fscanf( fp, " %d ", &N );
- printf( " Number pf points: %d \n", N );
- // size of data chunks on each node
- N_local = N / size;
- // make space in memory for x (node zero)
- x = (double *)malloc( sizeof(double)*(N_local+size) );
-
- for ( process=1 ; process<size ; process++ )
- {
- // send # of numbers to node
- MPI_Ssend( &N_local, 1, MPI_INT, process, 121, MPI_COMM_WORLD );
- // read in x
- for ( k=0 ; k<N_local ; k++ )
- fscanf( fp, " %lf %lf ", &dumb, &x[k] );
- // send x array to node
- MPI_Ssend( x, N_local, MPI_DOUBLE, process, 122, MPI_COMM_WORLD );
- }
- // read in x for node 0
- N_local = N - (size-1)*N_local;
-
- printf( " Node %d - N %d \n", my_rank, N_local );
-
- for ( k=0 ; k<N_local ; k++ )
- fscanf( fp, " %lf %lf ", &dumb, &x[k] );
- // close file
- fclose ( fp );
- // average (local sum)
- average = 0.0;
- for ( k=0 ; k<N_local ; k++ )
- average = average + x[k];
- for ( process=1 ; process<size ; process++ )
- {
- MPI_Recv( &local_sum, 1, MPI_DOUBLE, MPI_ANY_SOURCE, 123,
- MPI_COMM_WORLD, &recv_status );
- average = average + local_sum;
- }
- average = average / (double)(N);
- printf( " Average: %f \n", average );
- // distribute average to nodes
- for ( process=1 ; process<size ; process++ )
- {
- MPI_Ssend( &average, 1, MPI_DOUBLE, process, 124, MPI_COMM_WORLD );
- }
- //standard deviation
- sum = 0.0;
- for ( k=0 ; k<N_local ; k++ )
- sum = sum + ( x[k]-average ) * ( x[k]-average );
- for ( process=1 ; process<size ; process++ )
- {
- MPI_Recv( &local_sum, 1, MPI_DOUBLE, MPI_ANY_SOURCE, 125,
- MPI_COMM_WORLD, &recv_status );
- sum = sum + local_sum;
- }
- std_dev = sqrt( sum / (double)(N-1) );
- printf( " Standard deviation: %f \n\n", std_dev );
+ fprintf(stderr, "%s requires more than one node\n", argv[0]);
+ return EXIT_FAILURE;
}
+
+ if (rank == 0)
+ master(argc, argv, rank, size);
else
+ slave(rank);
+
+ MPI_Finalize();
+ return EXIT_SUCCESS;
+}
- // OTHER NODES
+int master(int argc, char *argv[], int rank, int size)
+{
+ FILE *fp;
+ char *file_name = "data";
+ int N, N_local, N_local_residual, process, i, err;
+ double *data, x, average, diff, std_dev, local_sum;
+ MPI_Status recv_status;
+ // parse arguments
+ if (argc > 1)
+ file_name = argv[1];
+
+ // setup
+
+ // open the file
+ if ((fp = fopen(file_name, "r")) == NULL)
{
- // Number of numbers to analize locally
- MPI_Recv( &N_local, 1, MPI_INT, 0, 121,
- MPI_COMM_WORLD, &recv_status );
-
- printf( " Node %d - N %d \n", my_rank, N_local );
-
- // make space in memory for x (node zero)
- x = (double *)malloc( sizeof(double)*(N_local+size) );
- // local x array
- MPI_Recv( x, N_local, MPI_DOUBLE, 0, 122,
- MPI_COMM_WORLD, &recv_status);
- // average (local sum)
- local_sum = 0.0;
- for ( k=0 ; k<N_local ; k++ )
- local_sum = local_sum + x[k];
- // send local sum to node 0
- MPI_Ssend( &local_sum, 1, MPI_DOUBLE, 0, 123, MPI_COMM_WORLD );
- // avarage
- MPI_Recv( &average, 1, MPI_DOUBLE, 0, 124,
- MPI_COMM_WORLD, &recv_status);
- //standard deviation
- local_sum = 0.0;
- for ( k=0 ; k<N_local ; k++ )
- local_sum = local_sum + ( x[k]-average ) * ( x[k]-average );
- // send local sum to node 0
- MPI_Ssend( &local_sum, 1, MPI_DOUBLE, 0, 125, MPI_COMM_WORLD );
+ fprintf(stderr, "error in opening data file %s\n", file_name);
+ return EXIT_FAILURE;
+ }
+ // read the size of the data file
+ fscanf(fp, "# %d", &N);
+ printf("reading %d points\n", N);
+
+ N_local = N / size; // size of data chunks on each node
+ N_local_residual = N % size; // extra points for the master node
+
+ // allocate memory to hold a data chunk
+ data = (double *)malloc(sizeof(double) * (N_local+N_local_residual));
+ if (data == NULL)
+ {
+ fprintf(stderr, "could not allocate %d bytes\n", sizeof(double)* N_local);
+ return EXIT_FAILURE;
}
- // free memory
- free(x);
- // finalize MPI
- MPI_Finalize();
- // exit
- exit(0);
+ for (process=1 ; process < size ; process++)
+ {
+ // send # of numbers to node
+ MPI_Ssend(&N_local, 1, MPI_INT, process, TAG_NUMBER, MPI_COMM_WORLD);
+
+ // read in the data
+ for (i=0; i < N_local; i++)
+ fscanf(fp, "%lf %lf", &x, &data[i]);
+
+ // send data to the node
+ MPI_Ssend(data, N_local, MPI_DOUBLE, process, TAG_DATA, MPI_COMM_WORLD);
+ }
+
+ N_local += N_local_residual;
+
+ // read in data for the master
+ for (i=0; i < N_local; i++)
+ fscanf(fp, "%lf %lf", &x, &data[i]);
+
+ // close file
+ fclose(fp);
+
+ printf("computing\n");
+ average = 0;
+ for (i=0; i < N_local; i++)
+ average += data[i];
+ printf(" node %d - N %d, average %f\n",
+ rank, N_local, average/N_local);
+
+ // collect sums from other nodes
+ for (process=1; process < size; process++)
+ {
+ err = MPI_Recv(&local_sum, 1, MPI_DOUBLE, MPI_ANY_SOURCE, TAG_SUM,
+ MPI_COMM_WORLD, &recv_status);
+ average += local_sum;
+ }
+
+ printf("sum: %f\n", average);
+ average /= N;
+ printf("average: %f\n", average);
+
+ // distribute average to nodes
+ for (process=1; process < size; process++)
+ {
+ MPI_Ssend(&average, 1, MPI_DOUBLE, process, TAG_AVERAGE,
+ MPI_COMM_WORLD);
+ }
+
+ // standard deviation
+ std_dev = 0.0;
+ for (i=0; i < N_local; i++) {
+ diff = data[i] - average;
+ std_dev += diff * diff;
+ }
+ printf(" node %d - std dev %f\n", rank, std_dev/N_local);
+
+ // collect sums from other nodes
+ for (process=1; process<size; process++)
+ {
+ MPI_Recv(&local_sum, 1, MPI_DOUBLE, MPI_ANY_SOURCE, TAG_STD_DEV,
+ MPI_COMM_WORLD, &recv_status);
+ std_dev = std_dev + local_sum;
+ }
+
+ std_dev = sqrt(std_dev / (N-1));
+ printf("standard deviation: %f\n", std_dev);
+
+ // cleanup and exit
+ free(data);
+ return EXIT_SUCCESS;
+}
+
+int slave(int rank)
+{
+ int master=0, N, i, err;
+ double *data, average, sum, diff;
+ MPI_Status recv_status;
+
+ // get the number of numbers to analyze locally
+ err = MPI_Recv(&N, 1, MPI_INT, master, TAG_NUMBER, MPI_COMM_WORLD,
+ &recv_status);
+
+ // allocate memory to hold a data chunk
+ data = (double *)malloc(sizeof(double)*N);
+ if (data == NULL)
+ {
+ fprintf(stderr, "could not allocate %d bytes\n", sizeof(double)* N);
+ return EXIT_FAILURE;
+ }
+
+ // get the data
+ err = MPI_Recv(data, N, MPI_DOUBLE, master, TAG_DATA, MPI_COMM_WORLD,
+ &recv_status);
+
+ // average (local sum)
+ sum = 0.0;
+ for (i=0; i < N; i++)
+ sum = sum + data[i];
+ printf(" node %d - N %d, average %f\n", rank, N, sum/N);
+
+ // send local sum to master
+ MPI_Ssend(&sum, 1, MPI_DOUBLE, master, TAG_SUM, MPI_COMM_WORLD);
+
+ // get the average
+ MPI_Recv(&average, 1, MPI_DOUBLE, master, TAG_AVERAGE, MPI_COMM_WORLD,
+ &recv_status);
+
+ //standard deviation
+ sum = 0.0;
+ for (i=0; i < N; i++)
+ {
+ diff = data[i] - average;
+ sum += diff * diff;
+ }
+ printf(" node %d - std dev sum %f\n", rank, sum/N);
+
+ // send local sum to master
+ MPI_Ssend(&sum, 1, MPI_DOUBLE, master, TAG_STD_DEV, MPI_COMM_WORLD);
+
+ // cleanup and exit
+ free(data);
+ return EXIT_SUCCESS;
}
+++ /dev/null
- 25729
- 1.040188 -1.484743
- 0.998440 -1.608843
- 0.535223 -1.124128
- 0.753970 -1.011400
- 0.564784 -1.813525
- 1.116195 -1.398474
- 0.341603 -2.401893
- 0.442887 -1.393351
- 0.356679 -1.836376
- 0.308809 -1.977118
- 0.712932 -0.735482
- 0.496032 -0.515075
- 0.693583 -1.006823
- 0.971358 -1.429044
- 0.600229 -1.077092
- 0.552458 -2.038310
- 0.269755 1.169535
- 0.286056 -0.997981
- 1.090233 -1.699440
- 0.220023 -2.680431
- 0.438280 -2.618971
- 1.050920 -1.213937
- 0.575207 -0.489371
- 0.867724 -1.718133
- 0.637638 -2.156838
- 0.920952 -1.338729
- 0.839979 -1.204321
- 0.365974 -1.887345
- 1.029201 -1.452260
- 1.093372 -1.361055
- 1.156468 -1.309855
- 1.058676 -1.710138
- 0.598437 -0.942727
- 1.110972 -1.543403
- 1.150252 -1.876599
- 1.081062 -1.085495
- 0.819596 -1.375908
- 0.507458 -1.360146
- 0.387533 -0.765901
- 0.616501 -1.493153
- 0.303171 -0.846667
- 0.960475 -2.176829
- 0.884445 -1.339564
- 0.568664 -1.315024
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+++ /dev/null
-//
-// to generate random data
-//
-
-#include <stdio.h>
-#include <math.h>
-#include <strings.h>
-#include <stdlib.h>
-
-// random numbers in { 0 - 1 }
-double random_num()
-{
- return (double)rand()/(double)RAND_MAX;
-}
-
-
-//
-// Gaussian distributed random numbers
-//
-double gaussian ( double *gauss1, double *gauss2 )
-{
- double twou, radius, theta;
-
- twou = -2.0*log(1.0-random_num());
- radius = sqrt(twou);
- theta = 2*M_PI*random_num();
- *gauss1 = radius*cos(theta);
- *gauss2 = radius*sin(theta);
-}
-
-int main( int argc, char *argv[] )
-{
- int N, i;
- double xmin, xmax, x, y;
- double gauss1, gauss2;
-
- N = atoi( argv[1] );
- printf( " %d \n", N );
-
- xmin = 0.2;
- xmax = 1.2;
-
- for ( i=0; i< N ; i++ )
- {
- x = xmin + (xmax-xmin)*random_num();
- y = -1.5 + 0.8*x - 0.7*x*x;
- gaussian( &gauss1, &gauss2 );
- y = y * ( 1 + 0.30*gauss1*0.7/x );
- printf( " %f %f \n", x, y );
- }
-}
-
--- /dev/null
+/* generate random data
+ *
+ * usage: generate_random N
+ *
+ * Arguments:
+ * N the number of pairs to generate.
+ * Output:
+ * An ASCII file whose first line is '# N', and subsequent lines are
+ * tab (\t) separated (x,y) pairs. For example:
+ * # 25729
+ * 1.040188 -1.484743
+ * 0.998440 -1.608843
+ * The random numbers will be uniformly distributed on [XMIN, XMAX]
+ * with y values given by: y(x) = YA + YB x + YC x^2 + YR*random_num().
+ */
+
+#include <stdio.h>
+#include <math.h>
+#include <strings.h>
+#include <stdlib.h>
+
+/* NOTE: Strictly ISO or POSIX compiant compilers will not define M_PI.
+ * See http://www.sbin.org/doc/glibc/libc_19.html#SEC389
+ * You can define it yourself by uncommenting the following line. */
+//# define M_PI 3.14159265358979323846 /* pi */
+
+#define XMIN 0.2
+#define XMAX 1.2
+#define YA -1.5
+#define YB 0.8
+#define YC -0.7
+#define YR 0.2
+
+/* Uniform random number from [0,1] */
+double random_num()
+{
+ return (double)rand() / (double)RAND_MAX;
+}
+
+int main( int argc, char *argv[] )
+{
+ int N, i;
+ double x, y;
+
+ N = atoi(argv[1]);
+ printf("# %d\n", N);
+
+ for (i=0; i < N ; i++)
+ {
+ x = XMIN + (XMAX-XMIN)*random_num();
+ y = YA + YB*x + YC*x*x + YR*random_num();
+ printf("%f\t%f\n", x, y);
+ }
+
+ return EXIT_SUCCESS;
+}
--- /dev/null
+#include <stdio.h>
+#include <stdlib.h>
+
+#include "read_data.h"
+
+
+
--- /dev/null
+#ifndef READ_DATA_H /* protect against multiple inclusion */
+#define READ_DATA_H
+
+
+#endif /* READ_DATA_H */
projects / parallel_computing.git / commitdiff