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Added modules and main()

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Worth noting that this will change the diff of the parallel section quite a bit, since they became the body of the main procedure.
Thus each line in intented.
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Ian Bertolacci
2015-08-02 15:37:01 -07:00
parent 1f6f7b7843
commit b27d526822
1 changed files with 251 additions and 197 deletions
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chapel.html.markdown
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@@ -673,234 +673,288 @@ var copyNewTypeList = new GenericClass( realList, int );
for value in copyNewTypeList do write( value, ", " ); for value in copyNewTypeList do write( value, ", " );
writeln( ); writeln( );
// Parallelism
// In other languages, parallelism is typically this is done with
// complicated libraries and strange class structure hierarchies.
// Chapel has it baked right into the language.
// A begin statement will spin the body of that statement off into one new task. // Modules are Chapel's way of managing name spaces.
// A sync statement will ensure that the progress of the main // The files containing these modules do not need to be named after the modules
// task will not progress until the children have synced back up. // (as is with Java), but files implicitly name modules.
sync { // In this case, this file implicitly names the 'learnchapel' module
begin { // Start of new task's body
var a = 0;
for i in 1..1000 do a += 1;
writeln( "Done: ", a);
} // End of new tasks body
writeln( "spun off a task!");
}
writeln( "Back together" );
proc printFibb( n: int ){ module OurModule {
writeln( "fibonacci(",n,") = ", fibonacci( n ) ); // We can use modules inside of other modules.
} use Time;
// A cobegin statement will spin each statement of the body into one new task // We'll use this a procedure in the parallelism section.
cobegin { proc countdown( seconds: int ){
printFibb( 20 ); // new task for i in 1..seconds by -1 {
printFibb( 10 ); // new task writeln( i );
printFibb( 5 ); // new task sleep( 1 );
{
// This is a nested statement body and thus is a single statement
// to the parent statement and is executed by a single task
writeln( "this gets" );
writeln( "executed as" );
writeln( "a whole" );
}
}
// Notice here that the prints from each statement may happen in any order.
// Coforall loop will create a new task for EACH iteration
var num_tasks = 10; // Number of tasks we want
coforall taskID in 1..#num_tasks {
writeln( "Hello from task# ", taskID );
}
// Again we see that prints happen in any order.
// NOTE! coforall should be used only for creating tasks!
// Using it to iterating over a structure is very a bad idea!
// forall loops are another parallel loop, but only create a smaller number
// of tasks, specifically --dataParTasksPerLocale=number of task
forall i in 1..100 {
write( i, ", ");
}
writeln( );
// Here we see that there are sections that are in order, followed by
// a section that would not follow ( e.g. 1, 2, 3, 7, 8, 9, 4, 5, 6, ).
// This is because each task is taking on a chunk of the range 1..10
// (1..3, 4..6, or 7..9) doing that chunk serially, but each task happens
// in parallel.
// Your results may depend on your machine and configuration
// For both the forall and coforall loops, the execution of the
// parent task will not continue until all the children sync up.
// forall loops are particularly useful for parallel iteration over arrays.
// Lets run an experiment to see how much faster a parallel loop is
use Time; // Import the Time module to use Timer objects
var timer: Timer;
var myBigArray: [{1..4000,1..4000}] real; // Large array we will write into
// Serial Experiment
timer.start( ); // Start timer
for (x,y) in myBigArray.domain { // Serial iteration
myBigArray[x,y] = (x:real) / (y:real);
}
timer.stop( ); // Stop timer
writeln( "Serial: ", timer.elapsed( ) ); // Print elapsed time
timer.clear( ); // Clear timer for parallel loop
// Parallel Experiment
timer.start( ); // start timer
forall (x,y) in myBigArray.domain { // Parallel iteration
myBigArray[x,y] = (x:real) / (y:real);
}
timer.stop( ); // Stop timer
writeln( "Parallel: ", timer.elapsed( ) ); // Print elapsed time
timer.clear( );
// You may have noticed that (depending on how many cores you have)
// that the parallel loop went faster than the serial loop
// A succinct way of writing a forall loop over an array:
// iterate over values
[ val in myBigArray ] val = 1 / val;
// or iterate over indicies
[ idx in myBigArray.domain ] myBigArray[idx] = -myBigArray[idx];
proc countdown( seconds: int ){
for i in 1..seconds by -1 {
writeln( i );
sleep( 1 );
}
}
// Atomic variables, common to many languages, are ones whose operations
// occur uninterupted. Multiple threads can both modify atomic variables
// and can know that their values are safe.
// Chapel atomic variables can be of type bool, int, uint, and real.
var uranium: atomic int;
uranium.write( 238 ); // atomically write a variable
writeln( uranium.read() ); // atomically read a variable
// operations are described as functions, you could define your own operators.
uranium.sub( 3 ); // atomically subtract a variable
writeln( uranium.read() );
var replaceWith = 239;
var was = uranium.exchange( replaceWith );
writeln( "uranium was ", was, " but is now ", replaceWith );
var isEqualTo = 235;
if uranium.compareExchange( isEqualTo, replaceWith ) {
writeln( "uranium was equal to ", isEqualTo,
" so replaced value with ", replaceWith );
} else {
writeln( "uranium was not equal to ", isEqualTo,
" so value stays the same... whatever it was" );
}
sync {
begin { // Reader task
writeln( "Reader: waiting for uranium to be ", isEqualTo );
uranium.waitFor( isEqualTo );
writeln( "Reader: uranium was set (by someone) to ", isEqualTo );
}
begin { // Writer task
writeln( "Writer: will set uranium to the value ", isEqualTo, " in..." );
countdown( 3 );
uranium.write( isEqualTo );
}
}
// sync vars have two states: empty and full.
// If you read an empty variable or write a full variable, you are waited
// until the variable is full or empty again
var someSyncVar$: sync int; // varName$ is a convention not a law.
sync {
begin { // Reader task
writeln( "Reader: waiting to read." );
var read_sync = someSyncVar$;
writeln( "value is ", read_sync );
}
begin { // Writer task
writeln( "Writer: will write in..." );
countdown( 3 );
someSyncVar$ = 123;
}
}
// single vars can only be written once. A read on an unwritten single results
// in a wait, but when the variable has a value it can be read indefinitely
var someSingleVar$: single int; // varName$ is a convention not a law.
sync {
begin { // Reader task
writeln( "Reader: waiting to read." );
for i in 1..5 {
var read_single = someSingleVar$;
writeln( "Reader: iteration ", i,", and the value is ", read_single );
} }
} }
begin { // Writer task // Submodule of Ourmodule
writeln( "Writer: will write in..." ); // It is possible to create arbitrarily deep module nests.
countdown( 3 ); module ChildModule {
someSingleVar$ = 5; // first and only write ever. proc foo(){
writeln( "ChildModule.foo()");
}
} }
module SiblingModule {
proc foo(){
writeln( "SiblingModule.foo()" );
}
}
} // end OurModule
// Using OurModule also uses all the modules it uses.
// Since OurModule uses Time, we also use time.
use OurModule;
// At this point we have not used ChildModule or SiblingModule so their symbols
// (i.e. foo ) are not available to us.
// However, the module names are, and we can explicitly call foo() through them.
SiblingModule.foo(); // Calls SiblingModule.foo()
// Super explicit naming.
OurModule.ChildModule.foo(); // Calls ChildModule.foo()
use ChildModule;
foo(); // Less explicit call on ChildModule.foo()
// We can declare a main procedure
// Note: all the code above main still gets executed.
proc main(){
// Parallelism
// In other languages, parallelism is typically this is done with
// complicated libraries and strange class structure hierarchies.
// Chapel has it baked right into the language.
// A begin statement will spin the body of that statement off
// into one new task.
// A sync statement will ensure that the progress of the main
// task will not progress until the children have synced back up.
sync {
begin { // Start of new task's body
var a = 0;
for i in 1..1000 do a += 1;
writeln( "Done: ", a);
} // End of new tasks body
writeln( "spun off a task!");
}
writeln( "Back together" );
proc printFibb( n: int ){
writeln( "fibonacci(",n,") = ", fibonacci( n ) );
}
// A cobegin statement will spin each statement of the body into one new task
cobegin {
printFibb( 20 ); // new task
printFibb( 10 ); // new task
printFibb( 5 ); // new task
{
// This is a nested statement body and thus is a single statement
// to the parent statement and is executed by a single task
writeln( "this gets" );
writeln( "executed as" );
writeln( "a whole" );
}
}
// Notice here that the prints from each statement may happen in any order.
// Coforall loop will create a new task for EACH iteration
var num_tasks = 10; // Number of tasks we want
coforall taskID in 1..#num_tasks {
writeln( "Hello from task# ", taskID );
}
// Again we see that prints happen in any order.
// NOTE! coforall should be used only for creating tasks!
// Using it to iterating over a structure is very a bad idea!
// forall loops are another parallel loop, but only create a smaller number
// of tasks, specifically --dataParTasksPerLocale=number of task
forall i in 1..100 {
write( i, ", ");
}
writeln( );
// Here we see that there are sections that are in order, followed by
// a section that would not follow ( e.g. 1, 2, 3, 7, 8, 9, 4, 5, 6, ).
// This is because each task is taking on a chunk of the range 1..10
// (1..3, 4..6, or 7..9) doing that chunk serially, but each task happens
// in parallel.
// Your results may depend on your machine and configuration
// For both the forall and coforall loops, the execution of the
// parent task will not continue until all the children sync up.
// forall loops are particularly useful for parallel iteration over arrays.
// Lets run an experiment to see how much faster a parallel loop is
use Time; // Import the Time module to use Timer objects
var timer: Timer;
var myBigArray: [{1..4000,1..4000}] real; // Large array we will write into
// Serial Experiment
timer.start( ); // Start timer
for (x,y) in myBigArray.domain { // Serial iteration
myBigArray[x,y] = (x:real) / (y:real);
}
timer.stop( ); // Stop timer
writeln( "Serial: ", timer.elapsed( ) ); // Print elapsed time
timer.clear( ); // Clear timer for parallel loop
// Parallel Experiment
timer.start( ); // start timer
forall (x,y) in myBigArray.domain { // Parallel iteration
myBigArray[x,y] = (x:real) / (y:real);
}
timer.stop( ); // Stop timer
writeln( "Parallel: ", timer.elapsed( ) ); // Print elapsed time
timer.clear( );
// You may have noticed that (depending on how many cores you have)
// that the parallel loop went faster than the serial loop
// A succinct way of writing a forall loop over an array:
// iterate over values
[ val in myBigArray ] val = 1 / val;
// or iterate over indicies
[ idx in myBigArray.domain ] myBigArray[idx] = -myBigArray[idx];
proc countdown( seconds: int ){
for i in 1..seconds by -1 {
writeln( i );
sleep( 1 );
}
}
// Atomic variables, common to many languages, are ones whose operations
// occur uninterupted. Multiple threads can both modify atomic variables
// and can know that their values are safe.
// Chapel atomic variables can be of type bool, int, uint, and real.
var uranium: atomic int;
uranium.write( 238 ); // atomically write a variable
writeln( uranium.read() ); // atomically read a variable
// operations are described as functions, you could define your own operators.
uranium.sub( 3 ); // atomically subtract a variable
writeln( uranium.read() );
var replaceWith = 239;
var was = uranium.exchange( replaceWith );
writeln( "uranium was ", was, " but is now ", replaceWith );
var isEqualTo = 235;
if uranium.compareExchange( isEqualTo, replaceWith ) {
writeln( "uranium was equal to ", isEqualTo,
" so replaced value with ", replaceWith );
} else {
writeln( "uranium was not equal to ", isEqualTo,
" so value stays the same... whatever it was" );
}
sync {
begin { // Reader task
writeln( "Reader: waiting for uranium to be ", isEqualTo );
uranium.waitFor( isEqualTo );
writeln( "Reader: uranium was set (by someone) to ", isEqualTo );
}
begin { // Writer task
writeln( "Writer: will set uranium to the value ", isEqualTo, " in..." );
countdown( 3 );
uranium.write( isEqualTo );
}
}
// sync vars have two states: empty and full.
// If you read an empty variable or write a full variable, you are waited
// until the variable is full or empty again
var someSyncVar$: sync int; // varName$ is a convention not a law.
sync {
begin { // Reader task
writeln( "Reader: waiting to read." );
var read_sync = someSyncVar$;
writeln( "value is ", read_sync );
}
begin { // Writer task
writeln( "Writer: will write in..." );
countdown( 3 );
someSyncVar$ = 123;
}
}
// single vars can only be written once. A read on an unwritten single results
// in a wait, but when the variable has a value it can be read indefinitely
var someSingleVar$: single int; // varName$ is a convention not a law.
sync {
begin { // Reader task
writeln( "Reader: waiting to read." );
for i in 1..5 {
var read_single = someSingleVar$;
writeln( "Reader: iteration ", i,", and the value is ", read_single );
}
}
begin { // Writer task
writeln( "Writer: will write in..." );
countdown( 3 );
someSingleVar$ = 5; // first and only write ever.
}
}
// Heres an example of using atomics and a synch variable to create a
// count-down mutex (also known as a multiplexer)
var count: atomic int; // our counter
var lock$: sync bool; // the mutex lock
count.write( 2 ); // Only let two tasks in at a time.
lock$.writeXF( true ); // Set lock$ to full (unlocked)
// Note: The value doesnt actually matter, just the state
// (full:unlocked / empty:locked)
// Also, writeXF() fills (F) the sync var regardless of its state (X)
coforall task in 1..#5 { // Generate tasks
// Create a barrier
do{
lock$; // Read lock$ (wait)
}while count.read() < 1; // Keep waiting until a spot opens up
count.sub(1); // decrement the counter
lock$.writeXF( true ); // Set lock$ to full (signal)
// Actual 'work'
writeln( "Task #", task, " doing work." );
sleep( 2 );
count.add( 1 ); // Increment the counter
lock$.writeXF( true ); // Set lock$ to full (signal)
}
// we can define the operations + * & | ^ && || min max minloc maxloc
// over an entire array using scans and reductions
// Reductions apply the operation over the entire array and
// result in a single value
var listOfValues: [1..10] int = [15,57,354,36,45,15,456,8,678,2];
var sumOfValues = + reduce listOfValues;
var maxValue = max reduce listOfValues; // 'max' give just max value
// 'maxloc' gives max value and index of the max value
// Note: We have to zip the array and domain together with the zip iterator
var (theMaxValue, idxOfMax) = maxloc reduce zip(listOfValues,
listOfValues.domain);
writeln( (sumOfValues, maxValue, idxOfMax, listOfValues[ idxOfMax ] ) );
// Scans apply the operation incrementally and return an array of the
// value of the operation at that index as it progressed through the
// array from array.domain.low to array.domain.high
var runningSumOfValues = + scan listOfValues;
var maxScan = max scan listOfValues;
writeln( runningSumOfValues );
writeln( maxScan );
} }
// Heres an example of using atomics and a synch variable to create a
// count-down mutex (also known as a multiplexer)
var count: atomic int; // our counter
var lock$: sync bool; // the mutex lock
count.write( 2 ); // Only let two tasks in at a time.
lock$.writeXF( true ); // Set lock$ to full (unlocked)
// Note: The value doesnt actually matter, just the state
// (full:unlocked / empty:locked)
// Also, writeXF() fills (F) the sync var regardless of its state (X)
coforall task in 1..#5 { // Generate tasks
// Create a barrier
do{
lock$; // Read lock$ (wait)
}while count.read() < 1; // Keep waiting until a spot opens up
count.sub(1); // decrement the counter
lock$.writeXF( true ); // Set lock$ to full (signal)
// Actual 'work'
writeln( "Task #", task, " doing work." );
sleep( 2 );
count.add( 1 ); // Increment the counter
lock$.writeXF( true ); // Set lock$ to full (signal)
}
// we can define the operations + * & | ^ && || min max minloc maxloc
// over an entire array using scans and reductions
// Reductions apply the operation over the entire array and
// result in a single value
var listOfValues: [1..10] int = [15,57,354,36,45,15,456,8,678,2];
var sumOfValues = + reduce listOfValues;
var maxValue = max reduce listOfValues; // 'max' give just max value
// 'maxloc' gives max value and index of the max value
// Note: We have to zip the array and domain together with the zip iterator
var (theMaxValue, idxOfMax) = maxloc reduce zip(listOfValues,
listOfValues.domain);
writeln( (sumOfValues, maxValue, idxOfMax, listOfValues[ idxOfMax ] ) );
// Scans apply the operation incrementally and return an array of the
// value of the operation at that index as it progressed through the
// array from array.domain.low to array.domain.high
var runningSumOfValues = + scan listOfValues;
var maxScan = max scan listOfValues;
writeln( runningSumOfValues );
writeln( maxScan );
``` ```
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