Our previous examples used a single worker thread, and thus only one processor core. If we want to take full advantage of multi-core processors, we need the ability to delegate expensive computations to a pool of theads. This example demonstrates the pool thread that comes bundled with threads_a_gogo.
First, we create a pool
var Threads = require('threads_a_gogo');
var pool = Threads.createPool(3);
Then we load our fibonacci function in all the pool's threads:
function fibo(n) {
return n > 1 ? fibo(n - 1) + fibo(n - 2) : 1;
}
pool.all.eval(fibo);
Now, we can get fibonacci numbers from our pool
We request them in reverse order, to show that longer computations (fibo(40)
) run in
parallel with shorter ones (fibo(39)
, fibo(38)
, ...). The results won't come out in strictly decreasing order.
var remain = 11;
for (var i = 40; i >= 30; i--) {
// extra closure to get proper scoping on 'i'
(function(i) {
// dispatch each request to the first available thread
pool.any.eval('fibo(' + i + ')', function(err, val) {
console.log('fibo(' + i + ')=' + i);
// destroy the pool when all results have been produced
if (--remain == 0) console.log('bye!'), pool.destroy();
});
})(i);
}
(*) Execution is non-deterministic. So order may vary.
fibo(38)=38
fibo(39)=39
fibo(37)=37
fibo(35)=35
fibo(36)=36
fibo(33)=33
fibo(34)=34
fibo(31)=31
fibo(32)=32
fibo(30)=30
fibo(40)=40
bye!