Manpages - dispatch_apply.3

The

function provides data-level concurrency through a “for (;;)” loop like primitive:

size_t iterations = 10;

/ ’idx’ is zero indexed, just like: / for (idx = 0; idx < iterations; idx++)

dispatch_apply(iterations, DISPATCH_APPLY_AUTO, ^(size_t idx) { printf(“%zu\n”, idx); });

Although any queue can be used, it is strongly recommended to use

as the

argument to both

and

as shown in the example above, since this allows the system to automatically use worker threads that match the configuration of the current thread as closely as possible. No assumptions should be made about which global concurrent queue will be used.

Like a “for (;;)” loop, the

function is synchronous. If asynchronous behavior is desired, wrap the call to

with a call to

against another queue.

Sometimes, when the block passed to

is simple, the use of striding can tune performance. Calculating the optimal stride is best left to experimentation. Start with a stride of one and work upwards until the desired performance is achieved (perhaps using a power of two search):

#define STRIDE 3

dispatch_apply(count / STRIDE, DISPATCH_APPLY_AUTO, ^(size_t idx) { size_t j = idx * STRIDE; size_t j_stop = j + STRIDE; do { printf(“%zu\n”, j++); } while (j < j_stop); });

size_t i; for (i = count - (count % STRIDE); i < count; i++) { printf(“%zu\n”, i); }

Synchronous functions within the dispatch framework hold an implied reference on the target queue. In other words, the synchronous function borrows the reference of the calling function (this is valid because the calling function is blocked waiting for the result of the synchronous function, and therefore cannot modify the reference count of the target queue until after the synchronous function has returned).

This is in contrast to asynchronous functions which must retain both the block and target queue for the duration of the asynchronous operation (as the calling function may immediately release its interest in these objects).

and

attempt to quickly create enough worker threads to efficiently iterate work in parallel. By contrast, a loop that passes work items individually to

will incur more overhead and does not express the desired parallel execution semantics to the system, so may not create an optimal number of worker threads for a parallel workload. For this reason, prefer to use

when parallel execution is important.

The

function is a wrapper around

Unlike

a block submitted to

is expected to be either independent or dependent

on work already performed in lower-indexed invocations of the block. If the block’s index dependency is non-linear, it is recommended to use a for-loop around invocations of