Module git_features::parallel [−][src]
Expand description
Run computations in parallel, or not based the parallel feature toggle.
in_parallel(…)
The in_parallel(…) is the typical fan-out-fan-in mode of parallelism, with thread local storage
made available to a consume(…) function to process input. The result is sent to the Reduce running in the calling
thread to aggregate the results into a single output, which is returned by in_parallel().
Interruptions can be achieved by letting the reducers feed(…)` method fail.
It gets a boost in usability as it allows threads to borrow variables from the stack, most commonly the repository itself or the data to work on.
This mode of operation doesn’t lend itself perfectly to being wrapped for async as it appears like a single long-running
operation which runs as fast as possible, which is cancellable only by merit of stopping the input or stopping the output
aggregation.
reduce::Stepwise
The Stepwise iterator works exactly as in_parallel() except that the processing of the output produced by
consume(I, &mut State) -> O is made accessible by the Iterator trait’s next() method. As produced work is not
buffered, the owner of the iterator controls the progress made.
Getting the final output of the Reduce is achieved through the consuming Stepwise::finalize() method, which
is functionally equivalent to calling in_parallel().
In an async context this means that progress is only made each time next() is called on the iterator, while merely dropping
the iterator will wind down the computation without any result.
Maintaining Safety
In order to assure that threads don’t outlive the data they borrow because their handles are leaked, we enforce
the 'static lifetime for its inputs, making it less intuitive to use. It is, however, possible to produce
suitable input iterators as long as they can hold something on the heap.
Re-exports
pub use reduce::Reduce;Modules
Structs
Evaluate any iterator in their own thread.
Enums
An conditional EagerIter, which may become a just-in-time iterator running in the main thread depending on a condition.
Functions
Read items from input and consume them in multiple threads,
whose output output is collected by a reducer. Its task is to
aggregate these outputs into the final result returned by this function with the benefit of not having to be thread-safe.
Run in_parallel() only if the given condition() returns true when eagerly evaluated.
Runs left and right in parallel, returning their output when both are done.
Return the ‘optimal’ (size of chunks, amount of threads as Option, amount of threads) to use in in_parallel() for the given
desired_chunk_size, num_items, thread_limit and available_threads.