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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Nim does not offer one concurrency feature. It offers separate tools for two different jobs: waiting on slow operations such as network or file I/O without blocking the program, and running CPU-heavy work on several threads at once. Use async and await from std/asyncdispatch for the first job. Use threads, created with createThread or spawn, for the second. Channels pass values between workers, and locks or atomics protect shared state. One caution applies before you build on the parallel-task API in std/threadpool: its current online documentation labels the module unstable and deprecated, in favor of the Nimble packages malebolgia, taskpools, or weave.
Concurrency and parallelism are different problems
Concurrency means several tasks are in progress at the same time, with their steps interleaved. Parallelism means they execute at the same instant on separate CPU cores. Async/await provides concurrency for work that spends most of its time waiting: a socket with no data yet, a file read, a timer. One thread can keep many such waits in flight. It does not make arithmetic faster. Threads and parallel tasks are the tool when the work is CPU-bound and should use several cores. Choosing by workload rather than by keyword avoids most wasted effort.
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| Question | Async/await (std/asyncdispatch) |
Threads and parallel tasks |
|---|---|---|
| Main fit | Asynchronous I/O and waiting on futures | CPU-heavy work, or work that should run in a separate worker |
| Execution model | A dispatcher (event loop) runs async procedures | Multiple threads of execution, or parallel tasks handed to a pool |
| How results come back | A future, consumed with await |
FlowVar in std/threadpool, thread joins, or task handles from a third-party library |
| Shared-state concerns | Usually fewer, when the work stays on one event loop | Heap-sharing restrictions, synchronization, and failure handling all need attention |
| API status | The current online documentation describes the module’s asynchronous I/O role | createThread is documented in the Nim manual; the std/threadpool documentation labels that module unstable and deprecated |
Async/await with std/asyncdispatch
The std/asyncdispatch module supplies the dispatcher, the Future type, and the {.async.} pragma. An async procedure returns a future. Inside it, await suspends that procedure until the awaited future completes, and while it is suspended the dispatcher runs other pending work. At the top level of a program, waitFor runs the dispatcher until a given future finishes.
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A minimal example
import std/asyncdispatch
proc fetchValue(id: int): Future[int] {.async.} =
await sleepAsync(100)
result = id * 2
proc main() {.async.} =
let a = await fetchValue(1)
let b = await fetchValue(2)
echo a + b
waitFor main()This program prints 6. Because each await finishes before the next call starts, the two 100 ms sleeps run one after the other, about 200 ms in total. If you start both futures before awaiting either, their waits overlap. That is the concurrency gain, and it applies to waiting, not to computation.
What await does not do
An async procedure runs on the dispatcher’s thread. A long synchronous loop inside it keeps the dispatcher busy, and nothing else progresses until the loop returns. An await placed in the loop does not change that. For CPU-bound work, move the computation to a thread, as described in the next section.
Threads: createThread and spawn
The Nim 2.2.0 manual states that threads are enabled by default in that version, under the --threads:on setting. Run nim --version to confirm your release, and read the manual for that release, because defaults and thread rules can change between versions.
Thread procedures and the no-heap-sharing rule
A procedure that runs on a thread must be marked {.thread.}. The compiler also checks a no-heap-sharing restriction tied to thread-local heaps. When it rejects code, the usual fix is to restructure the program so each thread owns the data it touches, or to pass values across the boundary. Suppressing the check is not a fix.
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createThread
proc worker(n: int) {.thread.} =
echo "worker received ", n
var t: Thread[int]
createThread(t, worker, 42)
joinThread(t)createThread starts the procedure on a new thread and passes it one argument. joinThread blocks the calling thread until the worker returns. Use this form when you manage a fixed set of workers yourself.
spawn and FlowVar
The Nim manual mentions spawn alongside createThread. The std/threadpool module documents it in more detail: spawn schedules a call and returns a FlowVar that holds its eventual result. Dereferencing the FlowVar with the ^ operator blocks until the spawned work completes.
import std/threadpool
proc square(n: int): int = n * n
let f = spawn square(7)
echo ^fThis prints 49. The same module also documents parallel blocks for grouping spawned calls; read its page for their exact completion rules. Because this module is deprecated, check the status section below before using it in new code.
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Channels: passing values between workers
A channel is a queue that one thread writes to and another reads from. Workers exchange values through it rather than reaching into each other’s variables. That pattern keeps ownership clear, which is why it is often the safer way to coordinate threads.
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1Clear out junk files and repair common Windows errors2Fix the driver behind crashes, sound loss and screen glitches3Repair Windows errors before they cause bigger problemsThe exact behavior of Nim’s built-in channels is version-specific. Buffering, whether several producers or consumers may share one channel, which payload types are allowed, and how ownership moves under the memory manager all depend on the release you use. The channels_builtin documentation for your Nim version is the authority on these points. Confirm them there before you design around any of them.
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Shared mutable state: locks, atomics, and guards
When threads must read and write the same data, the Nim manual documents locks, atomics, condition variables, guard annotations, and lock sections. The std/locks module provides the Lock type, initLock, and withLock.
import std/locks
var
lock: Lock
counter {.guard: lock.}: int
initLock lock
proc bump() =
withLock lock:
counter += 1A guard annotation makes the compiler check that a guarded variable is touched only inside a lock section for its lock. The Nim Manual is direct about the limit of that check: “The path analysis is currently unsound, but that doesn’t make it useless.” Treat guards as a net that catches common mistakes, not as proof that a program is free of data races. The sentence comes from the Nim Manual rather than a named author, so cite it that way.
Errors inside threads
- A handled exception in one thread cannot affect another thread.
- An unhandled exception in any thread terminates the whole process, so catch exceptions inside each thread procedure.
- Report failures as part of the result: for example, return a result type that can express an error, rather than relying on an exception to reach the caller.
Is std/threadpool deprecated?
The current online documentation for std/threadpool describes the module as unstable and deprecated, and names the Nimble packages malebolgia, taskpools, and weave as replacements. Treat that as a reason to check before you adopt it, not as a reason to rewrite working code without testing.
- Read each replacement’s own documentation; this article does not compare their APIs or recommend one.
- Confirm that the package supports the Nim release you run.
- Check how recently the package was maintained.
- Expect API differences, so
spawn-style code will need adapting.
Choosing an approach
- Identify the wait or the computation. If the program mostly waits on network, disk, or timers, use async/await with
std/asyncdispatch. - If CPU-heavy work needs several cores, pick a threading model. Use
createThreadfor a fixed set of workers you manage. For many small jobs that return results, use a task library, after checking its documentation. - If workers must exchange values, use channels. Check the
channels_builtindocumentation for your Nim version first. - If workers must share mutable state, protect it. Use locks, atomics, or guards, and keep critical sections short.
- Before writing new code on
std/threadpool, check the status section above and the current documentation of the replacement you intend to use.
The official pages describe what each module is for. They do not measure speed, so no speedup figures appear in this article. Measure your own workload with the approach you choose.
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