# Does @allocated not work with multithreading?
**URL:** https://discourse.julialang.org/t/does-allocated-not-work-with-multithreading/59354
**Category:** Performance
**Tags:** bug, multithreading, memory-allocation
**Created:** [April 15, 2021, 4:14pm UTC](https://discourse.julialang.org/t/does-allocated-not-work-with-multithreading/59354 "2021-04-15T16:14:50Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@nmayhall-vt](https://discourse.julialang.org/u/nmayhall-vt)
#### Post date: [April 15, 2021, 4:14pm UTC](https://discourse.julialang.org/t/does-allocated-not-work-with-multithreading/59354/1 "2021-04-15T16:14:50Z")
I’ve been trying to better undertstand how to find allocations in my code, and I stumbled on this simple MWE which either exposes some limitation of @allocated, or (more likely) a limitation of my understanding.
```julia
function test()
a = @allocated begin
end
if a>0
println(a)
error(" Found an allocation?")
end
end
```
With nothing in the begin/end block, no allocations should be done, and so the function should just finish without an error. This is the case if I just run it on a single thread.
```julia
for _ in 1:10000
test()
end
```
But now doing the same thing in a threaded loop behaves differently (it returns the error message):
```julia
Threads.@threads for _ in 1:10000
test()
end
```
Am I doing something dumb here?
I’m using Julia Version 1.5.2 (2020-09-23):
```nohighlight
Commit 539f3ce943 (2020-09-23 23:17 UTC)
Platform Info:
OS: macOS (x86_64-apple-darwin18.7.0)
CPU: Intel(R) Core(TM) i7-8700B CPU @ 3.20GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-9.0.1 (ORCJIT, skylake)
Environment:
JULIA_NUM_THREADS = 12
```
---
### Author:  [@Mason](https://discourse.julialang.org/u/Mason)
#### Post date: [April 16, 2021, 4:18am UTC](https://discourse.julialang.org/t/does-allocated-not-work-with-multithreading/59354/2 "2021-04-16T04:18:21Z")
Yes, multithreading causes allocations. The allocations are essentially fundamental to being able to coordinate dataflow and communication between threads.
---
### Author:  [@Elrod](https://discourse.julialang.org/u/Elrod)
#### Post date: [April 16, 2021, 4:37am UTC](https://discourse.julialang.org/t/does-allocated-not-work-with-multithreading/59354/3 "2021-04-16T04:37:38Z")
I wouldn’t say they’re essential. BLAS, for example, doesn’t allocate.
---
### Author:  [@tkf](https://discourse.julialang.org/u/tkf)
#### Post date: [April 16, 2021, 5:12am UTC](https://discourse.julialang.org/t/does-allocated-not-work-with-multithreading/59354/4 "2021-04-16T05:12:38Z")
Well, I think it’s fair to say BLAS does not coordinate (arbitrary) dataflow and communication 🙂
> [@nmayhall-vt](#):
>
> exposes some limitation of @allocated
Yes, this is the case. It’s not clearly documented, but `@allocated` cannot be used concurrently. It uses “a global counter” \[1\] to detect allocations. That is to say, with
```julia
@sync begin
@spawn do_some_allocation()
x = @allocated nothing
end
```
`x` can, in principle, include some allocations in `do_some_allocation`.
* * *
1. More specifically this is a set of counters local to OS thread but shared across executions. But at the level of Julia interface, it acts as if a single counter [by combining the set of counters](https://github.com/JuliaLang/julia/blob/29d5158d27ddc3983ae2e373c4cd05569b9ead6c/src/gc.c#L1055-L1069).