Multi-Threading
Base.Threads.@threads
— MacroThreads.@threads [schedule] for ... end
A macro to parallelize a for
loop to run with multiple threads. Splits the iteration space among multiple tasks and runs those tasks on threads according to a scheduling policy. A barrier is placed at the end of the loop which waits for all tasks to finish execution.
The schedule
argument can be used to request a particular scheduling policy. The only currently supported value is :static
, which creates one task per thread and divides the iterations equally among them. Specifying :static
is an error if used from inside another @threads
loop or from a thread other than 1.
The default schedule (used when no schedule
argument is present) is subject to change.
The schedule
argument is available as of Julia 1.5.
Base.Threads.@spawn
— MacroThreads.@spawn expr
Create and run a Task
on any available thread. To wait for the task to finish, call wait
on the result of this macro, or call fetch
to wait and then obtain its return value.
Values can be interpolated into @spawn
via $
, which copies the value directly into the constructed underlying closure. This allows you to insert the value of a variable, isolating the aysnchronous code from changes to the variable's value in the current task.
See the manual chapter on threading for important caveats.
This macro is available as of Julia 1.3.
Interpolating values via $
is available as of Julia 1.4.
Base.Threads.threadid
— FunctionThreads.threadid()
Get the ID number of the current thread of execution. The master thread has ID 1
.
Base.Threads.nthreads
— FunctionThreads.nthreads()
Get the number of threads available to the Julia process. This is the inclusive upper bound on threadid()
.
Synchronization
Base.Threads.Condition
— TypeThreads.Condition([lock])
A thread-safe version of Base.Condition
.
To call wait
or notify
on a Threads.Condition
, you must first call lock
on it. When wait
is called, the lock is atomically released during blocking, and will be reacquired before wait
returns. Therefore idiomatic use of a Threads.Condition
c
looks like the following:
lock(c)
try
while !thing_we_are_waiting_for
wait(c)
end
finally
unlock(c)
end
This functionality requires at least Julia 1.2.
Base.Event
— TypeEvent()
Create a level-triggered event source. Tasks that call wait
on an Event
are suspended and queued until notify
is called on the Event
. After notify
is called, the Event
remains in a signaled state and tasks will no longer block when waiting for it.
This functionality requires at least Julia 1.1.
See also Synchronization.
Atomic operations
The API for atomic operations has not yet been finalized and is likely to change.
Base.Threads.Atomic
— TypeThreads.Atomic{T}
Holds a reference to an object of type T
, ensuring that it is only accessed atomically, i.e. in a thread-safe manner.
Only certain "simple" types can be used atomically, namely the primitive boolean, integer, and float-point types. These are Bool
, Int8
...Int128
, UInt8
...UInt128
, and Float16
...Float64
.
New atomic objects can be created from a non-atomic values; if none is specified, the atomic object is initialized with zero.
Atomic objects can be accessed using the []
notation:
Examples
julia> x = Threads.Atomic{Int}(3)
Base.Threads.Atomic{Int64}(3)
julia> x[] = 1
1
julia> x[]
1
Atomic operations use an atomic_
prefix, such as atomic_add!
, atomic_xchg!
, etc.
Base.Threads.atomic_cas!
— FunctionThreads.atomic_cas!(x::Atomic{T}, cmp::T, newval::T) where T
Atomically compare-and-set x
Atomically compares the value in x
with cmp
. If equal, write newval
to x
. Otherwise, leaves x
unmodified. Returns the old value in x
. By comparing the returned value to cmp
(via ===
) one knows whether x
was modified and now holds the new value newval
.
For further details, see LLVM's cmpxchg
instruction.
This function can be used to implement transactional semantics. Before the transaction, one records the value in x
. After the transaction, the new value is stored only if x
has not been modified in the mean time.
Examples
julia> x = Threads.Atomic{Int}(3)
Base.Threads.Atomic{Int64}(3)
julia> Threads.atomic_cas!(x, 4, 2);
julia> x
Base.Threads.Atomic{Int64}(3)
julia> Threads.atomic_cas!(x, 3, 2);
julia> x
Base.Threads.Atomic{Int64}(2)
Base.Threads.atomic_xchg!
— FunctionThreads.atomic_xchg!(x::Atomic{T}, newval::T) where T
Atomically exchange the value in x
Atomically exchanges the value in x
with newval
. Returns the old value.
For further details, see LLVM's atomicrmw xchg
instruction.
Examples
julia> x = Threads.Atomic{Int}(3)
Base.Threads.Atomic{Int64}(3)
julia> Threads.atomic_xchg!(x, 2)
3
julia> x[]
2
Base.Threads.atomic_add!
— FunctionThreads.atomic_add!(x::Atomic{T}, val::T) where T <: ArithmeticTypes
Atomically add val
to x
Performs x[] += val
atomically. Returns the old value. Not defined for Atomic{Bool}
.
For further details, see LLVM's atomicrmw add
instruction.
Examples
julia> x = Threads.Atomic{Int}(3)
Base.Threads.Atomic{Int64}(3)
julia> Threads.atomic_add!(x, 2)
3
julia> x[]
5
Base.Threads.atomic_sub!
— FunctionThreads.atomic_sub!(x::Atomic{T}, val::T) where T <: ArithmeticTypes
Atomically subtract val
from x
Performs x[] -= val
atomically. Returns the old value. Not defined for Atomic{Bool}
.
For further details, see LLVM's atomicrmw sub
instruction.
Examples
julia> x = Threads.Atomic{Int}(3)
Base.Threads.Atomic{Int64}(3)
julia> Threads.atomic_sub!(x, 2)
3
julia> x[]
1
Base.Threads.atomic_and!
— FunctionThreads.atomic_and!(x::Atomic{T}, val::T) where T
Atomically bitwise-and x
with val
Performs x[] &= val
atomically. Returns the old value.
For further details, see LLVM's atomicrmw and
instruction.
Examples
julia> x = Threads.Atomic{Int}(3)
Base.Threads.Atomic{Int64}(3)
julia> Threads.atomic_and!(x, 2)
3
julia> x[]
2
Base.Threads.atomic_nand!
— FunctionThreads.atomic_nand!(x::Atomic{T}, val::T) where T
Atomically bitwise-nand (not-and) x
with val
Performs x[] = ~(x[] & val)
atomically. Returns the old value.
For further details, see LLVM's atomicrmw nand
instruction.
Examples
julia> x = Threads.Atomic{Int}(3)
Base.Threads.Atomic{Int64}(3)
julia> Threads.atomic_nand!(x, 2)
3
julia> x[]
-3
Base.Threads.atomic_or!
— FunctionThreads.atomic_or!(x::Atomic{T}, val::T) where T
Atomically bitwise-or x
with val
Performs x[] |= val
atomically. Returns the old value.
For further details, see LLVM's atomicrmw or
instruction.
Examples
julia> x = Threads.Atomic{Int}(5)
Base.Threads.Atomic{Int64}(5)
julia> Threads.atomic_or!(x, 7)
5
julia> x[]
7
Base.Threads.atomic_xor!
— FunctionThreads.atomic_xor!(x::Atomic{T}, val::T) where T
Atomically bitwise-xor (exclusive-or) x
with val
Performs x[] $= val
atomically. Returns the old value.
For further details, see LLVM's atomicrmw xor
instruction.
Examples
julia> x = Threads.Atomic{Int}(5)
Base.Threads.Atomic{Int64}(5)
julia> Threads.atomic_xor!(x, 7)
5
julia> x[]
2
Base.Threads.atomic_max!
— FunctionThreads.atomic_max!(x::Atomic{T}, val::T) where T
Atomically store the maximum of x
and val
in x
Performs x[] = max(x[], val)
atomically. Returns the old value.
For further details, see LLVM's atomicrmw max
instruction.
Examples
julia> x = Threads.Atomic{Int}(5)
Base.Threads.Atomic{Int64}(5)
julia> Threads.atomic_max!(x, 7)
5
julia> x[]
7
Base.Threads.atomic_min!
— FunctionThreads.atomic_min!(x::Atomic{T}, val::T) where T
Atomically store the minimum of x
and val
in x
Performs x[] = min(x[], val)
atomically. Returns the old value.
For further details, see LLVM's atomicrmw min
instruction.
Examples
julia> x = Threads.Atomic{Int}(7)
Base.Threads.Atomic{Int64}(7)
julia> Threads.atomic_min!(x, 5)
7
julia> x[]
5
Base.Threads.atomic_fence
— FunctionThreads.atomic_fence()
Insert a sequential-consistency memory fence
Inserts a memory fence with sequentially-consistent ordering semantics. There are algorithms where this is needed, i.e. where an acquire/release ordering is insufficient.
This is likely a very expensive operation. Given that all other atomic operations in Julia already have acquire/release semantics, explicit fences should not be necessary in most cases.
For further details, see LLVM's fence
instruction.
ccall using a threadpool (Experimental)
Base.@threadcall
— Macro@threadcall((cfunc, clib), rettype, (argtypes...), argvals...)
The @threadcall
macro is called in the same way as ccall
but does the work in a different thread. This is useful when you want to call a blocking C function without causing the main julia
thread to become blocked. Concurrency is limited by size of the libuv thread pool, which defaults to 4 threads but can be increased by setting the UV_THREADPOOL_SIZE
environment variable and restarting the julia
process.
Note that the called function should never call back into Julia.
Low-level synchronization primitives
These building blocks are used to create the regular synchronization objects.
Base.Threads.SpinLock
— TypeSpinLock()
Create a non-reentrant, test-and-test-and-set spin lock. Recursive use will result in a deadlock. This kind of lock should only be used around code that takes little time to execute and does not block (e.g. perform I/O). In general, ReentrantLock
should be used instead.
Each lock
must be matched with an unlock
.
Test-and-test-and-set spin locks are quickest up to about 30ish contending threads. If you have more contention than that, different synchronization approaches should be considered.