Multi-Threading

This experimental interface supports Julia’s multi-threading capabilities. Types and functions described here might (and likely will) change in the future.

Base.Threads.threadid — Function.

Threads.threadid()

Get the ID number of the current thread of execution. The master thread has ID 1.

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Base.Threads.nthreads — Function.

Threads.nthreads()

Get the number of threads available to the Julia process. This is the inclusive upper bound on threadid().

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Base.Threads.@threads — Macro.

Threads.@threads

A macro to parallelize a for-loop to run with multiple threads. This spawns nthreads() number of threads, splits the iteration space amongst them, and iterates in parallel. A barrier is placed at the end of the loop which waits for all the threads to finish execution, and the loop returns.

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Base.Threads.Atomic — Type.

Threads.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.

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Base.Threads.atomic_cas! — Function.

Threads.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)

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Base.Threads.atomic_xchg! — Function.

Threads.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

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Base.Threads.atomic_add! — Function.

Threads.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

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Base.Threads.atomic_sub! — Function.

Threads.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

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Base.Threads.atomic_and! — Function.

Threads.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

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Base.Threads.atomic_nand! — Function.

Threads.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

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Base.Threads.atomic_or! — Function.

Threads.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

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Base.Threads.atomic_xor! — Function.

Threads.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

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Base.Threads.atomic_max! — Function.

Threads.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

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Base.Threads.atomic_min! — Function.

Threads.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

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Base.Threads.atomic_fence — Function.

Threads.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.

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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.

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Low-level synchronization primitives

These building blocks are used to create the regular synchronization objects.

Base.Threads.Mutex — Type.

Mutex()

These are standard system mutexes for locking critical sections of logic.

On Windows, this is a critical section object, on pthreads, this is a pthread_mutex_t.

See also SpinLock for a lighter-weight lock.

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Base.Threads.SpinLock — Type.

SpinLock()

Create a non-reentrant lock. Recursive use will result in a deadlock. 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, perhaps a lock is the wrong way to synchronize.

See also Mutex for a more efficient version on one core or if the lock may be held for a considerable length of time.

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