Concurrency in Kotlin/Native

Workers

Instead of threads Kotlin/Native runtime offers the concept of workers: concurrently executed control flow streams with an associated request queue. Workers are very similar to the actors in the Actor Model. A worker can exchange Kotlin objects with another worker, so that at any moment each mutable object is owned by a single worker, but ownership can be transferred. See section Object transfer and freezing.

Once a worker is started with the Worker.start function call, it can be addressed with its own unique integer worker id. Other workers, or non-worker concurrency primitives, such as OS threads, can send a message to the worker with the execute call.

val future = execute(TransferMode.SAFE, { SomeDataForWorker() }) { // data returned by the second function argument comes to the // worker routine as 'input' parameter. input -> // Here we create an instance to be returned when someone consumes result future. WorkerResult(input.stringParam + " result") } future.consume { // Here we see result returned from routine above. Note that future object or // id could be transferred to another worker, so we don't have to consume future // in same execution context it was obtained. result -> println("result is $result") } 

The call to execute uses a function passed as its second parameter to produce an object subgraph (i.e. set of mutually referring objects) which is then passed as a whole to that worker, it is then no longer available to the thread that initiated the request. This property is checked if the first parameter is TransferMode.SAFE by graph traversal and is just assumed to be true, if it is TransferMode.UNSAFE. The last parameter to execute is a special Kotlin lambda, which is not allowed to capture any state, and is actually invoked in the target worker's context. Once processed, the result is transferred to whatever consumes it in the future, and it is attached to the object graph of that worker/thread.

If an object is transferred in UNSAFE mode and is still accessible from multiple concurrent executors, program will likely crash unexpectedly, so consider that last resort in optimizing, not a general purpose mechanism.

For a more complete example please refer to the workers example in the Kotlin/Native repository.

Object subgraph detachment

An object subgraph without external references can be disconnected using DetachedObjectGraph<T> to a COpaquePointer value, which could be stored in void* data, so the disconnected object subgraphs can be stored in a C data structure, and later attached back with DetachedObjectGraph<T>.attach() in an arbitrary thread or a worker. Combining it with raw memory sharing it allows side channel object transfer between concurrent threads, if the worker mechanisms are insufficient for a particular task. Note, that object detachment may require explicit leaving function holding object references and then performing cyclic garbage collection. For example, code like:

val graph = DetachedObjectGraph { val map = mutableMapOf<String, String>() for (entry in map.entries) { // ... } map } 

will not work as expected and will throw runtime exception, as there are uncollected cycles in the detached graph, while:

val graph = DetachedObjectGraph { { val map = mutableMapOf<String, String>() for (entry in map.entries) { // ... } map }().also { kotlin.native.internal.GC.collect() } } 

will work properly, as holding references will be released, and then cyclic garbage affecting reference counter is collected.

Raw shared memory

Considering the strong ties between Kotlin/Native and C via interoperability, in conjunction with the other mechanisms mentioned above it is possible to build popular data structures, like concurrent hashmap or shared cache with Kotlin/Native. It is possible to rely upon shared C data, and store in it references to detached object subgraphs. Consider the following .def file:

package = global --- typedef struct { int version; void* kotlinObject; } SharedData; SharedData sharedData; 

After running the cinterop tool it can share Kotlin data in a versionized global structure, and interact with it from Kotlin transparently via autogenerated Kotlin like this:

class SharedData(rawPtr: NativePtr) : CStructVar(rawPtr) { var version: Int var kotlinObject: COpaquePointer? } 

So in combination with the top-level variable declared above, it can allow looking at the same memory from different threads and building traditional concurrent structures with platform-specific synchronization primitives.

Atomic primitives and references

Kotlin/Native standard library provides primitives for safe working with concurrently mutable data, namely AtomicInt, AtomicLong, AtomicNativePtr, AtomicReference and FreezableAtomicReference in the package kotlin.native.concurrent. Atomic primitives allows concurrency-safe update operations, such as increment, decrement and compare-and-swap, along with value setters and getters. Atomic primitives are considered always frozen by the runtime, and while their fields can be updated with the regular field.value += 1, it is not concurrency safe. Value must be be changed using dedicated operations, so it is possible to perform concurrent-safe global counters and similar data structures.

Some algorithms require shared mutable references across the multiple workers, for example global mutable configuration could be implemented as an immutable instance of properties list atomically replaced with the new version on configuration update as the whole in a single transaction. This way no inconsistent configuration could be seen, and at the same time configuration could be updated as needed. To achieve such functionality Kotlin/Native runtime provides two related classes: kotlin.native.concurrent.AtomicReference and kotlin.native.concurrent.FreezableAtomicReference. Atomic reference holds reference to a frozen or immutable object, and its value could be updated by set or compare-and-swap operation. Thus, dedicated set of objects could be used to create mutable shared object graphs (of immutable objects). Cycles in the shared memory could be created using atomic references. Kotlin/Native runtime doesn't support garbage collecting cyclic data when reference cycle goes through AtomicReference or frozen FreezableAtomicReference. So to avoid memory leaks atomic references that are potentially parts of shared cyclic data should be zeroed out once no longer needed.

If atomic reference value is attempted to be set to non-frozen value runtime exception is thrown.

Freezable atomic reference is similar to the regular atomic reference, but until frozen behaves like regular box for a reference. After freezing it behaves like an atomic reference, and can only hold a reference to a frozen object.