I think sending messages is more about the way you think about concurrency, more than the implementation.
I have always found the "one thread doing "while True receive message, handle message" much easier to reason about than "remember to lock this chunk of data in case more than one thread should access it"
[1] at the very least you will need one queue for each cpu pair, but that's yet another layer of complication.
https://www.erlang.org/blog/parallel-signal-sending-optimiza...
1. One scheduler per core. 2. Schedulers run one actor behaviour at a time. 3. When a scheduler has an empty work queue, they will steal work from other schedulers. 4. The number of schedulers will scale up and down with the amount of work (but never more than number of cores).
There are various parameters you can change to alter scheduler behaviour should your pattern of use need it.
That's a valid point of view, but Pony's claim to which I objected is about performance, not ease-of-use or convenience.
No, you also need synchronization operations on the sending and the receiving end, even if you have a single sender and a single receiver. That's because message queues are implemented on top of shared memory – there's no way around this on general-purpose hardware.
I think of pony actors in the same way as I think of erlang actors. They have a "mailbox", and when they receive a message, they wake up, execute some amount of code, and then go back to sleep.
This is how I think about it. This is not how it is actually implemented.
Here's the key that I think many people miss about pony.
Referential Capabilities DO NOT EXIST at runtime.
So let's talk passing a String iso from Actor A, to Actor B. (iso is the capability that guarantees that this is the only reference to this object):
// This is code in Actor A
actorB.some_behaviour_call(consume myisostring)
The reference to myisostring then gets sent to Actor B via its mailbox.
If ActorB was idle, then the message receive will cause Actor B to be scheduled and it will receive the reference to that String iso - completely isolated.
Now, if we're going to measure "performance of passing data between threads" as latency per transaction, then actor contention on a scheduler is going to be a bigger factor.
If you're measuring performance across an entire system with millions of these actions occurring, then I would argue that this approach would be faster as there is no spinning involved.
Lockfree spinlocks will only waste cycles on one CPU. A huge difference when you have dozens and hundreds of cores.
Because modern mutexes are so cheap (only 1 byte directly in the data structure, no heap allocation), you can do very fine-grained locking. This way, a mutex will almost never be contended. Keep in mind that a reader waiting on an empty queue or a writer waiting on a full queue will also involve syscalls.
> […] and likely stalls all the CPUs on your machine.
Huh? Where did you get this idea? Only the waiting thread will be blocked, and it won't "stall" the core, let alone the entire CPU.
By the way, if all your threads are waiting on a single mutex, then your architecture is wrong. In the equivalent case, all your actors would be waiting on one central actor as well, so you'd have the same loss of parallelism.
No. Modern mutex implementations [1] are extremely efficient, require only 1 byte of memory (no heap allocation), and are almost free when there's no contention on the lock – certainly much faster and much lower latency than sending messages between actors.
[1] Like the parking_lot crate for Rust.