Triple buffering in Rust

What is this?

This is an implementation of triple buffering written in Rust. You may find it useful for the following class of thread synchronization problems:

• There is one producer thread and one consumer thread
• The producer wants to update a shared memory value frequently
• The consumer wants to access the latest update from the producer at any time

It is currently used as follows:

```rust // Create a triple buffer of any Clone type: let buf = TripleBuffer::new(0);

// Split it into an input and output interface, to be respectively sent to // the producer thread and the consumer thread: let (mut bufinput, mut bufoutput) = buf.split();

// The producer can move a value into the buffer at any time buf_input.write(42);

// The consumer can access the latest value from the producer at any time let latestvalueref = bufoutput.read(); asserteq!(*latestvalueref, 42); ```

Give me details! How does it compare to alternatives?

Compared to a mutex:

• Only works in single-producer, single-consumer scenarios
• Is nonblocking, and more precisely bounded wait-free. Concurrent accesses will be slowed down by cache contention, but no deadlock, livelock, or thread scheduling induced slowdown is possible.
• Allows the producer and consumer to work simultaneously
• Uses a lot more memory (3x payload + 4 integers vs 1x payload + 1 bool)
• Does not allow in-place updates, new value must be cloned or moved
• Should be slower if updates are rare, faster if updates are frequent

Compared to the read-copy-update (RCU) primitive from the Linux kernel:

• Only works in single-producer, single-consumer scenarios
• Has higher readout overhead on relaxed-memory architectures (ARM, POWER...)
• Does not require accounting for reader "grace periods": once the reader has gotten access to the latest value, the synchronization transaction is over
• Does not use the slow compare-and-swap hardware primitive on update
• Does not suffer from the ABA problem, allowing much simpler code
• Allocates memory on initialization only, rather than on every update
• May use more memory (3x payload + 4 integers vs 1x pointer + amount of payloads and refcounts that depends on the readout and update pattern)
• Should be slower if updates are rare, faster if updates are frequent

Compared to sending the updates on a message queue:

• Only works in single-producer, single-consumer scenarios (queues can work in other scenarios, although the implementations are much less efficient)
• Consumer only has access to the latest state, not the previous ones
• Consumer does not need to get through every previous state
• Is nonblocking AND uses bounded amounts of memory (with queues, it's a choice)
• Can transmit information in a single move, rather than two
• Should be faster for any compatible use case

In short, triple buffering is what you're after in scenarios where a shared memory location is updated frequently by a single writer, read by a single reader who only wants the latest version, and you can spare some RAM.

• If you need multiple producers and consumers, look somewhere else
• If you can't tolerate the RAM overhead or want to update the data in place, try a Mutex instead (or possibly an RWLock)
• If the shared value is updated very rarely (e.g. every second), try an RCU
• If the consumer must get every update, try a message queue

How do I know your unsafe lock-free code is working?

By running the tests, of course! Which is unfortunately currently harder than I'd like it to be.

First of all, we have sequential tests, which are very thorough but obviously do not check the lock-free/synchronization part. You run them as follows:

$ cargo test --release

Then we have a concurrent test where a reader thread continuously observes the values from a rate-limited writer thread, and makes sure that he can see every single update without any incorrect value slipping in the middle.

This test is more important, but it is also harder to run because one must first check some assumptions:

• The testing host must have at least 2 physical CPU cores to test all possible race conditions
• No other code should be eating CPU in the background. Including other tests.
• As the proper writing rate is system-dependent, what is configured in this test may not be appropriate for your machine.

Taking this and the relatively long run time (~10 s) into account, this test is ignored by default.

Finally, we have benchmarks, which allow you to test how well the code is performing on your machine. Because cargo bench has not yet landed in Stable Rust, these benchmarks masquerade as tests, which make them a bit unpleasant to run. I apologize for the inconvenience.

To run the concurrent test and the benchmarks, make sure no one is eating CPU in the background and do:

$ cargo test --release -- --ignored --nocapture --test-threads=1

Here is a guide to interpreting the benchmark results:

• clean_read measures the triple buffer readout time when the data has not changed. It should be extremely fast (a couple of CPU clock cycles).
• write measures the amount of time it takes to write data in the triple buffer when no one is reading.
• write_and_dirty_read performs a write as before, immediately followed by a sequential read. To get the dirty read performance, substract the write time from that result. Writes and dirty read should take comparable time.
• concurrent_write measures the write performance when a reader is continuously reading. Expect significantly worse performance: lock-free techniques can help against contention, but are not a panacea.
• concurrent_read measures the read performance when a writer is continuously writing. The performance should be even worse than for writes, because the reading CPU core also needs to fetch the data from the writer's cache.

On my laptop's CPU (Intel Core i7-4720HQ), typical results are as follows:

• Write: 7.7 ns
• Clean read: 0.85 ns
• Dirty read: 7.2 ns
• Concurrent write: 45 ns
• Concurrent read: 88 ns

License

This crate is distributed under the terms of the LGPLv3 license. See the LICENSE-LGPL-3.0.md file for details.

More relaxed licensing (Apache, MIT, BSD...) may also be negociated, in exchange of a financial contribution. Contact me for details at knightsofni AT gmx DOTCOM.