# Triple buffering in Rust
[](https://crates.io/crates/triple_buffer)
[](https://docs.rs/triple_buffer/)
[](https://travis-ci.org/HadrienG2/triple-buffer)
## 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 periodically
- 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 buf_input, mut buf_output) = 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 latest_value_ref = buf_output.read();
assert_eq!(*latest_value_ref, 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 and in-place updates are much more
efficient than moves, faster otherwise.
Compared to the read-copy-update (RCU) primitive from the Linux kernel:
- Only works in single-producer, single-consumer scenarios
- Has higher dirty read 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 inefficient 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, look somewhere else
- If you need multiple consumers, you may be interested in my related "SPMC
buffer" work, which basically extends triple buffering to multiple consumers
- 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. Again, a significant hit is to be expected.
On my laptop's CPU (Intel Core i7-4720HQ), typical results are as follows:
* Write: 7.4 ns
* Clean read: 0.75 ns
* Dirty read: 9.4 ns
* Concurrent write: 41 ns
* Concurrent read: 98 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
knights_of_ni AT gmx DOTCOM.