St³ — the Stealing Static Stack

Lock-free, bounded, work-stealing queues with FIFO stealing and LIFO or FIFO semantic for the worker thread.

Overview

The Go scheduler and the Tokio runtime are examples of high-performance schedulers that rely on fixed-capacity (bounded) work-stealing queues to avoid the allocation and synchronization overhead associated with unbounded queues such as the Chase-Lev work-stealing deque (used in particular by Crossbeam Deque). This is a natural design choice for schedulers that use a global injector queue as the latter often can, at nearly no extra cost, buffer the overflow should a local queue become full. For such applications, St3 provides high-performance, fixed-size, lock-free FIFO and LIFO work-stealing queues.

The FIFO queue is based on the Tokio queue, but provides a somewhat more convenient and more flexible API. The LIFO queue is a novel design with the same API and performance profile as its FIFO counterpart; it can be considered a faster, fixed-size alternative to the Chase-Lev deque.

Usage

Add this to your Cargo.toml:

[dependencies]
st3 = "0.4.1"

Example

use std::thread;
use st3::lifo::Worker;

// Push 4 items into a queue of capacity 256.
let worker = Worker::new(256);
worker.push("a").unwrap();
worker.push("b").unwrap();
worker.push("c").unwrap();
worker.push("d").unwrap();

// Steal items concurrently.
let stealer = worker.stealer();
let th = thread::spawn(move || {
    let other_worker = Worker::new(256);
    // Try to steal half the items and return the actual count of stolen items.
    match stealer.steal(&other_worker, |n| n/2) {
        Ok(actual) => actual,
        Err(_) => 0,
    }
});

// Pop items concurrently.
let mut pop_count = 0;
while worker.pop().is_some() {
    pop_count += 1;
}

// Does it add up?
let steal_count = th.join().unwrap();
assert_eq!(pop_count + steal_count, 4);

Safety — a word of caution

The St³ queues are low-level primitives and as such their implementation relies on unsafe. The test suite makes extensive use of Loom to assess correctness. As amazing as it is, however, Loom is only a tool: it cannot formally prove the absence of data races.

Before St³ sees wider use in the field and receives greater scrutiny, you should exercise caution before using it in mission-critical software. The LIFO queue in particular is a new concurrent algorithm and it is therefore possible that soundness issues will be discovered that weren't caught by the test suite.

Performance

The St³ queues use no atomic fences and very few atomic Read-Modify-Write (RMW) operations. Similarly to the Tokio queue, they needs no RMW for push and only one for pop. Stealing operations require only a single RMW in the LIFO variant and 2 in the FIFO variant.

The first benchmark measures performance in the single-threaded, no-stealing case: a series of 64 push operations (or 256 in the large-batch case) is followed by as many pop operations.

Test CPU: i5-7200U

The second benchmark is a synthetic test that aims at characterizing multi-threaded performance with concurrent stealing. It uses a toy work-stealing executor which schedules on each of 4 workers an arbitrary number of tasks (from 1 to 256), each task being repeated by re-injection onto its worker an arbitrary number of times (from 1 to 100). The number of tasks initially assigned to each workers and the number of times each task is to be repeated are deterministically pre-determined with a pseudo-RNG, meaning that the workload is the same for all benchmarked queues. All queues use the Crossbeam Dequeue work-stealing strategy: half of the tasks are stolen, up to a maximum of 32 tasks. Nevertheless, the re-distribution of tasks via work-stealing is ultimately non-deterministic as it is affected by thread timing.

Given the somewhat simplistic and subjective design of the benchmark, the figures below must be taken with a grain of salt. In particular, this benchmark does not model message-passing.

Test CPU: i5-7200U

ABA

Just like the Tokio queue, the St³ queues are susceptible to ABA. For instance, in a naive implementation, if a steal operation was preempted at the wrong moment for exactly the time necessary to pop a number of items equal to the queue capacity while pushing less items than are popped, once resumed the stealer could attempt to steal more items than are available. ABA is overcome by using buffer positions that can index many times the actual buffer capacity so as to increase the cycle period beyond worst-case preemption.

For this reason, St³ will use 32-bit buffer positions whenever the target supports 64-bit atomics, which should in practice provide full resilience against ABA. Targets that only support 32-bit atomics (e.g. MIPS) will instead use 16-bit buffer positions, which in theory introduces a very remote risk of ABA. Note that Tokio had been using 16-bit positions for all targets up to version 1.21.1, so you probably should not worry too much about it.

Acknowledgements

Although the LIFO implementation ended up quite different, the Tokio FIFO queue was an inspiration which also helped set the goal in terms of performance.

Tokio's queue is itself a modified version of Go's work-stealing queue. Go uses something akin to a Seqlock pattern where stealers optimistically read all items marked for stealing and later discard them if they have been concurrently evicted from the queue. Because of its stricter aliasing rules, Rust makes this pattern hard to implement so the Tokio queue was designed with the ability to "book" the items beforehand, an idea which St³'s LIFO queue borrowed.

License

This software is licensed under the Apache License, Version 2.0 or the MIT license, at your option.

Some assets of the test suite and benchmark may be licensed under different terms, which are explicitly outlined within those assets.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.