A Family of Relaxed Concurrent Queues for Low-Latency Operations and Item Transfers

The producer-consumer communication over shared memory is a critical function of current scalable systems. Queues that provide low latency and high throughput on highly utilized systems can improve the overall performance perceived by the end users. In order to address this demand, we set as priority to achieve both high operation performance and item transfer speed. The Relaxed Concurrent Queues (RCQs) are a family of queues that we have designed and implemented for that purpose. Our key idea is a relaxed ordering model that splits the enqueue and dequeue operations into a stage of sequential assignment to a queue slot and a stage of concurrent execution across the slots. At each slot, we apply no order restrictions among the operations of the same type. We define several variants of the RCQ algorithms with respect to offered concurrency, required hardware instructions, supported operations, occupied memory space, and precondition handling. For specific RCQ algorithms, we provide pseudo-code definitions and reason about their correctness and progress properties. Additionally, we theoretically estimate and experimentally validate the worst-case distance between an RCQ algorithm and a strict first-in-first-out (FIFO) queue. We developed prototype implementations of the RCQ algorithms and experimentally compare them with several representative strict FIFO and relaxed data structures over a range of workload and system settings. The RCQS algorithm is a provably linearizable lock-free member of the RCQ family. We experimentally show that RCQS achieves factors to orders of magnitude advantage over the state-of-the-art strict or relaxed queue algorithms across several latency and throughput statistics of the queue operations and item transfers.