Performance Impact of Lock-Free Algorithms on Multicore Communication APIs
This addresses performance bottlenecks for developers of embedded and real-time systems, though it is incremental as it builds on existing lock-free algorithm concepts.
The paper tackled the problem of lock management overhead in multicore communication APIs by implementing lock-free messaging, resulting in improved performance where migration to multicore hardware degraded lock-based performance and increased lock-free performance.
Data race conditions in multi-tasking software applications are prevented by serializing access to shared memory resources, ensuring data consistency and deterministic behavior. Traditionally tasks acquire and release locks to synchronize operations on shared memory. Unfortunately, lock management can add significant processing overhead especially for multicore deployments where tasks on different cores convoy in queues waiting to acquire a lock. Implementing more than one lock introduces the risk of deadlock and using spinlocks constrains which cores a task can run on. The better alternative is to eliminate locks and validate that real-time properties are met, which is not directly considered in many embedded applications. Removing the locks is non-trivial and packaging lock-free algorithms for developers reduces the possibility of concurrency defects. This paper details how a multicore communication API implementation is enhanced to support lock-free messaging and the impact this has on data exchange latency between tasks. Throughput and latency are compared on Windows and Linux between lock-based and lock-free implementations for data exchange of messages, packets, and scalars. A model of the lock-free exchange predicts performance at the system architecture level and provides a stop criterion for the refactoring. The results show that migration from single to multicore hardware architectures degrades lock-based performance, and increases lock-free performance.