2023/02/25 by Ajay Singh, Trevor Brown, Singh, Ajay +3
Computer Science · #Cloud Computing and Resource Management #D.1.3 #D.3.4 #Distributed #Distributed systems and fault tolerance #E.1 #FOS: Computer and information sciences #Hardware Architecture (cs.AR) #Parallel #Parallel Computing and Optimization Techniques #Programming Languages (cs.PL) #and Cluster Computing (cs.DC)
paper · pdf · doi:10.48550/arxiv.2302.12958
openalex publication_date 2023/02/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
Safe memory reclamation (SMR) algorithms are crucial for preventing use-after-free errors in optimistic data structures. SMR algorithms typically delay reclamation for safety and reclaim objects in batches for efficiency. It is difficult to strike a balance between performance and space efficiency. Small batch sizes and frequent reclamation attempts lead to high overhead, while freeing large batches can lead to long program interruptions and high memory footprints. An ideal SMR algorithm would forgo batching, and reclaim memory immediately, without suffering high reclamation overheads. To this end, we propose Conditional Access: a set of hardware instructions that offer immediate reclamation and low overhead in optimistic data structures. Conditional Access harnesses cache coherence to enable threads to efficiently detect potential use-after-free errors without explicit shared memory communication, and without introducing additional coherence traffic. We implement and evaluate Conditional Access in Graphite, a multicore simulator. Our experiments show that Conditional Access can rival the performance of highly optimized and carefully tuned SMR algorithms while simultaneously allowing immediate reclamation. This results in concurrent data structures with similar memory footprints to their sequential counterparts.