Efficient algorithms for persistent transactional memory

Abstract

Durable techniques coupled with transactional semantics provide to application developers the guarantee that data is saved consistently in persistent memory (PM), even in the event of a non-corrupting failure. Persistence fences and flush instructions are known to have a significant impact on the throughput of persistent transactions. In this paper we explore different trade-offs in terms of memory usage vs. number of fences and flushes. We present two new algorithms, named Trinity and Quadra, for durable transactions on PM and implement each of them in the form of a user-level library persistent transactional memory (PTM). Quadra achieves the lower bound with respect to the number of persistence fences and executes one flush instruction per modified cache line. Trinity can be easily combined with concurrency control techniques based on fine grain locking, and we have integrated it with our TL2 adaptation, with eager locking and write-through update strategy. Moreover, the combination of Trinity and TL2 into a PTM provides good scalability for data structures and workloads with a disjoint access pattern. We used this disjoint PTM to implement a key-value (KV) store with durable linearizable transactions. When compared with previous work, our TL2 KV store provides better throughput in nearly all experiments.