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Hardware Transactional Memory (HTM) simplifies concurrent programming and can accelerate multithreaded execution through lock elision. Non-Volatile Memory (NVM) combines the speed and byte addressability of DRAM with the durability of storage, enabling the construction of high-performance, persistent data structures. Unfortunately, the write-back instructions typically needed to ensure post-crash consistency in NVM cause HTM transactions to abort, precluding the straightforward combination of HTM and persistent data structures. The problem goes away on machines with persistent caches, but these require special battery-backed circuitry and are far from commonplace.To combine HTM and persistent data structures, we advocate for buffered durable linearizability (BDL), a relaxed correctness criterion that enables recovery to a "recent" consistent state in the wake of a crash, allowing writes-back to occur outside transactions.Significantly, BDL retains the persistence guarantees of storage systems—such as databases backed by disks or flash—that have relied on buffering for decades.The combination of HTM and buffered durability enables three separate usage scenarios. First, we add durability to an existing HTM-based structure (a van Emde Boas tree due to Khalaji et al.); second, we use HTM to simplify an existing persistent structure (a skiplist due to Wang et al.); third, we "back port" an HTM-based structure optimized for persistent caches (a hash table due to Zhang et al.) to work well on more conventional processors. The first two scenarios yield several-fold improvements in throughput; the third sees very little slowdown. 

Non-volatile Memory (NVM) offers the opportunity to build large, durable B+ trees with markedly higher performance and faster post-crash recovery than is possible with traditional disk- or flash-based persistence. Unfortunately, cache flush and fence instructions, required for crash consistency and failure atomicity on many machines, introduce substantial overhead not present in non-persistent trees, and force additional NVM reads and writes. The overhead is particularly pronounced in workloads that benefit from cache reuse due to good temporal locality or small working sets---traits commonly observed in real-world applications. In this paper, we propose a buffered durable B+ tree (BD+Tree) that improves performance and reduces NVM traffic viarelaxedpersistence. Execution of a BD+Tree is divided intoepochsof a few milliseconds each; if a crash occurs in epoche,the tree recovers to its state as of the end of epoche-2. (The persistence boundary can always be made current with an explicit sync operation, which quickly advances the epoch by 2.) NVM writes within an epoch are aggregated for delayed persistence, thereby increasing cache reuse and reducing traffic to NVM. In comparison to state-of-the-art persistent B+ trees, our micro-benchmark experiments show that BD+Tree can improve throughput by up to 2.4x and reduce NVM writes by up to 90% when working sets are small or workloads exhibit strong temporal locality. On real-world workloads that benefit from cache reuse, BD+Tree realizes throughput improvements of 1.1--2.4x and up to a 99% decrease in NVM writes. Even on uniform workloads, with working sets that significantly exceed cache capacity, BD+Tree still improves throughput by 1--1.3x. The performance advantage of BD+Tree increases with larger caches, suggesting ongoing benefits as CPUs evolve toward gigabyte cache capacities. 

San Diego, CA 

We present a fully lock-free variant of our recent Montage system for persistent data structures. The variant, nbMontage, adds persistence to almost any nonblocking concurrent structure without introducing significant overhead or blocking of any kind. Like its predecessor, nbMontage is buffered durably linearizable: it guarantees that the state recovered in the wake of a crash will represent a consistent prefix of pre-crash execution. Unlike its predecessor, nbMontage ensures wait-free progress of the persistence frontier, thereby bounding the number of recent updates that may be lost on a crash, and allowing a thread to force an update of the frontier (i.e., to perform a sync operation) without the risk of blocking. As an extra benefit, the helping mechanism employed by our wait-free sync significantly reduces its latency. Performance results for nonblocking queues, skip lists, trees, and hash tables rival custom data structures in the literature – dramatically faster than achieved with prior general-purpose systems, and generally within 50% of equivalent non-persistent structures placed in DRAM. 

The emergence of fast, dense, nonvolatile main memory suggests that certain long-lived data might remain in their natural pointerrich format across program runs and hardware reboots. Operations on such data must currently be instrumented with explicit writeback and fence instructions to ensure consistency in the wake of a crash. Techniques to minimize the cost of this instrumentation are an active topic of research. We present what we believe to be the first general-purpose approach to building buffered persistent data structures, and a system, Montage, to support that approach. Montage is built on top of the Ralloc nonblocking persistent allocator. It employs a millisecondgranularity epoch clock, and ensures that no operation appears to span an epoch boundary. It also arranges to persist only that data minimally required to reconstruct the structure after a crash. If a crash occurs in epoch e, all work performed in epochs e and e − 1 is lost, but work from prior epochs is preserved, consistently. As in traditional file and database systems, a sync operation can be used to flush buffers on demand; the Montage sync is extremely fast. We describe the implementation of Montage, argue its correctness, and report unprecedented throughput for persistent queues, sets/mappings, and general graphs. 

The recent emergence of fast, dense, nonvolatile main memory suggests that certain long-lived data structures might remain in their natural, pointer-rich format across program runs and hardware reboots. Operations on such structures must be instrumented with explicit write-back and fence instructions to ensure consistency in the wake of a crash. Techniques to minimize the cost of this instrumentation are an active topic of current research. We present what we believe to be the first general-purpose approach to building buffered durably linearizable persistent data structures, and a system, Montage, to support that approach. Montage is built on top of the Ralloc nonblocking persistent allocator. It employs a slow-ticking epoch clock, and ensures that no operation appears to span an epoch boundary. If a crash occurs in epoch e, all work performed in epochs e and e-1 is lost, but all work from prior epochs is preserved. We describe the implementation of Montage, argue its correctness, and report on experiments confirming excellent performance for operations on queues, sets/mappings, and general graphs.