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Byte-addressable persistent memory, such as Intel/Micron 3D XPoint, is an emerging technology that bridges the gap between volatile memory and persistent storage. Data in persistent memory survives crashes and restarts; however, it is challenging to ensure that this data is consistent after failures. Existing approaches incur significant performance costs to ensure crash consistency. This paper introduces Crafty, a new approach for ensuring consistency and atomicity on persistent memory operations using commodity hardware with existing hardware transactional memory (HTM) capabilities, while incurring low overhead. Crafty employs a novel technique called nondestructive undo logging that leverages commodity HTM to control persist ordering. Our evaluation shows that Crafty outperforms state-of-the-art prior work under low contention, and performs competitively under high contention.
Synchronous Mirroring (SM) is a standard approach to building highly-available and fault-tolerant enterprise storage systems. SM ensures strong data consistency by maintaining multiple exact data replicas and synchronously propagating every update to
With the growing DRAM capacity and core count in modern servers, database systems are becoming increasingly multi-engine to feature a heterogeneous set of engines. In particular, a memory-optimized engine and a conventional storage-centric engine may
The most successful unfolding rules used nowadays in the partial evaluation of logic programs are based on well quasi orders (wqo) applied over (covering) ancestors, i.e., a subsequence of the atoms selected during a derivation. Ancestor (sub)sequenc
This paper presents a scalable path- and context-sensitive data-dependence analysis. The key is to address the aliasing-path-explosion problem via a sparse, demand-driven, and fused approach that piggybacks the computation of pointer information with
Python has become a popular programming language because of its excellent programmability. Many modern software packages utilize Python for high-level algorithm design and depend on native libraries written in C/C++/Fortran for efficient computation