391,988 research outputs found
Cache-Oblivious Persistence
Partial persistence is a general transformation that takes a data structure
and allows queries to be executed on any past state of the structure. The
cache-oblivious model is the leading model of a modern multi-level memory
hierarchy.We present the first general transformation for making
cache-oblivious model data structures partially persistent
Fine-Grain Checkpointing with In-Cache-Line Logging
Non-Volatile Memory offers the possibility of implementing high-performance,
durable data structures. However, achieving performance comparable to
well-designed data structures in non-persistent (transient) memory is
difficult, primarily because of the cost of ensuring the order in which memory
writes reach NVM. Often, this requires flushing data to NVM and waiting a full
memory round-trip time.
In this paper, we introduce two new techniques: Fine-Grained Checkpointing,
which ensures a consistent, quickly recoverable data structure in NVM after a
system failure, and In-Cache-Line Logging, an undo-logging technique that
enables recovery of earlier state without requiring cache-line flushes in the
normal case. We implemented these techniques in the Masstree data structure,
making it persistent and demonstrating the ease of applying them to a highly
optimized system and their low (5.9-15.4\%) runtime overhead cost.Comment: In 2019 Architectural Support for Programming Languages and Operating
Systems (ASPLOS 19), April 13, 2019, Providence, RI, US
Endurable Transient Inconsistency in Byte-Addressable Persistent B+-Tree
Department of Computer Science and EngineeringWith the emergence of byte-addressable persistent memory (PM), a cache line, instead of a page, is expected to be the unit of data transfer between volatile and non-volatile devices, but the failure-atomicity of write operations is guaranteed in the granularity of 8 bytes rather than cache lines. This granularity mismatch problem has generated interest in redesigning block-based data structures such as B+-trees. However, various methods of modifying B+-trees for PM degrade the efficiency of B+-trees, and attempts have been made to use in-memory data structures for PM.
In this study, we develop Failure-Atomic ShifT (FAST) and Failure-Atomic In-place Rebalance (FAIR) algorithms to resolve the granularity mismatch problem. Every 8-byte store instruction used in the FAST and FAIR algorithms transforms a B+-tree into another consistent state or a {\it transient inconsistent} state that read operations can tolerate. By making read operations tolerate transient inconsistency, we can avoid expensive copy-on-write, logging, and even the necessity of read latches so that read transactions can be non-blocking. Our experimental results show that legacy B+-trees with FAST and FAIR schemes outperform the state-of-the-art persistent indexing structures by a large margin.clos
PROSET — A Language for Prototyping with Sets
We discuss the prototyping language PROSET(Prototyping with Sets) as a language for experimental and evolutionary prototyping, focusing its attention on algorithm design. Some of PROSET’s features include generative communication, flexible exception handling and the integration of persistence. A discussion of some issues pertaining to the compiler and the programming environment conclude the pape
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