PETRA
| Autor: | Christina Peterson, Yan Solihin, Ramin Izadpanah, Damian Dechev |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
010302 applied physics
Process state Computer science Distributed computing Transactional memory 02 engineering and technology Linked data Data structure 01 natural sciences Hardware and Architecture 020204 information systems 0103 physical sciences Scalability 0202 electrical engineering electronic engineering information engineering Software transactional memory Persistent data structure Database transaction Software Information Systems |
| Zdroj: | ACM Transactions on Architecture and Code Optimization. 18:1-26 |
| ISSN: | 1544-3973 1544-3566 |
| Popis: | Emerging byte-addressable Non-Volatile Memories (NVMs) enable persistent memory where process state can be recovered after crashes. To enable applications to rely on persistent data, durable data structures with failure-atomic operations have been proposed. However, they lack the ability to allow users to execute a sequence of operations as transactions. Meanwhile, persistent transactional memory (PTM) has been proposed by adding durability to Software Transactional Memory (STM). However, PTM suffers from high performance overheads and low scalability due to false aborts, logging, and ordering constraints on persistence. In this article, we propose PETRA, a new approach for constructing persistent transactional linked data structures. PETRA natively supports transactions, but unlike PTM, relies on the high-level information from the data structure semantics. This gives PETRA unique advantages in the form of high performance and high scalability. Our experimental results using various benchmarks demonstrate the scalability of PETRA in all workloads and transaction sizes. PETRA outperforms the state-of-the-art PTMs by an order of magnitude in transactions of size greater than one, and demonstrates superior performance in transactions of size one. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|