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  1. Proceedings of the 11th International Workshop on Data Management on New Hardware (DaMoN'15)
  2. The Serial Safety Net: Efficient Concurrency Control on Modern Hardware
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Energy-Efficient In-Memory Data Stores on Hybrid Memory Hierarchies
Beyond the Wall: Near-Data Processing for Databases
Scaling the Memory Power Wall With DRAM-Aware Data Management
NUMA obliviousness through memory mapping
By their fruits shall ye know them: A Data Analyst's Perspective on Massively Parallel System Design
TLB misses: The Missing Issue of Adaptive Radix Tree?
Applying HTM to an OLTP System: No Free Lunch
The Serial Safety Net: Efficient Concurrency Control on Modern Hardware
Efficient Lightweight Compression Alongside Fast Scans
Energy-Efficient Query Processing on Embedded CPU-GPU Architectures
Toward GPUs being mainstream in analytic processing: An initial argument using simple scan-aggregate queries
Ultra-Fast Similarity Search Using Ternary Content Addressable Memory

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The Serial Safety Net: Efficient Concurrency Control on Modern Hardware

Content Provider ACM Digital Library
Author Wang, Tianzheng Pandis, Ippokratis Fekete, Alan Johnson, Ryan
Abstract Concurrency control (CC) algorithms must trade off strictness for performance, with serializable schemes generally paying high cost---both in runtime overhead such as contention on lock tables, and in wasted efforts by aborting transactions---to prevent anomalies. We propose the serial safety net (SSN), a serializability-enforcing certifier for modern hardware with substantial core count and large main memory. SSN can be applied with minimal overhead on top of various CC schemes that offer higher performance but admit anomalies, e.g., snapshot isolation and read committed. We demonstrate the efficiency, accuracy and robustness of SSN using a memory-optimized OLTP engine with different CC schemes. We find that SSN is a promising approach to serializability with low abort rates and robust performance for various workloads.
Starting Page 1
Ending Page 8
Page Count 8
File Format PDF
ISBN 9781450336383
DOI 10.1145/2771937.2771949
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2015-05-31
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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