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SiMoD '23: Proceedings of the 1st Workshop on Simplicity in Management of Data
ACM2023 Proceeding
Publisher:
  • Association for Computing Machinery
  • New York
  • NY
  • United States
Conference:
SiMoD '23: 1st Workshop on Simplicity in Management of Data Bellevue WA USA 23 June 2023
ISBN:
979-8-4007-0783-4
Published:
17 July 2023

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Best Paper
Lock-Free Buffer Managers Do Not Require Delayed Memory Reclamation

High-performance data systems running on modern many-core CPUs should not require readers to acquire physical locks. There exist multiple synchronization schemes that allow this, but they all require a solution for concurrent memory reclamation. In ...

research-article
Open Access
Cooperative Memory Management for Table and Temporary Data

The traditional paradigm for managing memory in database management systems (DBMS) treats memory used for caching table data and memory for temporary data as separate entities. This leads to inefficient utilization of the available memory capacity for ...

research-article
Simplicity done right for SIMDified query processing on CPU and FPGA

We present a simple but effective solution idea to port SIMDified query processing code to Intel® FPGA cards for acceleration. The main advantage of our approach is the seamless integration with existing SIMD abstraction libraries originally developed ...

research-article
Learning from Uncurated Regular Expressions for Semantic Type Classification

Significant work has been done on learning regular expressions from a set of data values. Depending on the domain, this approach can be very successful. However, significant time is required to learn these expressions and the resulting expressions can ...

research-article
Open Access
Hybrid Index Selection Using Integer Linear Programming Based on Cached Cost Estimates of Heuristic Approaches

Indexes are essential for speeding up database workloads. Existing index selection approaches have different strengths and weaknesses. On the one hand, approaches based on integer linear programming (ILP) guarantee optimal solutions but cannot consider ...

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