Breaking the memory wall in MonetDB
By Peter A. Boncz, Martin Leopold Kersten, Stefan Manegold. CACM, 2008
305 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/ab4e0d6c59196243ab8d7f8644ecff86708fbefe
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Matt Crane
- Joel M. Mackenzie
- Jimmy J. Lin
- J. Shane Culpepper
- Andrew Trotman
- Dean M. Tullsen
- David R. Cheriton
- Nuwan Jayasena
In Computer Vision and Pattern Recognition
- Geoffrey P. Ellis
- Florian Mansmann
- J. Shane Culpepper
- Daniel A. Keim
- Jimmy J. Lin
- Andrew Trotman
- Jörn Kohlhammer
- Dean M. Tullsen
In Signal Processing
- Matt Crane
- Jimmy J. Lin
- Joel M. Mackenzie
- J. Shane Culpepper
- Andrew Trotman
- Geoffrey P. Ellis
- Dean M. Tullsen
- Daniel A. Keim
Citations in the corpus
- A Comparison of Document-at-a-Time and Score-at-a-Time Query Evaluation (2017, background): “This is not a new observation, as the lesson is well-known in the database community [6, 32], but our experiments nicely summarize the performance characteristics of modern processor architectures in the context of information retrieval algorithms.”
- Mastering the Information Age - Solving Problems with Visual Analytics (2010, background): “MonetDB[18] is a more general-purpose transactional database engine developed at CWI in Amsterdam that is also column-based.”
- Horton Tables: Fast Hash Tables for In-Memory Data-Intensive Computing (2016, background): “However, although BCHTs are higher-performing than other open addressing schemes [60, 64], we find that as the performance of modern computing systems becomes increasingly constrained by memory bandwidth [1, 11, 52, 70], they too suffer from a number of inefficiencies that originate from how data is”