Dynamic performance tuning of word-based software transactional memory

By Pascal Felber, Christof Fetzer, Torvald Riegel. ACM SIGPLAN Symposium on Principles & Practice of Parallel Programming, 2008

518 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Experimental and Cognitive Psychology, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/57fe2b6acccbba91df0847442d2634ffef7ccfb4

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

1. Håkan Grahn
2. Kian-Lee Tan
3. Beng Chin Ooi
4. Meihui Zhang
5. Hao Zhang
6. Gang Chen
7. Michael M. Swift
8. Steven Swanson

In Experimental and Cognitive Psychology

1. Håkan Grahn

In Hardware and Architecture

1. Håkan Grahn
2. Kian-Lee Tan
3. Beng Chin Ooi
4. Meihui Zhang
5. Hao Zhang
6. Gang Chen
7. Steven Swanson
8. Jian Xu

Citations in the corpus

• Transactional memory (2010, background): “T INY STM [95] is a lock-based, time-based, and word-based software transactional memory system.”
• In-Memory Big Data Management and Processing: A Survey (2015, background): “STM Much Atomic Operation Large TinySTM [159], Clojure [160], Haskell [161] HTM No or Little Cache, Bus Protocol Small Intel TSX [162], AMD ASF [163]”
• Mnemosyne: lightweight persistent memory (2011, background): “Mnemosyne relies on TinySTM s existing global times­tamp counter, which is incremented at every transaction comple­tion.”