STAMP: Stanford Transactional Applications for Multi-Processing
By Chi Cao Minh, Jaewoong Chung, Christos Kozyrakis, Kunle Olukotun. IEEE International Symposium on Workload Characterization, 2008
1,007 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Hardware and Architecture
View Paper: https://www.semanticscholar.org/paper/e04d1a5f37bc62ca98079cd338e0e5fd9c6b2c07
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
- T. Harris
- J. Larus
- Ravi Rajwar
- Michael Lee Scott
- Michael F. Spear
- Danny Dig
- Luke Dalessandro
- Håkan Grahn
In Hardware and Architecture
- T. Harris
- J. Larus
- Ravi Rajwar
- Michael Lee Scott
- Michael F. Spear
- Luke Dalessandro
- Håkan Grahn
- Keir Fraser
Citations in the corpus
- Transactional Memory, 2nd edition (2010, background): “2 Applications and Computational Kernels The Stanford Transactional Applications for Multi-Processing benchmark suite (STAMP) provides eight applications that have been structured to use transactions [47].”
- A type and effect system for deterministic parallel Java (2009, methodology): “Using the DPJ compiler, we studied the following programs: Parallel merge sort, two codes from the Java Grande parallel benchmark suite (a Monte Carlo financial simulation and IDEA encryption), the force computation from the Barnes-Hut n-body simulation [45], k-means clustering from the STAMP benchm”
- NOrec: streamlining STM by abolishing ownership records (2010, methodology): “We use the RSTM RBTree microbenchmark [31] to isolate performance in specific circumstances, and the STAMP benchmark suite [26] for overall performance in larger programs.”