NU-MineBench
Core Team:
- Jay Pisharath
- Ying Liu
- Berkin Ozisikyilmaz
- Ramanathan Narayanan
- Wei-keng Liao
- Alok Choudhary (PI)
- Gokhan Memik
Sponsors:
- National Science Foundation (grants CCF-0444405, CNS-0406341, CCR-0325207, CNS-0551639, CNS-0551551)
- Department of Energy (grant DE-FC02-01ER25485)
- Intel Corporation
NU-MineBench
Description:
NU-MineBench is a data mining benchmark suite containing a mix of several representative data mining applications from different application domains. This benchmark is intended for use in computer architecture research, systems research, performance evaluation, and high-performance computing. Details...
Acknowledgements:
NU-MineBench is partially made possible by NSF grant CNS-0551639 to Northwestern University and grant CNS-0551551 to University of Minnesota.Acknowledgement of other contributions (click here)
Publications:
There have been numerous publications under this project and the list can be accessed here.Download:
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PLEASE NOTE: NU-MineBench is a copyright of CUCIS@Northwestern. This benchmark is intended for use in computer architecture research, systems research, performance evaluation and high-performance computing. The codes in the suite have been modified by the development team at Northwestern University in order to produce a uniform and consolidated benchmark suite. All rights reserved.
NEWLY ADDED: Data generator for clustering algorithms. (December 2010). It can be downloaded by clicking the link for NU-MineBench version 3.0. We have also used IBM Quest Data Generator to create syntethic data sets for association rule mining as well as classification applications. The data generator can be downloaded from IBM's website.
New applications based Approximate Frequent Pattern Mining Algorithms (October 2008)
- NU-MineBench version 3.0 code and dataset download - NU-MineBench-3.0
- NU-MineBench version 2.0 code and dataset download - NU-MineBench-2.0
- README file - README.pdf
- Our technial report for NU-MineBench-2.0 - CUCIS-2004-08-001.pdf
- Older Versions (Click here)