Robert R. McCormick School of Engineering and Applied Science Electrical Engineering and Computer Science Department Center for Ultra-scale Computing and Information Security at Northwestern University


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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. The well-known applications assembled in this benchmark suite have been collected from research groups in industry and academia. The applications contain highly optimized versions of the data mining algorithms. Scalable versions of the applications are also provided. Such extensions were designed and implemented by developers at Northwestern University. Currently, the benchmark has applications with algorithms based on clustering, association rules, classification, bayesian network, pattern recognition, support vector machines and several other well known data mining methodologies. These applications are used in diverse fields like bioinformatics, network intrusion, customer relationship management, and marketing.
If you would like to contribute any well-known and stable application to our benchmark suite, please do not hesitate to contact us.

List of algorithms and applications


NU-MineBench software package can be obtained from its download page.

Release notes:


NU-MineBench benchmark is an effort to bring in a diverse mix of applications from multiple application domains. Researchers from academia and industry contributed to our efforts. We would like to sincerely thank the following groups and personnel for their valuable contributions (code, technology, algorithms, etc):



Most files in the suite are self explanatory and include comments. In case you have unresolvable issues or if you would like to give suggestions or contribute software, please email us.

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