The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
OpenTuner: an extensible framework for program autotuning
Open accessAbstract
Program autotuning has been shown to achieve better or more portable performance in a number of domains. However, autotuners themselves are rarely portable between projects, for a number of reasons: using a domain-informed search space representation is critical to achieving good results; search spaces can be intractably large and require advanced machine learning techniques; and the landscape of search spaces can vary greatly between different problems, sometimes requiring domain specific search techniques to explore efficiently.
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Cites
The Design and Implementation of FFTW3
Frigo, M., & Johnson, S. G. (2005) · Proceedings of the IEEE · doi:10.1109/jproc.2004.840301 · Cited by 5,086
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Automatically Tuned Linear Algebra Software
Whaley, R. C., & Dongarra, J. J. (1998) · Conference on High Performance Computing (Supercomputing) · doi:10.5555/509058.509096 · Cited by 854
The LINPACK Benchmark: past, present and future
Dongarra, J. J., Luszczek, P., & Petitet, A. (2003) · Concurrency and Computation: Practice and Experience · doi:10.1002/cpe.728 · Cited by 813
Dongarra, J. J., Meuer, H.-W., & Strohmaier, E. (1997) · Cited by 663
OSKI: A library of automatically tuned sparse matrix kernels
Vuduc, R., Demmel, J. W., & Yelick, K. A. (2005) · Journal of Physics: Conference Series · doi:10.1088/1742-6596/16/1/071 · Cited by 490
Green: a framework for supporting energy-conscious programming using controlled approximation
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Using Machine Learning to Focus Iterative Optimization
Agakov, F. V., Bonilla, E. V., Cavazos, J. E., Franke, B., Fursin, G., O’boyle, M. F. P., Thomson, J. D., Toussaint, M., & Williams, C. K. I. (2006) · Proceedings of the CGO/Proceedings of the ... CGO · doi:10.1109/cgo.2006.37 · Cited by 426
PetaBricks: a language and compiler for algorithmic choice
Ansel, J., Chan, C., Wong, Y. L., Olszewski, M., Zhao, Q., Edelman, A., & Amarasinghe, S. (2009) · Proceedings of the 30th ACM SIGPLAN Conference on Programming Language Design and Implementation · doi:10.1145/1542476.1542481 · Cited by 355
Self-citation
Cited by
Ansel, J., Yang, E., He, H., Gimelshein, N., Jain, A., Voznesensky, M., Bao, B., Bell, P., Berard, D., Burovski, E., et al. (2024) · Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 · doi:10.1145/3620665.3640366 · Cited by 737
Self-citationThere’s plenty of room at the Top: What will drive computer performance after Moore’s law?
Leiserson, C. E., Thompson, N. C., Emer, J. S., Kuszmaul, B. C., Lampson, B. W., Sanchez, D., & Schardl, T. B. (2020) · Science · doi:10.1126/science.aam9744 · Cited by 469
UNICORN: Runtime Provenance-Based Detector for Advanced Persistent Threats
Han, X., Pasquier, T., Bates, A., Mickens, J., & Seltzer, M. (2020) · Proceedings 2020 Network and Distributed System Security Symposium · doi:10.14722/ndss.2020.24046 · Cited by 349
Bayesian Optimization of HPC Systems for Energy Efficiency
Miyazaki, T., Sato, I., & Shimizu, N. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-92040-5_3 · Cited by 27
GPTuner: An LLM-Based Database Tuning System
Lao, J., Wang, Y., Li, Y., Wang, J., Zhang, Y., Cheng, Z., Chen, W., Tang, M., & Wang, J. (2025) · ACM SIGMOD Record · doi:10.1145/3733620.3733641 · Cited by 17
Metadata
- Authors
- Ansel, J., Kamil, S., Veeramachaneni, K., Ragan-Kelley, J., Bosboom, J., O'Reilly, U.-M., & Amarasinghe, S.
- Venue
- Proceedings of the 23rd international conference on Parallel architectures and compilation
- Publisher
- ACM
- Published
- 2014-08-24
- Pages
- 303-316
- OpenAlex
- W2100218206
- Cited by
- 530
- References
- 26
- FWCI
- 22.94
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Ansel, J., Kamil, S., Veeramachaneni, K., Ragan-Kelley, J., Bosboom, J., O'Reilly, U.-M., & Amarasinghe, S. (2014). OpenTuner: an extensible framework for program autotuning. Proceedings of the 23rd international conference on Parallel architectures and compilation. https://doi.org/10.1145/2628071.2628092
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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