The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Improving performance via mini-applications.
Open accessAbstract
Application performance is determined by a combination of many choices: hardware platform, runtime environment, languages and compilers used, algorithm choice and implementation, and more. In this complicated environment, we find that the use of mini-applications - small self-contained proxies for real applications - is an excellent approach for rapidly exploring the parameter space of all these choices. Furthermore, use of mini-applications enriches the interaction between application, library and computer system developers by providing explicit functioning software and concrete performance results that lead to detailed, focused discussions of design trade-offs, algorithm choices and runtime performance issues. In this paper we discuss a collection of mini-applications and demonstrate how we use them to analyze and improve application performance on new and future computer platforms.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Fast Parallel Algorithms for Short-Range Molecular Dynamics
Plimpton, S. (1995) · Journal of Computational Physics · doi:10.1006/jcph.1995.1039 · Cited by 44,721
Bailey, D. H., Barszcz, E., Barton, J. T., Browning, D. S., Carter, R. L., Dagum, L., Fatoohi, R. A., Frederickson, P. O., Lasinski, T. A., Schreiber, R. S., et al. (1991) · The International Journal of Supercomputing Applications · doi:10.1177/109434209100500306 · Cited by 2,395
Dongarra, J. J., Meuer, H.-W., & Strohmaier, E. (1997) · Cited by 663
S12---The HPC Challenge (HPCC) benchmark suite
Luszczek, P. R., Bailey, D. H., Dongarra, J. J., Kepner, J., Lucas, R. F., Rabenseifner, R., & Takahashi, D. (2006) · Proceedings of the 2006 ACM/IEEE conference on Supercomputing - SC '06 · doi:10.1145/1188455.1188677 · Cited by 317
TOP500 Supercomputer sites 11/2000
Meuer, H. W., Strohmaier, E., Dongarra, J. J., & Simon, H. D. (2000) · doi:10.2172/843058 · Cited by 220
Analysis of benchmark characteristics and benchmark performance prediction
Saavedra, R. H., & Smith, A. J. (1996) · ACM Transactions on Computer Systems · doi:10.1145/235543.235545 · Cited by 209
How well can simple metrics represent the performance of HPC applications?
Carrington, L., Laurenzano, M. A., Snavely, A., et al. (2005) · Proceedings - Supercomputing · doi:10.1109/sc.2005.33 · Cited by 53
Cited by
Counterfactual Explanations for Multivariate Time Series
Ates, E., Aksar, B., Leung, V. J., & Coskun, A. K. (2021) · 2021 International Conference on Applied Artificial Intelligence (ICAPAI) · doi:10.1109/icapai49758.2021.9462056 · Cited by 88
First Experiences in Performance Benchmarking with the New SPEChpc 2021 Suites
Brunst, H., Chandrasekaran, S., Ciorba, F. M., Hagerty, N., Henschel, R., Juckeland, G., Li, J., Vergara, V. G. M., Wienke, S., & Zavala, M. (2022) · 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid) · doi:10.1109/ccgrid54584.2022.00077 · Cited by 22
Metadata
- Authors
- Crozier, P., Thornquist, H., Numrich, R., Williams, A., Edwards, H., Keiter, E., Rajan, M., Willenbring, J., Doerfler, D., & Heroux, M.
- Published
- 2009-09-01
- OpenAlex
- W2095954861
- Cited by
- 448
- References
- 7
- Type
- report
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Improving performance via mini-applications. https://app.cochat.ai/papers/10.2172/993908
- The paper
- Crozier, P., Thornquist, H., Numrich, R., Williams, A., Edwards, H., Keiter, E., Rajan, M., Willenbring, J., Doerfler, D., & Heroux, M. (2009). Improving performance via mini-applications. https://doi.org/10.2172/993908
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
