Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Design, Modeling, and Evaluation of a Scalable Multi-level Checkpointing System
2010335 citationsAdam Moody, Kathryn Mohror et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Bronis R. de Supinski
Since
Specialization
Citations
This map shows the geographic impact of Bronis R. de Supinski's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bronis R. de Supinski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bronis R. de Supinski more than expected).
Fields of papers citing papers by Bronis R. de Supinski
This network shows the impact of papers produced by Bronis R. de Supinski. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bronis R. de Supinski. The network helps show where Bronis R. de Supinski may publish in the future.
Co-authorship network of co-authors of Bronis R. de Supinski
This figure shows the co-authorship network connecting the top 25 collaborators of Bronis R. de Supinski.
A scholar is included among the top collaborators of Bronis R. de Supinski based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Bronis R. de Supinski. Bronis R. de Supinski is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Roberts, David, et al.. (2015). HpMC. Research Portal (Queen's University Belfast). 167–178.19 indexed citations
7.
Sato, Kento, Todd Gamblin, Adam Moody, et al.. (2012). Design and modeling of non-blocking checkpoint system. IEEE International Conference on High Performance Computing, Data, and Analytics. 39.3 indexed citations
Müller, Matthias, Bronis R. de Supinski, & Barbara Chapman. (2009). Evolving OpenMP in an age of extreme parallelism : 5th International Workshop on OpenMP, IWOMP 2009, Dresden, Germany, June 3-5, 2009 : proceedings. Springer eBooks.1 indexed citations
11.
Supinski, Bronis R. de, et al.. (2008). Scalable load-balance measurement for SPMD codes. IEEE International Conference on High Performance Computing, Data, and Analytics. 46.29 indexed citations
12.
Supinski, Bronis R. de, et al.. (2008). An Open Infrastructure for Scalable, Reconfigurable Analysis. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).
Schordan, Markus, et al.. (2003). Semantic-Driven Parallelization of Loops Operating on User-Defined Containers. University of North Texas Digital Library (University of North Texas).1 indexed citations
18.
Supinski, Bronis R. de, et al.. (2001). A Quantitative Measure of Memory Reference Regularity. University of North Texas Digital Library (University of North Texas).1 indexed citations
19.
Supinski, Bronis R. de, et al.. (1999). Experience with mixed MPI/threaded programming models. University of North Texas Digital Library (University of North Texas). 2907–2912.1 indexed citations
20.
Supinski, Bronis R. de, et al.. (1999). Benchmarking Pthreads performance. University of North Texas Digital Library (University of North Texas). 1985–1991.2 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.