Automated Debugging of Fragmented Programs in LuNA System
Communications in Computer and Information Science, ISSN: 1865-0937, Vol: 1750 CCIS, Page: 266-280
2022
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
The LuNA system, which was created in ICMMG SB RAS, follows the approach of fragmented programming. The LuNA-program runs in parallel, but the programmer does not specify the behaviour of individual processes or threads when creating it. Instead, the user defines the content of computational fragments that may have dependencies on each other. Then, during the execution of the LuNA-program, the runtime system allocates independent computational fragments and distributes them to computing nodes and cores of the multicomputer.Some properties of the system play significant role, e.g. LuNA is the single assignment language and the execution order of operators in the subprogram body is undefined in general case. That is why LuNA-programs are characterized by specific errors. They are not peculiar neither to sequential programs, nor to parallel in classical technologies (MPI, OpenMP etc.) The paper contains classification of semantic errors that are specific for fragmented programs. The analysis of the various approaches applicability to automated debugging in the LuNA system is given. The paper also describes the operation principle of the tool created by the authors for detecting some popular fragmented program errors. The work of the tool is shown on the example of a test programs with different errors. Since the debugging tool is based on a “post-mortem” analysis, it is important to evaluate overhead. The evaluation results are also given in the paper. The directions of further work are described.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85146697150&origin=inward; http://dx.doi.org/10.1007/978-3-031-24145-1_22; https://link.springer.com/10.1007/978-3-031-24145-1_22; https://dx.doi.org/10.1007/978-3-031-24145-1_22; https://link.springer.com/chapter/10.1007/978-3-031-24145-1_22
Springer Science and Business Media LLC
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