@article{
 title = {Performance Optimization for the Trinity RNA-Seq Assembler},
 type = {article},
 year = {2015},
 websites = {http://hdl.handle.net/2022/20490},
 publisher = {Springer},
 id = {5c9e7b4f-d9a2-3b72-b25a-2cdab705f453},
 created = {2018-02-27T18:07:27.239Z},
 file_attached = {false},
 profile_id = {42d295c0-0737-38d6-8b43-508cab6ea85d},
 group_id = {27e0553c-8ec0-31bd-b42c-825b8a5a9ae8},
 last_modified = {2018-02-27T18:07:27.239Z},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {false},
 hidden = {false},
 source_type = {article},
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 notes = {Article from presentation at 9th Parallel Tools Workshop, September 2-3, 2015 in Dresden, Germany},
 private_publication = {false},
 abstract = {Utilizing the enormous computing resources of high performance computing systems is anything but a trivial task. Performance analysis tools are designed to assist developers in this challenging task by helping to understand the application behavior and identify critical performance issues. In this paper we share our efforts and experiences in analyzing and optimizing Trinity, a well-established framework for the de novo reconstruction of transcriptomes from RNA-seq reads. Thereby, we try to reflect all aspects of the ongoing performance engineering: the identification of optimization targets, the code improvements resulting in 20% overall runtime reduction, as well as the challenges we encountered getting there.},
 bibtype = {article},
 author = {Wagner, M and Fulton, B and Henschel, R},
 journal = {Tools for High Performance Computing}
}

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