Performance Optimization for the Trinity RNA-Seq Assembler (Presentation)

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2015-09-02
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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.
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Presented at 9th Parallel Tools Workshop, September 2-3, 2015 in Dresden, Germany
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high performance computing, transcriptomes, performance analysis
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rted license (http://creativecommons.org/licenses/by/3.0/). This license includes the following terms: You are free to share - to copy, distribute and transmit the work and to remix - to adapt the work under the following conditions: attribution - you must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). For any reuse or distribution, you must make clear to others the license terms of this work
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