Performance Optimization for the Trinity RNA-Seq Assembler

  • Michael WagnerEmail author
  • Ben Fulton
  • Robert Henschel
Conference paper


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 22 % overall runtime reduction, as well as the challenges we encountered getting there.


Poor Scaling Parallel Region Runtime Behavior High Performance Computing System OpenMP Thread 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We like to thank the Score-P team, in particular, Ronny Tschüter and Bert Wesarg for their friendly and prompt support.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Barcelona Supercomputing CenterBarcelonaSpain
  2. 2.Center for Information Services and High Performance ComputingTechnische Universität DresdenDresdenGermany
  3. 3.Scientific Applications and Performance Tuning Indiana UniversityBloomingtonUSA

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