Data mining flow graphs in a dynamic compiler

• Author / Creator

  Jocksch, Adam

• This thesis introduces FlowGSP, a general-purpose sequence mining algorithm for flow graphs.
  FlowGSP ranks sequences according to the frequency with which they occur and according to their
  relative cost. This thesis also presents two parallel implementations of FlowGSP. The first implementation uses JavaTM threads and is designed for use on workstations equipped with multi-core
  CPUs. The second implementation is distributed in nature and intended for use on clusters.
  The thesis also presents results from an application of FlowGSP to mine program profiles in
  the context of the development of a dynamic optimizing compiler. Interpreting patterns within raw
  profiling data is extremely difficult and heavily reliant on human intuition.
  FlowGSP has been tested on performance-counter profiles collected from the IBM WebSphere
  Application Server. This investigation identifies a number of sequences which are known to be typical of WebSphere Application Server behavior, as well as some sequences which were previously
  unknown.

• Subjects / Keywords

  • Flow graph
  • Compilers
  • Data mining
  • Hardware counter
  • Parallel

• Graduation date

  Fall 2009

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R35941

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.