The Scientific-Industrial Advisory Board (SIAB) provides a cost-effective mechanism for quickly obtaining real-world feedback on project interim results, as well as at a scientific level. Moreover, it facilitates industry’s direct participation in identifying and pursuing exploitation opportunities. They are comprised of experts in the areas of programming models/runtime systems, performance tools, and performance optimization.


The SIAB has been identified by the General Assembly (GA) in order to meet the following objectives:

  • Evaluate the scientific quality and practical application of the work.
  • Provide expert opinion relating to the development of EPEEC programs and tools.
  • Assist in the dissemination of the project's results


Scientific-Industrial Advisory Board Members:

Frederic Pariente
HPC Relations Manager
Michael Klemm
Principal Engineer - Intel Deutschland GmbH
Chief Executive Officer - OpenMP ARB
Pavan Balaji
Computer Scientist and Group Lead
Argonne National Laboratory
Sunita Chandrasekaran
Assistant Professor - University of Delaware
Director - OpenACC User Adoption
Stefano Markidis
Associate Professor
KTH Royal Institute of Technology
The technical contributions of this project are impressive thus far. As the CEO of the OpenMP Architecture Review Board, I’m keen to hear more about the great results and start a conversation about potential benefits for the OpenMP API Specification.” 
Michael Klemm, Principal Engineer Intel Deutschland GmbH and CEO OpenMP ARB. 
“Overall, great job.  This project is coming along really well.” 
Pavan Balaji, Computer Scientist and Group Lead Argonne National Laboratory
"Productivity at Exascale without compromising on performance is a topic of paramount importance. It is fantastic to see EPEEC is getting to the bottom of it while interacting with users and stakeholders." 
Sunita Chandrasekaran, Assistant Professor University of Delaware and Director OpenACC User Adoption
“I am impressed by the current results of the project. In particular, the work on just-in-time compilation for heterogeneous systems, tasks on GPU, and data placement on heterogenous memories are timely and compelling research topics. This work could considerably impact HPC research in the next few years.”
Stefano Markidis, Associate Professor KTH Royal Institute of Technology
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