The project inEXASCALE aims to change the way people think about designing and analyzing algorithms in the exascale era. On supercomputers that exist today, achieving even close to the peak performance is incredibly difficult if not impossible for many applications.

Techniques designed to improve performance - making computations less expensive by reorganizing an algorithm, making intentional approximations, and using lower precision - all introduce what we can generally call "inexactness". The question is, with all this inexactness involved, does the algorithm still get close enough to the right answer?

The effects of these sources of inexactness have been studied separately, but never together in a holistic way. By studying the combination of different sources of inexactness, we will reveal not only the limitations of these techniques, but also reveal new opportunities for developing algorithms that are both fast and provably accurate.

inEXASCALE

Analyzing and Exploiting Inexactness in Exascale Matrix Computations

PI: Erin Carson
Charles University
Prague, Czech Republic

Publications

Coming soon!

People

PI: Erin C. Carson

Open Positions

Two postdoctoral researcher positions are available at the Faculty of Mathematics and Physics at Charles University in Prague within the framework of the ERC STG project inEXASCALE.

Applications are invited from candidates who have strong background in one or more of the following:

  • numerical linear algebra
  • Krylov subspace methods
  • finite precision analysis
  • randomized numerical linear algebra
  • parallel algorithms and high-performance computing

The initial appointment period is 1 year, with possibility of an extension of 2 additional years.

The desired start date is March 1, 2023, although this is negotiable. By the start date the applicants must hold a PhD degree.

The application deadline is January 15, 2023; however, applications will be accepted until the position is filled.

To apply, candidates should submit the following documents to carson@karlin.mff.cuni.cz:

  • Curriculum Vitae
  • Cover Letter explaining motivation and interest
  • List of publications
  • Brief summary of PhD thesis (including pdf file of PhD thesis if available)

In addition, the candidate should arrange for two letters of recommendation to be sent directly to the same e-mail address before January 15, 2023.

Questions regarding the application can be directed to carson@karlin.mff.cuni.cz

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