Jeremy Williams

My research is focused on evaluating and investigating the characteristics of leveraging key large-scale supercomputers and HPC systems to enable extreme-scale particle-in-cell monte carlo simulations in order to better understand and meet the demands of fusion energy research on current and future exascale supercomputing architectures, with an emphasis on optimizing and preparing prominent fusion energy codes for these next-generation systems.

Stefano Markidis is my principal supervisor, with Ivy Bo Peng and Erwin Laure as co-supervisors for this doctoral research.

In the EU-funded project called "Plasma-PEPSC (Plasma Exascale-Performance Simulations CoE)", coordinated by KTH, I serve as the WP7 Management Lead, Project Manager and Coordinator Contact (CoCo).  The EU project's primary goal is to maximize the parallel performance and efficiency of four European flagship plasma codes, each with unique individual grand challenges and a substantial user base : BIT, GENE, PIConGPU and Vlasiator. The EU project has a Plasma-PEPSC Community Page linked to the EU Open Research Repository, where project outputs are openly shared and accessible.

Further EU project information can be found here: https://plasma-pepsc.eu.

Additionally, I am a member of the Association for Computing Machinery (ACM) and attained fellowship status in ACM’s Special Interest Group on High-Performance Computing (SIGHPC) for my overall potential for excellence in data science and/or computational science, after a rigorous merit review.

Before coming to KTH, I completed a Master’s Degree in Modelling for Science and Engineering (MMSE) with a Data Science and Engineering Speciality at the Universitat Autònoma de Barcelona (UAB) in Cerdanyola del Vallès, Catalonia, Spain.

During MMSE, I completed a research stay at Department of Computer Architecture and Operating Systems (CAOS).

I am currently interested in:

- Performance Engineering

- High Performance Computing (HPC)

- High Performance Data Analytics (HPDA)

- Large-Scale Systems Monitoring and Resource Management