Ayesha Afzal

Ayesha Afzal, M.Sc.

Short Bio

Ayesha Afzal is a researcher working towards the PhD degree at the professorship for High Performance Computing at Erlangen National High Performance Computing Center (NHR@FAU), Germany. She holds a Master’s degree in Computational Engineering from the Friedrich Alexander University, Erlangen-Nürnberg, Germany, followed by a Bachelor’s degree in Electrical Engineering from the University of Engineering and Technology, Lahore, Pakistan. Her PhD research lies at the crossroads of analytic performance models, performance tools and parallel simulation frameworks, with a focus on first-principles performance modelling of distributed-memory parallel programs in high-performance computing. She further conducts research in multi-core and parallel architectures, parallel computing and algorithms, parallel programming models, modern C++, and domain-specific languages.

Ayesha contributes to significant scientific community events as a vice chair (Posters@SC24, IEEE Computer Society Germany Chapter), a chair (Publicity@ICPP24, WHPC posters@ISC24, PERMAVOST@HPDC24+23, WHPC mentoring@SC23), a program committee member (SC, CLUSTER, ICPP, HPCCT, CSTA, P3HPC, Euro-Par WHPC session, IEEE TechEthics ad hoc), a journal reviewer (TPDS), a panelist (NHR23 conference), a communication liaison (SC25), a section lead (IEEEXtreme Region 8 Germany section) and an active speaker. She has authored numerous peer-reviewed publications, received the Best Short Paper Award 2023 in the PMBS workshop at the Supercomputing Conference, and scored First Place in the ISC PhD Forum Award 2021 which honors outstanding PhD work. She was named in the Top 100 Future Leaders Role Model List in 2022 and 2023 supported by Yahoo Finance and YouTube, respectively, and won WearetheCity’s Global Award for Achievement 2023.

Teaching

Supervised Theses

  • Master thesis, 2024 (ongoing): Performance Analysis of a Parallel Optical Flow Solver
  • Master thesis, 2024 (ongoing): Visualizing Global Structures in Distributed-Memory Parallel Programs
  • Master thesis, 2024: Extending a Simulation Framework for Performance Assessment of Parallel Applications
  • Bachelor thesis, 2021: Integration of chip-level performance models into a parallel simulation framework
  • Master thesis, 2019: Development of a benchmark suite for investigating MPI communication behavior

Open Thesis

  • Energy Modeling and Simulation of Parallel Applications on Clusters
  • Optimizing Parallel Programs using Persistent and Neighborhood Collectives

Publications

2023

2022

2021

2020

2019

2018

Posters

2023

  • Afzal A., Hager G., Wellein G.:
    Making Applications Run Faster by Slowing Down Processes?
    ISC High Performance 2023
    (Hamburg, Germany, 2023-05-21/2023-05-25)
    Download: Poster PDF

2022

2021

2019