James D Trotter

K. H. Jæger, J. D. Trotter, X. Cai, H. Arevalo and A. Tveito

Evaluating computational efforts and physiological resolution of mathematical models of cardiac tissue

Scientific Reports

K. Pogorelov, J. D. Trotter and J. Langguth

Performance Prediction for Sparse Matrix Vector Multiplication using Structure-dependent Features

First Workshop on Tools for Data Locality, Power and Performance (TDLPP 2023)

X. Cai and J. D. Trotter

Enabling Cell-Based Simulations of Cardiac Electrophysiology with High-Performance Computing

SIAM Conference on Parallel Processing for Scientific Computing (PP24), Baltimore, Maryland, USA

J. D. Trotter, J. Langguth and X. Cai

Targeting performance and user-friendliness: GPU-accelerated finite element computation with automated code generation in FEniCS

Parallel Computing

Å. Telle, J. D. Trotter, X. Cai, H. Finsberg, M. Kuchta, J. Sundnes and S. Wall

A cell-based framework for modeling cardiac mechanics

Biomechanics and Modeling in Mechanobiology

S. Breiter, J. D. Trotter and K. Fürlinger

Modelling Data Locality of Sparse Matrix-Vector Multiplication on the A64FX

SC-W '23: Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis

J. D. Trotter, S. Ekmekçibaşı, J. Langguth, T. Torun, E. Düzakın, A. Ilic and D. Unat

Bringing Order to Sparsity: A Sparse Matrix Reordering Study on Multicore CPUs

SC '23: International Conference for High Performance Computing, Networking, Storage and Analysis

J. D. Trotter, X. Cai and S. W. Funke

On memory traffic and optimisations for low-order finite element assembly algorithms on multi-core CPUs

ACM Transactions on Mathematical Software

Å. Telle, J. D. Trotter, X. Cai, M. Kuchta, H. Finsberg, J. Sundnes and S. Wall

Modeling cardiac mechanics using a cell-based framework

15th World Congress on Computational Mechanics (WCCM-XV), Yokohama, Japan

J. D. Trotter

High-performance finite element computations: Performance modelling, optimisation, GPU acceleration & automated code generation

University of Oslo

J. D. Trotter, J. Langguth and X. Cai

Automated Code Generation for GPU-Based Finite Element Computations in FEniCS

J. D. Trotter, J. Langguth and X. Cai

Cache simulation for irregular memory traffic on multi-core CPUs: Case study on performance models for sparse matrix–vector multiplication

Journal of Parallel and Distributed Computing

J. D. Trotter, X. Cai, S. W. Funke and J. Langguth

Compiling finite element variational forms for GPU-based assembly

FEniCS‘19, Washington DC, USA

J. D. Trotter

Quantifying data traffic of sparse matrix-vector multiplication in a multi-level memory hierarchy