Modelling hierarchical musical structures with composite probabilistic networks. - Michèle Weiland (2008)

Profile of scientific applications on HPC architectures using the DEISA Benchmark Suite. - Michèle Weiland (Comput. Sci. Res. Dev., 2010)

Mixed-mode implementation of PETSc for scalable linear algebra on multi-core processors - Michèle Weiland; Lawrence Mitchell; Gerard Gorman; Stephan Kramer; Mark Parsons 001; James Southern (CoRR, 2012)

Achieving Efficient Strong Scaling with PETSc Using Hybrid MPI/OpenMP Optimisation. - Michael Lange 001; Gerard Gorman; Michèle Weiland; Lawrence Mitchell; James Southern (ISC, 2013)

Benchmarking mixed-mode PETSc performance on high-performance architectures. - Michael Lange 001; Gerard Gorman; Michèle Weiland; Lawrence Mitchell; Xiaohu Guo; James Southern (CoRR, 2013)

Experiences Porting Production Codes to Xeon Phi Processors. - Emmanouil Farsarakis; Adrian Jackson; Fiona Reid; David Scott; Michèle Weiland (PARCO, 2015)

Symposium on Experiences of Porting and Optimising Code for Xeon Phi Processors. - Adrian Jackson; Michèle Weiland; Mark Parsons 001; Simon McIntosh-Smith (PARCO, 2015)

A directive based hybrid met office NERC cloud model. - Nick Brown 002; Angus Lepper; Michèle Weiland; Adrian Hill; Ben Shipway; Chris M. Maynard (WACCPD@SC, 2015)

Feasibility Study of Porting a Particle Transport Code to FPGA. - Iakovos Panourgias; Michèle Weiland; Mark Parsons 001; David Turland; Dave Barrett; Wayne P. Gaudin (ISC, 2015)

Benchmarking for power consumption monitoring. - Michèle Weiland; Nick Johnson (Comput. Sci. Res. Dev., 2015)

On the trade-offs between energy to solution and runtime for real-world CFD test-cases. - Michael R. Bareford; Nick Johnson; Michèle Weiland (EASC, 2016)

Progressive load balancing of asynchronous algorithms. - Justs Zarins; Michèle Weiland (IA3@SC, 2017)

In situ data analytics for highly scalable cloud modelling on Cray machines. - Nick Brown 002; Michèle Weiland; Adrian Hill; Ben Shipway (Concurr. Comput. Pract. Exp., 2018)

Architectures for High Performance Computing and Data Systems using Byte-Addressable Persistent Memory. - Adrian Jackson; Michèle Weiland; Mark Parsons 001; Bernhard Homölle (CoRR, 2018)

Exploiting the Performance Benefits of Storage Class Memory for HPC and HPDA Workflows. - Michèle Weiland; Adrian Jackson; Nick Johnson; Mark Parsons 001 (Supercomput. Front. Innov., 2018)

Progressive Load Balancing in Distributed Memory. - Justs Zarins; Michèle Weiland (PARCO, 2019)

Evaluating the Arm Ecosystem for High Performance Computing. - Adrian Jackson; Andrew Turner; Michèle Weiland; Nick Johnson; Olly Perks; Mark Parsons 001 (PASC, 2019)

An early evaluation of Intel's optane DC persistent memory module and its impact on high-performance scientific applications. - Michèle Weiland; Holger Brunst; Tiago Quintino; Nick Johnson; Olivier Iffrig; Simon D. Smart; Christian Herold; Antonino Bonanni; Adrian Jackson; Mark Parsons 001 (SC, 2019)

A Study on the Performance of Reproducible Computations. - Nico Bombace; Michèle Weiland (ISC Workshops, 2019)

An Architecture for High Performance Computing and Data Systems Using Byte-Addressable Persistent Memory. - Adrian Jackson; Michèle Weiland; Mark Parsons 001; Bernhard Homölle (ISC Workshops, 2019)

Leveraging MPI RMA to optimize halo-swapping communications in MONC on Cray machines. - Nick Brown 002; Michael R. Bareford; Michèle Weiland (Concurr. Comput. Pract. Exp., 2019)

Investigating Applications on the A64FX. - Adrian Jackson; Michèle Weiland; Nick Brown 002; Andrew Turner; Mark Parsons 001 (CLUSTER, 2020)

A highly scalable Met Office NERC Cloud model. - Nick Brown 002; Michèle Weiland; Adrian Hill; Ben Shipway; Chris M. Maynard; Thomas Allen; Mike Rezny (CoRR, 2020)

Leveraging MPI RMA to optimise halo-swapping communications in MONC on Cray machines. - Nick Brown 002; Michael R. Bareford; Michèle Weiland (CoRR, 2020)

Porting the microphysics model CASIM to GPU and KNL Cray machines. - Nick Brown 002; Alexandr Nigay; Michèle Weiland; Adrian Hill; Ben Shipway (CoRR, 2020)

Usage Scenarios for Byte-Addressable Persistent Memory inHigh-Performance and Data Intensive Computing. - Michèle Weiland; Bernhard Homölle (CoRR, 2020)

Performance Evaluation of Adaptive Routing on Dragonfly-based Production Systems. - Sudheer Chunduri; Kevin Harms; Taylor L. Groves; Peter Mendygral; Justs Zarins; Michèle Weiland; Yasaman Ghadar (IPDPS, 2021)

Usage Scenarios for Byte-Addressable Persistent Memory in High-Performance and Data Intensive Computing. - Michèle Weiland; Bernhard Homölle (J. Comput. Sci. Technol., 2021)

Exploiting dynamic sparse matrices for performance portable linear algebra operations. - Christodoulos Stylianou; Michèle Weiland (P3HPC@SC, 2022)

Detecting Scale-Induced Overflow Bugs in Production HPC Codes. - Justs Zarins; Michèle Weiland; Paul Bartholomew; Leigh Lapworth; Mark Parsons 001 (ISC Workshops, 2022)

EPCC's Exascale Journey: A Retrospective of the Past 10 Years and a Vision of the Future. - Michèle Weiland; Mark Parsons 001 (Comput. Sci. Eng., 2022)

An Approach to Performance Portability Through Generic Programming. - Andreas Hadjigeorgiou; Christodoulos Stylianou; Michèle Weiland; Dirk Jacob Verschuur; Jacob Finkenrath (Euro-Par Workshops (1), 2023)

Optimizing Sparse Linear Algebra Through Automatic Format Selection and Machine Learning. - Christodoulos Stylianou; Michèle Weiland (IPDPS Workshops, 2023)

AArch64 Atomics: Might They Be Harming Your Performance? - Ricardo Jesus; Michèle Weiland (PPoPP, 2023)

A Study on the Performance Implications of AArch64 Atomics. - Ricardo Jesus; Michèle Weiland (ISC, 2023)

Vectorizing and distributing number-theoretic transform to count Goldbach partitions on Arm-based supercomputers. - Ricardo Jesus; Tomás Oliveira e Silva; Michèle Weiland (Concurr. Comput. Pract. Exp., 2023)

Morpheus unleashed: Fast cross-platform SpMV on emerging architectures. - Christodoulos Stylianou; Mark Klaisoongnoen; Ricardo Jesus; Nick Brown 002; Michèle Weiland (CoRR, 2023)

Evaluating and optimising compiler code generation for NVIDIA Grace. - Ricardo Jesus; Michèle Weiland (ICPP, 2024)

Sustainable AI: Experiences, Challenges & Recommendations. - Eleanor Broadway; Joseph K. L. Lee; Michèle Weiland (SC Workshops, 2024)

Benchmarking Machine Learning Applications on Heterogeneous Architecture using Reframe. - Christopher Rae; Joseph K. L. Lee; James Richings; Michèle Weiland (CoRR, 2024)

Performance and scaling of the LFRic weather and climate model on different generations of HPE Cray EX supercomputers. - J. Mark Bull; Andrew Coughtrie; Deva Deeptimahanti; Mark Hedley; Caoimhín Laoide-Kemp; Christopher M. Maynard; Harry Shepherd; Sebastiaan van de Bund; Michèle Weiland; Benjamin Went (CoRR, 2024)

Morpheus: A library for efficient runtime switching of sparse matrix storage formats. - Christodoulos Stylianou; Michèle Weiland (SoftwareX, 2024)

ASiMoV-CCS - A New Solver for Scalable and Extensible CFD & Combustion Simulations. - Paul Bartholomew; Alexei Borissov; Christopher Goddard; Shrutee Lakshminarasimha; Sébastien Lemaire; Justs Zarins; Michèle Weiland (PASC, 2025)