Asynchronous Many-Task Systems and Applications Second International Workshop, WAMTA 2024, Knoxville, TN, USA, February 14–16, 2024, Proceedings

This book constitutes the refereed proceedings of the Second International Workshop on Asynchronous Many-Task Systems and Applications, WAMTA 2024, held in Knoxville, TN, USA during February 14–16, 2024.

The 11 full papers and 5 short papers included in this book were carefully reviewed and selected from 20 submissions. The WAMTA 2024 proceedings help developers, users, and proponents of these models and systems share experience, discuss how they meet the challenges posed by Exascale system architectures, and explore opportunities for increased performance, robustness, productivity, and full-system utilization.

.- Speaking Pygion: Experiences Writing an Exascale Single Particle Imaging Code.
.- Futures for dynamic dependencies – Parallelizing the H-LU Factorization.
.- Evaluating PaRSEC through Matrix Computations in Scientific Applications.
.- Distributed Asynchronous Contact Mechanics with DARMA/vt.
.- IRIS Reimagined: Advancements in Intelligent Runtime System for Task Based Programming.
.- MatRIS: Addressing the Challenges for Portability and Heterogeneity using Tasking for Matrix Decomposition (Cholesky).
.- ParSweet: A Suite of Codes for Benchmarking and Testing Mutex-Based Parallel Systems.
.- Rethinking Programming Paradigms in the QC-HPC Context.
.- Dynamic Tuning of Core Counts to Maximize Performance in Object-based Runtime Systems.
.- Enhancing sparse direct solver scalability through runtime system automatic data partition.
.- Experiences Porting Shared and Distributed Applications to Asynchronous Tasks: A Multidimensional FFT Case-study.
.- An abstraction for distributed stencil computations using Charm++.
.- DLA-Future: a task-based linear algebra library which provides a GPU enabled distributed eigensolver.
.- ALPI: Enhancing Portability and Interoperability of Task-Aware Libraries.
.- Evolving APGAS Programs: Automatic and Transparent Resource Adjustments at Runtime.
.- Optimizing Parallel System Efficiency: Dynamic Task Graph Adaptation with Recursive Tasks.
.- HPX with Spack and Singularity Containers: Evaluating Overheads for HPX/Kokkos using an astrophysics application.