Asynchronous Many-Task Systems and Applications

4th International Workshop, WAMTA 2026, Garching, Germany, February 16–18, 2026, Proceedings

AvPatrick Diehl,Markus Rampp

Häftad, Engelska, 2026

Del i serien Lecture Notes in Computer Science

838 kr

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Beskrivning

This book constitutes the refereed proceedings of the 4th International Workshop on Asynchronous Many-Task Systems and Applications, WAMTA 2026, held in Garching, Germany, during February 16–18, 2026.The 12 full papers and 2 Short papers included in this book were carefully reviewed and selected from 18 submissions. They focus on the advantages and challenges of task-based programming on modern and future HPC systems.

Produktinformation

Utgivningsdatum:2026-06-27
Mått:155 x 235 x undefined mm
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:170
Förlag:Springer Nature Switzerland AG
ISBN:9783032276759

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Innehållsförteckning

.- Exploring Performance-Productivity Trade-offs in AMT Runtimes: A Task Bench Study of Itoyori, ItoyoriFBC, HPX, and MPI..- From Promts to Performance: Evaluating LLMs for Task-based Parallel Code Generation..- GPU-Resident Gaussian Process Regression Leveraging Asynchronous Tasks with HPX..- Silent Data Corruption Protection through Efficient Task Replication..- Managing Explicit Communications Within a Sequential Task Flow Paradigm..- Hierarchical Scheduling for Composable Affinity-Aware Policies in Task-Based Runtimes..- First Experiments to Evaluate the Relevance of Task-based Runtime Systems to Implement Large Language Model Applications..- Abstract communicators for task based runtime systems..- Leveraging PaRSEC for Task-Based Heterogeneous Computing in Python and Julia..- Dynamic Resource Management with Charm++ using Dynamic Processes with PSets..- Finding Conservation Laws of Large Dynamical Systems with Tasks and Futures: A Case Study in Utilizing Dynamic Data Dependencies..- Merging Parameterized Task Graphs in PaRSEC Through JDF Composition with LLM Assistance..- Multiresolution Analysis using Data-Flow Programming..- Using C++ Generators in Dataflow Broadcast.

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