Euro Par 2022 Parallel Processing
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Euro-Par 2022: Parallel Processing
This book constitutes the proceedings of the 33rd International Conference on Parallel and Distributed Computing, Euro-Par 2022, held in GLasgow, UK, in August 2022. The 25 full papers presented in this volume were carefully reviewed and selected from 102 submissions. The conference Euro-Par 2022 covers all aspects of parallel and distributed computing, ranging from theory to practice, scaling from the smallest to the largest parallel and distributed systems, from fundamental computational problems and models to full-fledged applications, from architecture and interface design and implementation to tools, infrastructures and applications.
Euro-Par 2022: Parallel Processing Workshops
This book constitutes revised selected papers from the workshops held at the 28th International European Conference on Parallel and Distributed Computing, Euro-Par 2022, which took place in Glasgow, UK, in August 22–26, 2022 Out of a total of 35 submissions 24 papers have been accepted, 19 of these are included in this book. They stem from the following workshops: - Workshop on Algorithms, Models and Tools for Parallel Computing on Heterogeneous Platforms (HeteroPar)- Workshop on Asynchronous Many-Task systems for Exascale (AMTE) - Workshop on Domain Specific Languages for High-Performance Computing (DSL-HPC)- Workshop on Distributed and Heterogeneous Programming in C and C++ (DHPCC++)- Workshop on Resiliency in High Performance Computing in Clouds, Grids, and Clusters (Resilience) In addition, the proceedings also contains 6 extended abstracts from the PhD Symposium.
Euro-Par 2024: Parallel Processing
The three-volume set LNCS 14801, 14802, and 14803 constitutes the proceedings of the 30th European Conference on Parallel and Distributed Processing, Euro-Par 2024, which took place in Madrid, Spain, during August 26–30, 2024. The 88 full papers included in the proceedings were carefully reviewed and selected from 293 submissions. They were organized in topical sections as follows: Part I: Programming, compilers, and performance; scheduling, resource management, cloud, edge computing, and workflows; Part II: Architectures and accelerators; data analytics, AI and computational science; Part III: Theory and algorithms; multidisciplinary, domain-specific and applied parallel and distributed computing.