The three-volume set LNCS 15900-15902 constitutes the proceedings of the 31st European Conference on Parallel and Distributed Processing, Euro-Par 2025, which took place in Dresden, Germany, during August 25–29, 2025.The 78 papers included in these proceedings were carefully reviewed and selected from 264 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-sepcific and applied parallel and distributed computing.

The three-volume set LNCS 15900-15902 constitutes the proceedings of the 31st European Conference on Parallel and Distributed Processing, Euro-Par 2025, which took place in Dresden, Germany, during August 25–29, 2025.The 78 papers included in these proceedings were carefully reviewed and selected from 264 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-sepcific and applied parallel and distributed computing.

The three-volume set LNCS 15900-15902 constitutes the proceedings of the 31st European Conference on Parallel and Distributed Processing, Euro-Par 2025, which took place in Dresden, Germany, during August 25–29, 2025.The 78 papers included in these proceedings were carefully reviewed and selected from 264 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-sepcific and applied parallel and distributed computing.