This paper presents the DECICE project (Device Edge Cloud Intelligent Collaboration framEwork), a Horizon Europe Research and Innovation Action (Grant No. 101092582, December 2022 to November 2025) that developed an open-source framework for intelligent workload scheduling across the cloud-HPC-edge compute continuum. A consortium of 12 partners across 6 European countries organized the work into six work packages covering AI-driven scheduling, digital twin infrastructure, system architecture and integration, monitoring, use case validation, and dissemination. The two core technical contributions are an Integrated AI Scheduler (IAIS) employing RNN-based prediction and formal workflow modeling for constraint-aware workload mapping, and a Digital Twin aggregating real-time metrics with carbon intensity and anomaly prediction for energy-aware scheduling. The framework operates within Kubernetes environments, supports unified workflow ingestion from multiple formats, and bridges cloud-native and HPC orchestration through a Slurm integration layer. We present the project vision, the overall architecture, contributions from each work package, quantitative evaluation results, and the open-source release.

翻译：本文介绍了DECICE项目（设备-边缘-云智能协作框架），这是一项欧盟地平线研究与创新行动（授权号101092582，2022年12月至2025年11月），该项目开发了一个开源框架，用于在云-HPC-边缘计算连续体中进行智能工作负载调度。由来自6个欧洲国家的12个合作伙伴组成的联盟将工作划分为六个工作包，涵盖AI驱动调度、数字孪生基础设施、系统架构与集成、监控、用例验证及成果传播。两项核心技术贡献分别是：集成AI调度器（IAIS），该调度器采用基于RNN的预测与形式化工作流建模来实现约束感知的工作负载映射；以及数字孪生技术，该技术聚合实时指标与碳排放强度及异常预测，以实现能量感知调度。该框架运行于Kubernetes环境中，支持从多种格式统一获取工作流，并通过Slurm集成层桥接云原生与HPC编排。本文展示了项目愿景、整体架构、各工作包的贡献、定量评估结果以及开源发布。