Summary

HPC1 seeks to redefine the integration of cloud-native environments with traditional high-performance computing (HPC). This ambitious project addresses the critical challenge of harmonizing heterogeneous HPC capabilities with native cloud environments, focusing on intricate aspects such as access, deployment, and architecture. The multidimensional endeavor revolves around a set of overarching objectives aimed at establishing a robust framework for scalable and high-performance serverless computing, seamlessly incorporating diverse computing and storage resources.

Goals

The core objective is to seamlessly integrate cloud-native paradigms with traditional HPC environments, developing abstraction layers, interoperable interfaces, and specialized services. The goal is to create a scientific-oriented serverless computing framework that transcends the limitations of existing paradigms, paving the way for a unified and efficient computational ecosystem. Within this context, a key focus lies on the meticulous orchestration of task deployment and resource provisioning to ensure fault-tolerant operation. This involves optimizing resource provisioning through intelligent utilization of information, establishing error management protocols during execution, and exploring interfaces for task execution. Additionally, attention is given to energy-efficient execution strategies, autoscaling, and elastic provisioning to enhance overall system efficiency. Simultaneously, HPC1 aims to fortify the security aspects of serverless computing. This involves designing a robust identity management system, establishing mechanisms for a secure computing environment, and deploying backend services across varying management and security zones. The objective includes addressing challenges associated with user management, such as the handling of User IDs (UIDs) and Group IDs (GIDs) between cloud-native systems and unique IDs in HPC environments. Another key goal in HPC1 is the development of efficient and low overhead monitoring services. This involves the identification and implementation of monitoring services optimized for serverless computing environments. HPC1 investigates strategies for efficient monitoring of tasks, emphasizing fault tolerance, and delves into methodologies for minimizing monitoring overhead to enhance system performance. Complementing these efforts, HPC1 will also work on enhancing data management for improved performance. This involves selecting methods to optimize data management, defining efficient procedures for data stage-in and stage-out operations, and determining optimal approaches for meta-data handling. HPC1 also addresses the implementation of comprehensive system-wide accounting, ensuring secure and efficient access to heterogeneous data sources, and exploring methods for the transferability of analytics from prototype to production systems.