Sort by
Refine Your Search
-
Listed
-
Field
-
) platform and its exploration in high-performance computing systems, such as HPC infrastructures. More specifically, we are looking for new scientific contributions that: 1) improve the platform's interface
-
applicability to new domains, including HPC systems, in order to identify different usage alternatives (e.g., user-space execution). It also intends to design and develop new features that extend and improve
-
developing an efficient storage solution for AI applications deployed at HPC centers. In detail, the work will focus on the development of a storage solution that optimizes the persistence of checkpoints of AI
-
development new functionalities associated with eBPF technology. Specifically, it aims to explore its applicability to new domains (e.g., observability in HPC systems) as well as the design and development
-
with Ansible, Docker, and Kubernetes technologies; - Practical Experience with cloud computing services (e.g., GCP) and high performance computing (HPC). 5. EVALUATION OF APPLICATIONS AND SELECTION