Cloud-Edge Continuum Infrastructure for Reconfigurable Multi-Accelerator Systems
Iñigo Díez De Ulzurrun, Juan Encinas, Alfonso Rodríguez, A. Otero · 2024
In the cloud-edge continuum, distributed computing resources must be viewed as a whole from the user’s perspective. This requires transparently virtualizing the underlying hardware to allow moving and scaling user applications across different computing resources. This can be particularly challenging when using reconfigurable systems due to their need to directly access the hardware underneath. This paper presents an infrastructure to integrate these platforms in the cloud-edge continuum, allowing for the seamless deployment of user applications throughout its different layers. The infrastructure employs Kubernetes as a microservice based solution to manage user applications across the continuum, and the ARTICo3 framework, extended to PCIe-based platforms in this work, to accelerate parallel sections of the target applications in hardware. As a result, the proposed infrastructure can be used to accelerate any user application on any FPGA-based device in the continuum. This infrastructure could also potentially exploit multi-tenant computing, where computing resources are shared among users, maximizing resource utilization. The benefits of the proposed solution, including virtualization, portability, and scalability, have been validated through an actual cloud-edge continuum implementation running the MachSuite benchmarks, inducing a worst-case overhead of 1.23% when compared against independent single node scenarios.