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Projecte llegit

Títol: Control and Orchestration of Hybrid Quantum Datacenter and HPC infrastructures

Estudiants que han llegit aquest projecte:

Director/a: SPADARO, SALVATORE

Departament: TSC

Títol: Control and Orchestration of Hybrid Quantum Datacenter and HPC infrastructures

Data inici oferta: 21-07-2025     Data finalització oferta: 21-03-2026


Estudis d'assignació del projecte:
    GR ENG SIS TELECOMUN
Tipus: Individual
 
Lloc de realització: EETAC
 
Segon director/a (UPC): PAGÈS CRUZ, ALBERT
 
Paraules clau:
Orchestration, Resource Allocation, OpenStack, High Performance Computing, Cloud Computing, , Hybrid Quantum Data Centre, Quantum Computing, Retrieval-Augmented Generation, Large Language Model.
 
Descripció del contingut i pla d'activitats:
Over the years, the usage of data center (DC) and High Performance Computing (HPC) infrastructures has increased, as more applications (e.g. Artificial Intelligence) and functionalities are moved to the cloud. Such applications have very intense requirements in storage space, CPU and GPU use and bandwidth (Petabit/s). Traditional DCs/HPCs, based on integrated servers, due to the fragmentation of the computational resources, fail to match these requirements. Thus, the disaggregated DCs (DDCs) paradigm has been proposed. Looking at future DC/HPC platforms, the integration of Quantum Computers (QC) is considered. HPC platforms have been identified as the site where QCs can be deployed. Although the development of the technology for QCs is still at an early-stage, the Quantum Processing Unit (QPU) are envisioned to be part of the (disaggregated) DC/HPC platforms, dedicated to solve problems that require the QPU processing capabilities. Therefore, it may be beneficial to have the coexistence between classical processing units and QCs.
 
Overview (resum en anglès):
Hybrid quantum datacentres are advancing rapidly, and yet most of the efforts are pointing to hardware development, while the software layer that orchestrates classical and quantum resources remains underdeveloped. This thesis designs and implements a state aware hybrid orchestrator that receives workload requests and places them into the designated cluster. The orchestrator is built as a set of REST services organised into NorthBound, allocation, resource and Southbound blocks. The classical cluster is deployed on an OpenStack environment using DevStack, while the quantum cluster is emulated by quantum agents. Two placement algorithms are implemented, First Fit and Load Balancing. Both operate over both clusters, they filter and select the corresponding node that suits the logic of the algorithm. Every allocation is persisted so the system recovers the status after a restart. A natural language entry layer was also implemented, combining retrieval augmentation generation with a large language model, converting the entry into a validated typed schema and routing to the appropriate tier, while a dashboard exposes the full pipeline and the live infrastructure state with role based visibility. The system was evaluated under identical 100 request campaigns using a mock backend that enables large scale testing without saturating the physical laboratory. Load Balancing increased the number of successful allocations by 19.15 per cent over First Fit, an advantage concentrated in the RAM constrained classical tier, and the natural language layer reached a routing accuracy of 96.8 per cent. The results confirm that a natural language interface can drive an orchestrator reliably. The main limitations are the emulated quantum cluster and a single classical laboratory deployment, future work includes integrating a real quantum backend, adding authentication to the dashboard, and introducing time aware resource release.

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