101 citations · 105 across the 8 of their papers we have counts for
8 papers
Attention-Based Deep Reinforcement Learning for Qubit Allocation in Modular Quantum Architectures
Enrico Russo, Maurizio Palesi, Davide Patti +2
Modular, distributed and multi-core architectures are currently considered a promising approach for scalability of quantum computing systems. The integration of multiple Quantum Pr…
Assessing the Role of Communication in Scalable Multi-Core Quantum Architectures
Maurizio Palesi, Enrico Russo, Davide Patti +2
Multi-core quantum architectures offer a solution to the scalability limitations of traditional monolithic designs. However, dividing the system into multiple chips introduces a cr…
Deep Reinforcement Learning based Online Scheduling Policy for Deep Neural Network Multi-Tenant Multi-Accelerator Systems
Francesco G. Blanco, Enrico Russo, Maurizio Palesi +3
Currently, there is a growing trend of outsourcing the execution of DNNs to cloud services. For service providers, managing multi-tenancy and ensuring high-quality service delivery…
Towards Fair and Firm Real-Time Scheduling in DNN Multi-Tenant Multi-Accelerator Systems via Reinforcement Learning
Enrico Russo, Francesco Giulio Blanco, Maurizio Palesi +3
This paper addresses the critical challenge of managing Quality of Service (QoS) in cloud services, focusing on the nuances of individual tenant expectations and varying Service Le…
A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures
Serena Curzel, Fabrizio Ferrandi, Leandro Fiorin +15
Given their increasing size and complexity, the need for efficient execution of deep neural networks has become increasingly pressing in the design of heterogeneous High-Performanc…
A Survey on Deep Learning Hardware Accelerators for Heterogeneous HPC Platforms
Cristina Silvano, Daniele Ielmini, Fabrizio Ferrandi +19
Recent trends in deep learning (DL) have made hardware accelerators essential for various high-performance computing (HPC) applications, including image classification, computer vi…
Scalable multi-chip quantum architectures enabled by cryogenic hybrid wireless/quantum-coherent network-in-package
Eduard Alarcón, Sergi Abadal, Fabio Sebastiano +9
The grand challenge of scaling up quantum computers requires a full-stack architectural standpoint. In this position paper, we will present the vision of a new generation of scalab…
Multi-Objective Hardware-Mapping Co-Optimisation for Multi-DNN Workloads on Chiplet-based Accelerators
Abhijit Das, Enrico Russo, Maurizio Palesi
The need to efficiently execute different Deep Neural Networks (DNNs) on the same computing platform, coupled with the requirement for easy scalability, makes Multi-Chip Module (MC…