Moreno Marzolla

DC
4papers
71citations
Novelty16%
AI Score15

4 Papers

LGJul 26, 2021
Dissecting FLOPs along input dimensions for GreenAI cost estimations

Andrea Asperti, Davide Evangelista, Moreno Marzolla

The term GreenAI refers to a novel approach to Deep Learning, that is more aware of the ecological impact and the computational efficiency of its methods. The promoters of GreenAI suggested the use of Floating Point Operations (FLOPs) as a measure of the computational cost of Neural Networks; however, that measure does not correlate well with the energy consumption of hardware equipped with massively parallel processing units like GPUs or TPUs. In this article, we propose a simple refinement of the formula used to compute floating point operations for convolutional layers, called α-FLOPs, explaining and correcting the traditional discrepancy with respect to different layers, and closer to reality. The notion of α-FLOPs relies on the crucial insight that, in case of inputs with multiple dimensions, there is no reason to believe that the speedup offered by parallelism will be uniform along all different axes.

DCAug 7, 2018
Anonymity and Confidentiality in Secure Distributed Simulation

Antonio Magnani, Gabriele D'Angelo, Stefano Ferretti et al.

Research on data confidentiality, integrity and availability is gaining momentum in the ICT community, due to the intrinsically insecure nature of the Internet. While many distributed systems and services are now based on secure communication protocols to avoid eavesdropping and protect confidentiality, the techniques usually employed in distributed simulations do not consider these issues at all. This is probably due to the fact that many real-world simulators rely on monolithic, offline approaches and therefore the issues above do not apply. However, the complexity of the systems to be simulated, and the rise of distributed and cloud based simulation, now impose the adoption of secure simulation architectures. This paper presents a solution to ensure both anonymity and confidentiality in distributed simulations. A performance evaluation based on an anonymized distributed simulator is used for quantifying the performance penalty for being anonymous. The obtained results show that this is a viable solution.

DCJun 12, 2018
A Blockchain-based Flight Data Recorder for Cloud Accountability

Gabriele D'Angelo, Stefano Ferretti, Moreno Marzolla

Many companies rely on Cloud infrastructures for their computation, communication and data storage requirements. While Cloud services provide some benefits, e.g., replacing high upfront costs for an IT infrastructure with a pay-as-you-go model, they also introduce serious concerns that are notoriously difficult to address. In essence, Cloud customers are storing data and running computations on infrastructures that they can not control directly. Therefore, when problems arise -- violations of Service Level Agreements, data corruption, data leakage, security breaches -- both customers and Cloud providers face the challenge of agreeing on which party is to be held responsible. In this paper, we review the challenges and requirements for enforcing accountability in Cloud infrastructures, and argue that smart contracts and blockchain technologies might provide a key contribution towards accountable Clouds.

DCMay 10, 2015
Cloud for Gaming

Gabriele D'Angelo, Stefano Ferretti, Moreno Marzolla

Cloud for Gaming refers to the use of cloud computing technologies to build large-scale gaming infrastructures, with the goal of improving scalability and responsiveness, improve the user's experience and enable new business models.