activity
20192022
most citedEXSCALATE: An extreme-scale in-silico virtual screening platform to evaluate 1 trillion compounds in 60 hours on 81 PFLOPS supercomputers

1 citations · 2 across the 6 of their papers we have counts for

collaborators

7 papers

cs.DC20221 cited

GPU-optimized Approaches to Molecular Docking-based Virtual Screening in Drug Discovery: A Comparative Analysis

Emanuele Vitali, Federico Ficarelli, Mauro Bisson +4

COVID-19 has shown the importance of having a fast response against pandemics. Finding a novel drug is a very long and complex procedure, and it is possible to accelerate the preli…

cs.DC20211 cited

EXSCALATE: An extreme-scale in-silico virtual screening platform to evaluate 1 trillion compounds in 60 hours on 81 PFLOPS supercomputers

Davide Gadioli, Emanuele Vitali, Federico Ficarelli +7

The social and economic impact of the COVID-19 pandemic demands the reduction of the time required to find a therapeutic cure. In the contest of urgent computing, we re-designed th…

cs.CV2021

Dynamic Network selection for the Object Detection task: why it matters and what we (didn't) achieve

Emanuele Vitali, Anton Lokhmotov, Gianluca Palermo

In this paper, we want to show the potential benefit of a dynamic auto-tuning approach for the inference process in the Deep Neural Network (DNN) context, tackling the object detec…

cs.DC2019

Tunable Approximations to Control Time-to-Solution in an HPC Molecular Docking Mini-App

Davide Gadioli, Gianluca Palermo, Stefano Cherubin +7

The drug discovery process involves several tasks to be performed in vivo, in vitro and in silico. Molecular docking is a task typically performed in silico. It aims at finding the…

cs.DC2019

Exploiting OpenMP & OpenACC to Accelerate a Molecular Docking Mini-App in Heterogeneous HPC Nodes

Emanuele Vitali, Davide Gadioli, Gianluca Palermo +3

In drug discovery, molecular docking is the task in charge of estimating the position of a molecule when interacting with the docking site. This task is usually used to perform scr…

cs.DC2019

An Efficient Monte Carlo-based Probabilistic Time-Dependent Routing Calculation Targeting a Server-Side Car Navigation System

Emanuele Vitali, Davide Gadioli, Gianluca Palermo +7

Incorporating speed probability distribution to the computation of the route planning in car navigation systems guarantees more accurate and precise responses. In this paper, we pr…