4 citations · 7 across the 9 of their papers we have counts for
10 papers
Tunable and Portable Extreme-Scale Drug Discovery Platform at Exascale: the LIGATE Approach
Gianluca Palermo, Gianmarco Accordi, Davide Gadioli +32
Today digital revolution is having a dramatic impact on the pharmaceutical industry and the entire healthcare system. The implementation of machine learning, extreme-scale computer…
Improving computation efficiency using input and architecture features for a virtual screening application
Gianmarco Accordi, Emanuele Vitali, Davide Gadioli +6
Virtual screening is an early stage of the drug discovery process that selects the most promising candidates. In the urgent computing scenario it is critical to find a solution in…
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…
A Review on Parallel Virtual Screening Softwares for High Performance Computers
Natarajan Arul Murugan, Artur Podobas, Davide Gadioli +3
Drug discovery is the most expensive, time demanding and challenging project in biopharmaceutical companies which aims at the identification and optimization of lead compounds from…
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…
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…
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…
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…
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…
The ANTAREX Domain Specific Language for High Performance Computing
Cristina Silvano, Giovanni Agosta, Andrea Bartolini +19
The ANTAREX project relies on a Domain Specific Language (DSL) based on Aspect Oriented Programming (AOP) concepts to allow applications to enforce extra functional properties such…