Gianluca Palermo | DeepAI

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Francesco Regazzoni
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Andrea Bartolini
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Jeronimo Castrillon
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Christian Pilato
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Davide Gadioli
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Emanuele Vitali
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Jakub Beránek
9 publications

∙ 04/19/2023

Tunable and Portable Extreme-Scale Drug Discovery Platform at Exascale: the LIGATE Approach

Today digital revolution is having a dramatic impact on the pharmaceutic...

0 Gianluca Palermo, et al. ∙

∙ 03/09/2023

Improving computation efficiency using input and architecture features for a virtual screening application

Virtual screening is an early stage of the drug discovery process that s...

0 Gianmarco Accordi, et al. ∙

∙ 03/06/2023

Fault Awareness in the MPI 4.0 Session Model

The latest version of MPI introduces new functionalities like the Sessio...

0 Roberto Rocco, et al. ∙

∙ 09/12/2022

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

COVID-19 has shown the importance of having a fast response against pand...

0 Emanuele Vitali, et al. ∙

∙ 09/05/2022

A Fault Resilient Approach to Non-collective Communication Creation in MPI

The increasing size of HPC architectures makes the faults' presence an e...

0 Roberto Rocco, et al. ∙

∙ 11/30/2021

A Review on Parallel Virtual Screening Softwares for High Performance Computers

Drug discovery is the most expensive, time demanding and challenging pro...

0 Natarajan Arul Murugan, et al. ∙

∙ 10/22/2021

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

The social and economic impact of the COVID-19 pandemic demands the redu...

0 Davide Gadioli, et al. ∙

∙ 05/27/2021

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

In this paper, we want to show the potential benefit of a dynamic auto-t...

0 Emanuele Vitali, et al. ∙

∙ 04/29/2021

Legio: Fault Resiliency for Embarrassingly Parallel MPI Applications

Due to the increasing size of HPC machines, the fault presence is becomi...

0 Roberto Rocco, et al. ∙

∙ 03/06/2021

EVEREST: A design environment for extreme-scale big data analytics on heterogeneous platforms

High-Performance Big Data Analytics (HPDA) applications are characterize...

0 Christian Pilato, et al. ∙

∙ 05/06/2020

A Collaborative Filtering Approach for the Automatic Tuning of Compiler Optimisations

Selecting the right compiler optimisations has a severe impact on progra...

0 Stefano Cereda, et al. ∙

∙ 05/06/2020

A Collaborative Filtering Approah for the Automatic Tuning of Compiler Optimisations

Selecting the right compiler optimisations has a severe impact on progra...

0 Stefano Cereda, et al. ∙

∙ 01/18/2019

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

The drug discovery process involves several tasks to be performed in viv...

0 Davide Gadioli, et al. ∙

∙ 01/18/2019

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

In drug discovery, molecular docking is the task in charge of estimating...

0 Emanuele Vitali, et al. ∙

∙ 01/18/2019

On-line Application Autotuning Exploiting Ensemble Models

Application autotuning is a promising path investigated in literature to...

0 Tomas Martinovic, et al. ∙

∙ 01/18/2019

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

Incorporating speed probability distribution to the computation of the r...

0 Emanuele Vitali, et al. ∙

∙ 01/18/2019

The ANTAREX Domain Specific Language for High Performance Computing

The ANTAREX project relies on a Domain Specific Language (DSL) based on ...

0 Cristina Silvano, et al. ∙

∙ 01/13/2018

A Survey on Compiler Autotuning using Machine Learning

Since the mid-1990s, researchers have been trying to use machine-learnin...

0 Amir H. Ashouri, et al. ∙

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