230 citations · 266 across the 16 of their papers we have counts for
18 papers
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…
Fault Awareness in the MPI 4.0 Session Model
Roberto Rocco, Gianluca Palermo, Daniele Gregori
The latest version of MPI introduces new functionalities like the Session model, but it still lacks fault management mechanisms. Past efforts produced tools and MPI standard extens…
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…
Fault-Aware Non-Collective Communication Creation and Reparation in MPI
Roberto Rocco, Gianluca Palermo
The increasing size of HPC architectures makes the faults' presence a more and more frequent eventuality. This issue becomes especially relevant since MPI, the de-facto standard fo…
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…
Quantum Molecular Unfolding
Kevin Mato, Riccardo Mengoni, Daniele Ottaviani +1
Molecular Docking (MD) is an important step of the drug discovery process which aims at calculating the preferred position and shape of one molecule to a second when they are bound…
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…
Legio: Fault Resiliency for Embarrassingly Parallel MPI Applications
Roberto Rocco, Davide Gadioli, Gianluca Palermo
Due to the increasing size of HPC machines, the fault presence is becoming an eventuality that applications must face. Natively, MPI provides no support for the execution past the…
EVEREST: A design environment for extreme-scale big data analytics on heterogeneous platforms
Christian Pilato, Stanislav Bohm, Fabien Brocheton +15
High-Performance Big Data Analytics (HPDA) applications are characterized by huge volumes of distributed and heterogeneous data that require efficient computation for knowledge ext…
A Collaborative Filtering Approach for the Automatic Tuning of Compiler Optimisations
Stefano Cereda, Gianluca Palermo, Paolo Cremonesi +1
Selecting the right compiler optimisations has a severe impact on programs' performance. Still, the available optimisations keep increasing, and their effect depends on the specifi…
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…
On-line Application Autotuning Exploiting Ensemble Models
Tomas Martinovic, Davide Gadioli, Gianluca Palermo +1
Application autotuning is a promising path investigated in literature to improve computation efficiency. In this context, the end-users define high-level requirements and an autono…
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…
A Survey on Compiler Autotuning using Machine Learning
Amir H. Ashouri, William Killian, John Cavazos +2
Since the mid-1990s, researchers have been trying to use machine-learning based approaches to solve a number of different compiler optimization problems. These techniques primarily…
Fast Dynamic Memory Integration in Co-Simulation Frameworks for Multiprocessor System on-Chip
O. Villa, P. Schaumont, I. Verbauwhede +2
In this paper is proposed a technique to integrate and simulate a dynamic memory in a multiprocessor framework based on C/C++/SystemC. Using host machine's memory management capabi…