230 citations · 333 across the 7 of their papers we have counts for
8 papers
A Survey on Deep Learning Hardware Accelerators for Heterogeneous HPC Platforms
Cristina Silvano, Daniele Ielmini, Fabrizio Ferrandi +19
Recent trends in deep learning (DL) have made hardware accelerators essential for various high-performance computing (HPC) applications, including image classification, computer vi…
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…
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…