most citedOn-line Application Autotuning Exploiting Ensemble Models

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

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.DC20191 cited

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…

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…

cs.DC2019

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…