4 citations · 4 across the 5 of their papers we have counts for
6 papers
GPU-Accelerated Hypergraph Partitioning and Placement to Map SNNs on Neuromorphic Hardware
Marco Ronzani, Cristina Silvano
SNNs running on neuromorphic hardware use spikes to achieve sparse and energy-efficient communication over a mesh of cores. In turn, system performance heavily depends on the assig…
SEADA: An efficient methodology for optimizing mixed-precision DNNs on multi-precision spatial architectures
Leandro Fiorin, Marco Ronzani, Cristina Silvano
Mixed-precision computation has been introduced in deep neural networks (DNNs) as an effective approach to reduce latency, energy consumption, and memory footprint. However, effici…
Hypergraph Partitioning on GPU with Distinct Incident Hyperedges and Size Constraints
Marco Ronzani, Cristina Silvano
Hypergraph partitioning is a recurring NP-hard problem in engineering; its efficient solution at scale hinges on parallelism. This work proposes a GPU-centric algorithm for multi-l…
Incidence Constraints in Hypergraph Partitioning on GPU
Marco Ronzani, Cristina Silvano
Hypergraph partitioning is a pervasive NP-hard problem, and accelerating its computation on GPU can both slice time-to-solution and raise quality of results. In this work, we imple…
A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware
Marco Ronzani, Cristina Silvano
Executing Spiking Neural Networks (SNNs) on neuromorphic hardware poses the problem of mapping neurons to cores. SNNs operate by propagating spikes between neurons that form a grap…
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…