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G. Di Guglielmo

3 papers hereh-index 6265 citations10 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.CR1
  • cs.LG1
  • physics.ins-det1

identity via Semantic Scholar / OpenAlex

activity
20192022
most citedPAGURUS: Low-Overhead Dynamic Information Flow Tracking on Loosely Coupled Accelerators

21 citations · 29 across the 2 of their papers we have counts for

collaborators

3 papers

physics.ins-det2022★ 8 cited

Accelerating Deep Neural Networks for Real-time Data Selection for High-resolution Imaging Particle Detectors

Yeon-Jae Jwa, Giuseppe Di Guglielmo, Luca P. Carloni +1

This paper presents the custom implementation, optimization, and performance evaluation of convolutional neural networks on field programmable gate arrays, for the purposes of acce…

cs.LG2021

Fast convolutional neural networks on FPGAs with hls4ml

Thea Aarrestad, Vladimir Loncar, Nicolò Ghielmetti +17

We introduce an automated tool for deploying ultra low-latency, low-power deep neural networks with convolutional layers on FPGAs. By extending the hls4ml library, we demonstrate a…

cs.CR2019★ 21 cited

PAGURUS: Low-Overhead Dynamic Information Flow Tracking on Loosely Coupled Accelerators

Luca Piccolboni, Giuseppe Di Guglielmo, Luca P. Carloni

Software-based attacks exploit bugs or vulnerabilities to get unauthorized access or leak confidential information. Dynamic information flow tracking (DIFT) is a security technique…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.