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T. Di Masciov

dblp:357/2576 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Embedded and real-time systems · 44% Memory systems · 44% Reconfigurable computing and FPGAs · 13%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Embedded and real-time systems › embedded hardware platform
heterogeneous system-on-chip
0.712023
Fine-Grained QoS Control via Tightly-Coupled Bandwidth Monitoring and Regulation for FPGA-based Heterogeneous SoCs · DAC 2023
Memory systems
memory bandwidth management
0.712023
Fine-Grained QoS Control via Tightly-Coupled Bandwidth Monitoring and Regulation for FPGA-based Heterogeneous SoCs · DAC 2023

Methods — techniques the papers use, named apart from their topics

throttling · 0.7bandwidth monitoring · 0.7
YearPublicationVenuePosition
2023 Fine-Grained QoS Control via Tightly-Coupled Bandwidth Monitoring and Regulation for FPGA-based Heterogeneous SoCs
abstract
Embedded systems are increasingly adopting heterogeneous templates integrating hardware accelerators and application-specific processors, which poses novel challenges. In particular, it is difficult to have accurate control of task activities in Commercial Off-the-shelf (COTS) System on Chips (SoCs), due to complex main memory sharing mechanisms among different computing engines. To address this problem, bandwidth regulation approaches based on monitoring and throttling are widely adopted. Existing solutions, however, are either too coarse-grained, limiting the control over computing engines activities, or platform-dependent, addressing the problem only for specific SoCs. In this paper we propose an innovative, fine-grained and platform-independent approach that can accurately control main memory bandwidth usage in an FPGA-based Heterogeneous System on Chip (HeSoC). Experimental results conducted on the Xilinx Zynq UltraScale+ platform demonstrate that our approach enables solutions not feasible with state-of-the-art bandwidth regulation methods.
Gianluca Brilli, Giacomo Valente, Alessandro Capotondi, Paolo Burgio, T. Di Masciov, Paolo Valente, Andrea Marongiu
DAC5