Davide Rossi

University of Bologna

Italy

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Articles (14)

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2021

Collaborators (8)

Andrea Bartolini

Assistant Professor

University of Bologna

ITALY

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LUCA BENINI

Professor

Eidgenössische Technische Hochschule Zürich

SWITZERLAND

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Sandro Pinto

University of Minho

PORTUGAL

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Francesco Conti

Assistant Professor

University of Bologna

ITALY

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Andrea ACQUAVIVA

University of Bologna

ITALY

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Giuseppe Tagliavini

University of Bologna

ITALY

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Simone Benatti

University of Bologna

ITALY

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Yvan Tortorella

University of Bologna

ITALY

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Davide Rossi

Research Interests

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Contact this professor

Articles (14)

Unleashing OpenTitan's Potential: a Silicon-Ready Embedded Secure Element for Root of Trust and Cryptographic Offloading

Marsellus: A Heterogeneous RISC-V AI-IoT End-Node SoC With 2–8 b DNN Acceleration and 30%-Boost Adaptive Body Biasing

Siracusa: A 16 nm Heterogenous RISC-V SoC for Extended Reality With At-MRAM Neural Engine

CVA6 RISC-V Virtualization: Architecture, Microarchitecture, and Design Space Exploration

Dustin: A 16-Cores Parallel Ultra-Low-Power Cluster With 2b-to-32b Fully Flexible Bit-Precision and Vector Lockstep Execution Mode

Dustin: A 16-Cores Parallel Ultra-Low-Power Cluster With 2b-to-32b Fully Flexible Bit-Precision and Vector Lockstep Execution Mode

Energy Efficiency of Opportunistic Refreshing for Gain-Cell Embedded DRAM

Scalable Hierarchical Instruction Cache for Ultralow-Power Processors Clusters

A Heterogeneous In-Memory Computing Cluster for Flexible End-to-End Inference of Real-World Deep Neural Networks

Vega: A Ten-Core SoC for IoT Endnodes With DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode

DARKSIDE: A Heterogeneous RISC-V Compute Cluster for Extreme-Edge On-Chip DNN Inference and Training

A Low-Power Transprecision Floating-Point Cluster for Efficient Near-Sensor Data Analytics

DORY: Automatic End-to-End Deployment of Real-World DNNs on Low-Cost IoT MCUs

A Fully Integrated 5-mW, 0.8-Gbps Energy-Efficient Chip-to-Chip Data Link for Ultralow-Power IoT End-Nodes in 65-nm CMOS

Collaborators (8)

Andrea Bartolini

LUCA BENINI

Sandro Pinto

Francesco Conti

Andrea ACQUAVIVA

Giuseppe Tagliavini

Simone Benatti

Yvan Tortorella

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