research
∙
09/04/2023
Scalable Hierarchical Instruction Cache for Ultra-Low-Power Processors Clusters
High Performance and Energy Efficiency are critical requirements for Int...
share
research
∙
07/31/2023
PATRONoC: Parallel AXI Transport Reducing Overhead for Networks-on-Chip targeting Multi-Accelerator DNN Platforms at the Edge
Emerging deep neural network (DNN) applications require high-performance...
research
∙
07/03/2023
A 3 TOPS/W RISC-V Parallel Cluster for Inference of Fine-Grain Mixed-Precision Quantized Neural Networks
The emerging trend of deploying complex algorithms, such as Deep Neural ...
research
∙
06/15/2023
ControlPULP: A RISC-V On-Chip Parallel Power Controller for Many-Core HPC Processors with FPGA-Based Hardware-In-The-Loop Power and Thermal Emulation
High-Performance Computing (HPC) processors are nowadays integrated Cybe...
research
∙
05/15/2023
Marsellus: A Heterogeneous RISC-V AI-IoT End-Node SoC with 2-to-8b DNN Acceleration and 30
Emerging Artificial Intelligence-enabled Internet-of-Things (AI-IoT) Sys...
research
∙
05/12/2023
Echoes: a 200 GOPS/W Frequency Domain SoC with FFT Processor and I2S DSP for Flexible Data Acquisition from Microphone Arrays
Emerging applications in the IoT domain require ultra-low-power and high...
research
∙
03/31/2023
DARKSIDE: A Heterogeneous RISC-V Compute Cluster for Extreme-Edge On-Chip DNN Inference and Training
On-chip DNN inference and training at the Extreme-Edge (TinyML) impose s...
research
∙
03/29/2023
Cyber Security aboard Micro Aerial Vehicles: An OpenTitan-based Visual Communication Use Case
Autonomous Micro Aerial Vehicles (MAVs), with a form factor of 10cm in d...
research
∙
02/06/2023
CVA6 RISC-V Virtualization: Architecture, Microarchitecture, and Design Space Exploration
Virtualization is a key technology used in a wide range of applications,...
research
∙
01/10/2023
RedMule: A Mixed-Precision Matrix-Matrix Operation Engine for Flexible and Energy-Efficient On-Chip Linear Algebra and TinyML Training Acceleration
The increasing interest in TinyML, i.e., near-sensor machine learning on...
research
∙
11/27/2022
HULK-V: a Heterogeneous Ultra-low-power Linux capable RISC-V SoC
IoT applications span a wide range in performance and memory footprint, ...
research
∙
11/23/2022
End-to-End DNN Inference on a Massively Parallel Analog In Memory Computing Architecture
The demand for computation resources and energy efficiency of Convolutio...
research
∙
08/18/2022
Kraken: A Direct Event/Frame-Based Multi-sensor Fusion SoC for Ultra-Efficient Visual Processing in Nano-UAVs
Small-size unmanned aerial vehicles (UAV) have the potential to dramatic...
research
∙
06/03/2022
Scale up your In-Memory Accelerator: Leveraging Wireless-on-Chip Communication for AIMC-based CNN Inference
Analog In-Memory Computing (AIMC) is emerging as a disruptive paradigm f...
research
∙
04/24/2022
RedMulE: A Compact FP16 Matrix-Multiplication Accelerator for Adaptive Deep Learning on RISC-V-Based Ultra-Low-Power SoCs
The fast proliferation of extreme-edge applications using Deep Learning ...
research
∙
03/29/2022
Geographic Diversity in Public Code Contributions
We conduct an exploratory, large-scale, longitudinal study of 50 years o...
research
∙
02/15/2022
Worldwide Gender Differences in Public Code Contributions
Gender imbalance is a well-known phenomenon observed throughout sciences...
research
∙
01/21/2022
Dustin: A 16-Cores Parallel Ultra-Low-Power Cluster with 2b-to-32b Fully Flexible Bit-Precision and Vector Lockstep Execution Mode
Computationally intensive algorithms such as Deep Neural Networks (DNNs)...
research
∙
01/04/2022
A Heterogeneous In-Memory Computing Cluster For Flexible End-to-End Inference of Real-World Deep Neural Networks
Deployment of modern TinyML tasks on small battery-constrained IoT devic...
research
∙
10/18/2021
Vega: A 10-Core SoC for IoT End-Nodes with DNN Acceleration and Cognitive Wake-Up From MRAM-Based State-Retentive Sleep Mode
The Internet-of-Things requires end-nodes with ultra-low-power always-on...
research
∙
09/05/2021
A Fully-Integrated 5mW, 0.8Gbps Energy-Efficient Chip-to-Chip Data Link for Ultra-Low-Power IoT End-Nodes in 65-nm CMOS
The increasing complexity of Internet-of-Things (IoT) applications and n...
research
∙
09/03/2021
End-to-end 100-TOPS/W Inference With Analog In-Memory Computing: Are We There Yet?
In-Memory Acceleration (IMA) promises major efficiency improvements in d...
research
∙
11/29/2020
XpulpNN: Enabling Energy Efficient and Flexible Inference of Quantized Neural Network on RISC-V based IoT End Nodes
This work introduces lightweight extensions to the RISC-V ISA to boost t...
research
∙
11/08/2020
Graphene-based Wireless Agile Interconnects for Massive Heterogeneous Multi-chip Processors
The main design principles in computer architecture have recently shifte...
research
∙
10/09/2020
An Energy-Efficient Low-Voltage Swing Transceiver for mW-Range IoT End-Nodes
As the Internet-of-Things (IoT) applications become more and more pervas...
research
∙
10/08/2020
A Mixed-Precision RISC-V Processor for Extreme-Edge DNN Inference
Low bit-width Quantized Neural Networks (QNNs) enable deployment of comp...
research
∙
08/27/2020
A transprecision floating-point cluster for efficient near-sensor data analytics
Recent applications in the domain of near-sensor computing require the a...
research
∙
08/17/2020
DORY: Automatic End-to-End Deployment of Real-World DNNs on Low-Cost IoT MCUs
The deployment of Deep Neural Networks (DNNs) on end-nodes at the extrem...
research
∙
07/27/2020
Performance-Aware Predictive-Model-Based On-Chip Body-Bias Regulation Strategy for an ULP Multi-Core Cluster in 28nm UTBB FD-SOI
The performance and reliability of Ultra-Low-Power (ULP) computing platf...
research
∙
07/17/2020
Always-On 674uW @ 4GOP/s Error Resilient Binary Neural Networks with Aggressive SRAM Voltage Scaling on a 22nm IoT End-Node
Binary Neural Networks (BNNs) have been shown to be robust to random bit...
research
∙
07/15/2020
Enabling Mixed-Precision Quantized Neural Networks in Extreme-Edge Devices
The deployment of Quantized Neural Networks (QNN) on advanced microcontr...
research
∙
07/15/2020
A 0.5GHz 0.35mW LDO-Powered Constant-Slope Phase Interpolator with 0.22% INL
Clock generators are an essential and critical building block of any com...
research
∙
06/25/2020
Arnold: an eFPGA-Augmented RISC-V SoC for Flexible and Low-Power IoT End-Nodes
A wide range of Internet of Things (IoT) applications require powerful, ...
research
∙
04/14/2020
Energy-Efficient Hardware-Accelerated Synchronization for Shared-L1-Memory Multiprocessor Clusters
The steeply growing performance demands for highly power- and energy-con...
research
∙
08/29/2019
PULP-NN: Accelerating Quantized Neural Networks on Parallel Ultra-Low-Power RISC-V Processors
We present PULP-NN, an optimized computing library for a parallel ultra-...
research
∙
03/05/2018
Hyperdrive: A Multi-Chip Systolically Scalable Binary-Weight CNN Inference Engine
Deep neural networks have achieved impressive results in computer vision...
research
∙
03/05/2018
Hyperdrive: A Systolically Scalable Binary-Weight CNN Inference Engine for mW IoT End-Nodes
Deep neural networks have achieved impressive results in computer vision...
research
∙
12/04/2017
NEURAghe: Exploiting CPU-FPGA Synergies for Efficient and Flexible CNN Inference Acceleration on Zynq SoCs
Deep convolutional neural networks (CNNs) obtain outstanding results in ...
research
∙
11/28/2017
A Transprecision Floating-Point Platform for Ultra-Low Power Computing
In modern low-power embedded platforms, floating-point (FP) operations e...
research
∙
04/29/2017
A sub-mW IoT-endnode for always-on visual monitoring and smart triggering
This work presents a fully-programmable Internet of Things (IoT) visual ...
research
∙
01/23/2017
Neurostream: Scalable and Energy Efficient Deep Learning with Smart Memory Cubes
High-performance computing systems are moving towards 2.5D and 3D memory...
research
∙
12/18/2016
An IoT Endpoint System-on-Chip for Secure and Energy-Efficient Near-Sensor Analytics
Near-sensor data analytics is a promising direction for IoT endpoints, a...
research
∙
08/30/2016
A near-threshold RISC-V core with DSP extensions for scalable IoT Endpoint Devices
Endpoint devices for Internet-of-Things not only need to work under extr...
research
∙
06/17/2016
