294 citations · 840 across the 40 of their papers we have counts for
34 papers · 1 filter
MEGATRON: a 28nm Analog PCM CiM/Digital System-on-Chip for Edge GenAI at 57.5 TOPS/W and 1.52 Mparam/mm
Alessandro Nadalini, Angelo Garofalo, Lorenzo Greco +12
We present MEGATRON, a heterogeneous Edge GenAI System-on-Chip in 28nm FD-SOI CMOS technology combining a non-volatile analog in-memory-computing engine based on a 4Mi-cell phase-c…
Scalable AXI4 Transaction Monitoring for Mixed-Criticality SoCs: From Phase-Level Precision to ID-Level Efficiency
Chaoqun Liang, Thomas Benz, Alessandro Ottaviano +4
Mixed-criticality Systems-on-Chip (SoCs) with on-chip interconnects based on the AXI4 open standard protocol lack a protocol-level timeout mechanism, exposing systems to deadlocks…
Assessing Triple Modular Redundancy for Wide-Link, Low-Latency NoC Routers: Reliability and Physical Design Challenges
Chen Wu, Michael Rogenmoser, Luca Benini +1
Protecting the Network-on-Chip (NoC) of physical-AI tile-based accelerators deployed in harsh environments against single-event effects (SEEs) is paramount for preventing NoC failu…
CVA6-RT: an Open-Source Time-Predictable RV64 Processor for Mixed-Criticality Systems
Enrico Zelioli, Christopher Reinwardt, Nils Wistoff +4
This work presents CVA6-RT, a real-time micro-architectural extension of the CVA6 core to bound worst-case latency and reduce task's timing execution variability. CVA6-RT implement…
Not All Faults Are Equal: Transient-Fault Sensitivity Characterization of an Open-Source RISC-V Vector Cluster
Maoyuan Cai, Amirhossein Kiamarzi, Davide Rossi +1
We present a transient-fault sensitivity study of the open-source RISC-V vector cluster Spatz under SET and SEU fault models. Across 100,000 fault injections on six MatMul and Wide…
Who Checks the Checker? Enhancing Component-level Architectural SEU Fault Tolerance for End-to-End SoC Protection
Michael Rogenmoser, Philippe Sauter, Chen Wu +2
Single-event upset (SEU) fault tolerance for systems-on-chip (SoCs) in radiation-heavy environments is often addressed by architectural fault-tolerance approaches protecting indivi…
VMXDOTP: A RISC-V Vector ISA Extension for Efficient Microscaling (MX) Format Acceleration
Max Wipfli, Gamze İslamoğlu, Navaneeth Kunhi Purayil +2
Compared to the first generation of deep neural networks, dominated by regular, compute-intensive kernels such as matrix multiplications (MatMuls) and convolutions, modern decoder-…
relOBI: A Reliable Low-latency Interconnect for Tightly-Coupled On-chip Communication
Michael Rogenmoser, Angelo Garofalo, Luca Benini
On-chip communication is a critical element of modern systems-on-chip (SoCs), allowing processor cores to interact with memory and peripherals. Interconnects require special care i…
FractalSync: Lightweight Scalable Global Synchronization of Massive Bulk Synchronous Parallel AI Accelerators
Victor Isachi, Alessandro Nadalini, Riccardo Fiorani Gallotta +3
The slow-down of technology scaling and the emergence of Artificial Intelligence (AI) workloads have led computer architects to increasingly exploit parallelization coupled with ha…
MXDOTP: A RISC-V ISA Extension for Enabling Microscaling (MX) Floating-Point Dot Products
Gamze İslamoğlu, Luca Bertaccini, Arpan Suravi Prasad +3
Fast and energy-efficient low-bitwidth floating-point (FP) arithmetic is essential for Artificial Intelligence (AI) systems. Microscaling (MX) standardized formats have recently em…
RedMulE-FT: A Reconfigurable Fault-Tolerant Matrix Multiplication Engine
Philip Wiese, Maurus Item, Luca Bertaccini +3
As safety-critical applications increasingly rely on data-parallel floating-point computations, there is an increasing need for flexible and configurable fault tolerance in paralle…
VEXP: A Low-Cost RISC-V ISA Extension for Accelerated Softmax Computation in Transformers
Run Wang, Gamze Islamoglu, Andrea Belano +4
While Transformers are dominated by Floating-Point (FP) Matrix-Multiplications, their aggressive acceleration through dedicated hardware or many-core programmable systems has shift…
Quadrilatero: A RISC-V programmable matrix coprocessor for low-power edge applications
Danilo Cammarata, Matteo Perotti, Marco Bertuletti +4
The rapid growth of AI-based Internet-of-Things applications increased the demand for high-performance edge processing engines on a low-power budget and tight area constraints. As…
CVA6-VMRT: A Modular Approach Towards Time-Predictable Virtual Memory in a 64-bit Application Class RISC-V Processor
Christopher Reinwardt, Robert Balas, Alessandro Ottaviano +2
The increasing complexity of autonomous systems has driven a shift to integrated heterogeneous SoCs with real-time and safety demands. Ensuring deterministic WCETs and low-latency…
A Reliable, Time-Predictable Heterogeneous SoC for AI-Enhanced Mixed-Criticality Edge Applications
Angelo Garofalo, Alessandro Ottaviano, Matteo Perotti +20
Next-generation mixed-criticality Systems-on-chip (SoCs) for robotics, automotive, and space must execute mixed-criticality AI-enhanced sensor processing and control workloads, ens…
Towards Reliable Systems: A Scalable Approach to AXI4 Transaction Monitoring
Chaoqun Liang, Thomas Benz, Alessandro Ottaviano +3
In safety-critical SoC applications such as automotive and aerospace, reliable transaction monitoring is crucial for maintaining system integrity. This paper introduces a drop-in T…
AXI-REALM: Safe, Modular and Lightweight Traffic Monitoring and Regulation for Heterogeneous Mixed-Criticality Systems
Thomas Benz, Alessandro Ottaviano, Chaoqun Liang +6
The automotive industry is transitioning from federated, homogeneous, interconnected devices to integrated, heterogeneous, mixed-criticality systems (MCS). This leads to challenges…
Open-Source Heterogeneous SoCs for AI: The PULP Platform Experience
Francesco Conti, Angelo Garofalo, Davide Rossi +2
Since 2013, the PULP (Parallel Ultra-Low Power) Platform project has been one of the most active and successful initiatives in designing research IPs and releasing them as open-sou…
A Flexible Template for Edge Generative AI with High-Accuracy Accelerated Softmax & GELU
Andrea Belano, Yvan Tortorella, Angelo Garofalo +3
Transformer-based generative Artificial Intelligence (GenAI) models achieve remarkable results in a wide range of fields, including natural language processing, computer vision, an…
vCLIC: Towards Fast Interrupt Handling in Virtualized RISC-V Mixed-criticality Systems
Enrico Zelioli, Alessandro Ottaviano, Robert Balas +3
The widespread diffusion of compute-intensive edge-AI workloads and the stringent demands of modern autonomous systems require advanced heterogeneous embedded architectures. Such a…
A Gigabit, DMA-enhanced Open-Source Ethernet Controller for Mixed-Criticality Systems
Chaoqun Liang, Alessandro Ottaviano, Thomas Benz +4
The ongoing revolution in application domains targeting autonomous navigation, first and foremost automotive "zonalization", has increased the importance of certain off-chip commun…
SentryCore: A RISC-V Co-Processor System for Safe, Real-Time Control Applications
Michael Rogenmoser, Alessandro Ottaviano, Thomas Benz +4
In the last decade, we have witnessed exponential growth in the complexity of control systems for safety-critical applications (automotive, robots, industrial automation) and their…
AXI-REALM: A Lightweight and Modular Interconnect Extension for Traffic Regulation and Monitoring of Heterogeneous Real-Time SoCs
Thomas Benz, Alessandro Ottaviano, Robert Balas +4
The increasing demand for heterogeneous functionality in the automotive industry and the evolution of chip manufacturing processes have led to the transition from federated to inte…
ITA: An Energy-Efficient Attention and Softmax Accelerator for Quantized Transformers
Gamze İslamoğlu, Moritz Scherer, Gianna Paulin +4
Transformer networks have emerged as the state-of-the-art approach for natural language processing tasks and are gaining popularity in other domains such as computer vision and aud…