16 citations · 24 across the 22 of their papers we have counts for
6 papers · 1 filter
Reducing Instruction-Fetch Energy in RISC-V for Embedded AI Processing via Dynamic and Static Loop Caching
Wiebren Wijnstra, Sameed Sohail, Berend-Jan van der Zwaag +2
Embedded RISC-V processors are increasingly deployed for on-device AI inference at the edge, where energy efficiency is a primary design constraint. Instruction fetching from SRAM-…
The Sparsity Tax: Weight Sparsity Trade-offs in Event-Driven SIMD and SIMT Neuromorphic Cores
Mattias Westerink, Sameed Sohail, Berend-Jan van der Zwaag +2
Event-driven neuromorphic inference exploits activation sparsity by updating neuron state only on spikes. However, weight sparsity introduces irregular gather-style updates that un…
Shooting Neutrons at Neurons: Radiation Testing of a Spiking Neural Network on Flash-Based FPGAs
Wim Nijsink, Bruno Endres Forlin, Amirreza Yousefzadeh +1
Neuromorphic, or spiking, processors are increasingly being considered for use in harsh, radiation-prone environments such as space and avionics, where energy efficiency and gracef…
Memory Wall is not gone: A Critical Outlook on Memory Architecture in Digital Neuromorphic Computing
Amirreza Yousefzadeh, Sameed Sohail, Ana Lucia Varbanescu
The rapid advancement of neuromorphic technology aims to address the memory wall challenge inherent in conventional von Neumann architectures. This paper critically examines curren…
From RISC-V Cores to Neuromorphic Arrays: A Tutorial on Building Scalable Digital Neuromorphic Processors
Amirreza Yousefzadeh
Digital neuromorphic processors are emerging as a promising computing substrate for low-power, always-on EdgeAI applications. In this tutorial paper, we outline the main architectu…
Energy-efficient SNN Architecture using 3nm FinFET Multiport SRAM-based CIM with Online Learning
Lucas Huijbregts, Liu Hsiao-Hsuan, Paul Detterer +3
Current Artificial Intelligence (AI) computation systems face challenges, primarily from the memory-wall issue, limiting overall system-level performance, especially for Edge devic…