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cs.AR2026

Syn2Logic: End-to-End Neuromorphic Design Automation

Artur Podobas

In this work, we propose a view on electronic Neuromorphic Design Automation (eNDA), which we see as a design automation flow that bridges computational neuroscience modeling with…

cs.AR2026

FPGA-Based Neural Network Accelerators for Space Applications: A Survey

Pedro Antunes, Artur Podobas

Space missions are becoming increasingly ambitious, necessitating high-performance onboard spacecraft computing systems. In response, field-programmable gate arrays (FPGAs) have ga…

cs.AR2026

NeuroRing: Scaling Spiking Neural Networks via Multi-FPGA Bidirectional Ring Topologies and Stream-Dataflow Architectures

Muhammad Ihsan Al Hafiz, Artur Podobas

Spiking neural networks (SNNs) are a promising paradigm for energy-efficient event-driven computation, but large-scale SNN execution remains challenging because sparse spike commun…

cs.AR2026

A Quarter of a Century of Neuromorphic Architectures on FPGAs -- an Overview

Wiktor J. Szczerek, Artur Podobas

Neuromorphic computing is a relatively new discipline of computer science, where the principles of biological brain's computation and memory are used to create a new way of process…

cs.AR2026

bitSMM: A bit-Serial Matrix Multiplication Accelerator

Pedro Antunes, Artur Podobas

Neural-network (NN) inference is increasingly present on-board spacecraft to reduce downlink bandwidth and enable timely decision making. However, the power and reliability constra…

cs.AR20261 cited

Evaluating Four FPGA-accelerated Space Use Cases based on Neural Network Algorithms for On-board Inference

Pedro Antunes, Muhammad Ihsan Al Hafiz, Jonah Ekelund +4

Space missions increasingly deploy high-fidelity sensors that produce data volumes exceeding onboard buffering and downlink capacity. This work evaluates FPGA acceleration of neura…