Paper: Neuromorphic architectures on FPGAs survey accepted to ACM Computing Surveys!

PhD student Wiktor's survey "A Quarter of a Century of Neuromorphic Architectures on FPGAs -- an Overview" has been accepted for publication in ACM Computing Surveys (CSUR)! The article reviews 25 years of FPGA-based neuromorphic systems and discusses where the field is heading. Find the paper here!

Paper: Comparing Solar Structure Detection Methods in SDO/AIA Observations and the Application to Raw Uncalibrated Data

Together with colleagues in the ASAP project, we have a new journal article in the Journal of Geophysical Research: Machine Learning and Computation! The paper compares methods for detecting solar structures in images from the Solar Dynamics Observatory (SDO/AIA), and studies how well they work on raw, uncalibrated data -- a key step towards running such detection directly on board a spacecraft. Check the paper here!

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

Our paper on scalable neuromorphic design has been accepted to Euro-Par 2026! PhD candidate Ihsan shows how spiking neural network simulation can scale beyond a single device by connecting multiple FPGAs in a bidirectional ring topology, combined with a stream-dataflow architecture that keeps the neurons and synapses flowing through the hardware. Check the preprint here!

Paper: Embedded FPGA Acceleration of Brain-Like Neural Networks: Online Learning to Scalable Inference

A second paper from the group has been accepted to MCSoC! PhD candidate Ihsan shows how brain-like neural networks, such as BCPNN, can be accelerated on embedded FPGAs -- covering the full path from online learning to scalable inference on resource-constrained hardware. Check the paper here!

Paper: Evaluating Four FPGA-Accelerated Space Use Cases Based on Neural Network Algorithms for On-Board Inference

Our paper on evaluating space AI use-cases has been accepted to the IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip (MCSoC)! As part of the ASAP project, PhD student Pedro Antunes evaluates four neural-network-based space use cases accelerated on FPGAs, showing what on-board inference can look like on future space missions. Check the paper here!

Paper: IncineRate: Multi-Modal FPGA Accelerator Architecture for SCNNs

Spiking convolutional neural networks (SCNNs) combine the energy-efficiency of spiking neurons with the power of convolutional models, but running them fast is a challenge. In this paper, we present IncineRate, a multi-modal FPGA accelerator architecture that accelerates SCNN inference, showing how reconfigurable hardware can be tailored to the sparse, event-driven nature of spiking networks.

CGRA4HPCA 2026 at IPDPS 2026!

Our workshop on coarse-grained reconfigurable architectures (CGRAs) for AI and HPC ran for the fifth year at IPDPS 2026. Thank you to all speakers and attendees who made it a great event! Check out the official site here!

CGRA4HPCA 2025 at IPDPS next month!

Our workshop on coarse-grained reconfigurable architectures (CGRAs) for AI and HPC is running for the fourth year at IPDPS 2025. If you are going there, make sure to visit us! Check out the official site here!

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

Space -- the final frontier -- will use neural networks to analyze the increasing amount of data that high-fidelity sensors generate. In this awesome paper, PhD student Pedro Antunes survey what role FPGAs will have in our future space endeavours, discussing trends and opportunities! Check the preprint here!

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

What role do FPGAs have in brain simulation and neuromorphic engineering, and when can we simulate the whole brain on a single FPGA? PhD student Wiktor answers these and many more questions in this review article about neuromorphic systems on FPGAs! Check the preprint here!

Paper: A Reconfigurable Stream-Based FPGA Accelerator for Bayesian Confidence Propagation Neural Networks

PhD candidate Ihsan shows how FPGAs can be up to a magnitude faster than GPUs and more energy-efficient when running emerging brain-like neural network models, such as BCPNN. The paper was accepted by ARC 2025 in Seville, Spain! Check the preprint here!

Paper: Fast Algorithms for Spiking Neural Network Simulation with FPGAs

PhD candidate Björn's paper on how to reach fast and power-efficient SNN simulation on FPGAs, reaching faster-than-realtime simulation on a well-known cortical microcircuit model while consuming as little as 21 nJ of energy per synaptic event, making our accelerator the most energy efficient for this type of circuit in the world! Accepted to IEEE Access. Check the preprint here!

PhD student Muhammad Ihsan Al Hafiz joins the team. Welcome!

Ihsan will work in the EU EXTRA-BRAIN project examining the neuromorphic systems in cloud/edge continuum

Paper: Accelerating Scientific Application through Transparent I/O Interposition

Together with colleagues from Univ. of Edinburgh and RIKEN, we introduce iFast, a new library-level approach to transparently accelerating scientific applications based on MPI-IO. It decouples application I/O, data caching, and data storage to support heterogeneous storage models. Check the preprint here!

EXTRA-BRAIN EU Projects Starts!!

The EU Extra-Brain project will push state-of-the-art in applying brain-inspired (e.g., BCPNN) systems to solve applications in industry. Follow the project: here.

PhD student Pedro Antunes joins the team. Welcome!

Pedro will work in ASAP project examining the reconfigurable systems in space

PhD students Wiktor Sczerek. Welcome!

Wiktor will work on generating neuromorphic hardware using the Syn2Logic DSL.

Paper: Quantifying the effects of copious 3D-stacked cache on HPC workloads

Together with colleagues from RIKEN, Intel, IIT, Chalmers, TiTech, and AIST, we explore what it means for future (A64FX-like) processors to grow vertically. Check the full paper here!

ASAP EU Projects Starts!!

The ASAP project will investigate the use of reconfigurable architectures (FPGAs) for use in future deep-space missions.

PhD student Björn Lindqvist joins the team. Welcome!

Björn will work on accelerating neuroscience applications on FPGAs.