Publications related to Fully-Asynchronous Fully-Implicit Variable-Order Variable-Timestep Simulation of Neural Networks

Related publications (35)

Highly Parallel RTL Simulation

Verification and testing of hardware heavily relies on cycle-accurate simulation of RTL. As single-processor performance is growing only slowly, conventional, single-threaded RTL simulation is becoming impractical for increasingly complex chip designs and ...

EPFL2024

Machine-Learning-Enhanced Real-Time Aerodynamic Forces Prediction Based on Sparse Pressure Sensor Inputs

Jan Sickmann Hesthaven, Junming Duan

Accurate real-time prediction of aerodynamic forces is crucial for the navigation of unmanned aerial vehicles (UAVs). This paper presents a data-driven aerodynamic force prediction model based on a small number of pressure sensors located on the surface of ...

2024

Swift : a modern highly parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Yves Revaz, Yannick Michael Bahé, Loïc Hausammann, Mladen Ivkovic

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and ...

2024

Manticore: Hardware-Accelerated RTL Simulation with Static Bulk-Synchronous Parallelism

James Richard Larus, Sahand Kashani, Seyedmahyar Emami

The demise of Moore's Law and Dennard Scaling has revived interest in specialized computer architectures and accelerators. Verification and testing of this hardware depend heavily upon cycle-accurate simulation of register-transfer-level (RTL) designs. The ...

Assoc Computing Machinery2023

Dynamic SIMD Parallel Execution on GPU from High-Level Dataflow Synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Developing and fine-tuning software programs for heterogeneous hardware such as CPU/GPU processing platforms comprise a highly complex endeavor that demands considerable time and effort of software engineers and requires evaluating various fundamental comp ...

MDPI2022

Methods for acute and long-term imaging of the ventral nerve cord in behaving adult Drosophila

Laura Joan Hermans

Understanding how neural circuits remodel and adapt to animal behavior is a central theme in the field of Neuroscience. One strategy to reach this goal is to repeatedly record the same animal's neural circuits and observe how they adapt when facing differe ...

EPFL2022

Building Chips Faster: Hardware-Compiler Co-Design for Accelerated RTL Simulation

Sahand Kashani

The demise of Moore's Law and Dennard scaling has resulted in diminishing performance gains for general-purpose processors, and so has prompted a surge in academic and commercial interest for hardware accelerators. Specialized hardware has already redefine ...

EPFL2023

GEAR-RT: Towards Exa-Scale Moment Based Radiative Transfer For Cosmological Simulations Using Task-Based Parallelism And Dynamic Sub-Cycling with SWIFT

Mladen Ivkovic

Numerical simulations have become an indispensable tool in astrophysics and cosmology. The constant need for higher accuracy, higher resolutions, and models of ever-increasing sophistication and complexity drives the development of modern tools which targe ...

EPFL2023

On the Spatial Distribution of Temporal Complexity in Resting State and Task Functional MRI

Dimitri Nestor Alice Van De Ville, Maria Giulia Preti, Enrico Amico, Raphaël Pierre Liégeois, Amir Hossein Omidvarnia

Measuring the temporal complexity of functional MRI (fMRI) time series is one approach to assess how brain activity changes over time. In fact, hemodynamic response of the brain is known to exhibit critical behaviour at the edge between order and disorder. ...

MDPI2022

Inter-actions parallel execution on GPU from high-level dataflow synthesis

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

Recent GPU architectures make available numbers of parallel processing units that exceed by orders of magnitude the ones offered by CPU architectures. Whereas programs written using dataflow programming languages are well suited for programming heterogeneo ...

IEEE2022

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

Auke Ijspeert, Andrea Di Russo, Dimitar Yuriev Stanev

Objective. Studying the neural components regulating movement in human locomotion is obstructed by the inability to perform invasive experimental recording in the human neural circuits. Neuromechanical simulations can provide insights by modeling the locom ...

Iop Publishing Ltd2023

Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation

Weina Ji, Henry Markram, Felix Schürmann, Daniel Keller, Eilif Benjamin Muller, Michael Reimann, Werner Alfons Hilda Van Geit, Srikanth Ramaswamy, Matthias Wolf, James Gonzalo King, Alexis Arnaudon, András Ecker, Rajnish Ranjan, Jean-Denis Georges Emile Courcol, Armando Romani, Pramod Shivaji Kumbhar, Judit Planas Carbonell, Giuseppe Chindemi, Michael Emiel Gevaert, Christian Andreas Rössert, Fernando Joaquim Leite Pereira, Omar Awile, Mustafa Anil Tuncel, Daniela Egas Santander, James Bryden Isbister, Natali Barros Zulaica, Samuel Lieven D. Lapere, Sirio Bolaños Puchet, Maria Reva, Genrich Ivaska, Tanguy Pierre Louis Damart, Darshan Mandge, Joni Henrikki Herttuainen, Christoph Pokorny, Elvis Boci, Vishal Sood, Thomas Brice Delemontex, Aleksandra Zuzanna Teska, Polina Litvak, Alexander Dietz, Jorge Blanco Alonso, Gianluca Ficarelli

Cortical dynamics underlie many cognitive processes and emerge from complex multi-scale interactions, which are challenging to study in vivo. Large-scale, biophysically detailed models offer a tool which can complement laboratory approaches. We present a m ...

2024

Cortical Surfaces Integration with Tractography for Structural Connectivity Analysis

Gabriel Girard, Maxime Descoteaux

Background: Mapping diffusion MRI tractography streamlines to the cortical surface facilitates the integration of white matter features onto gray matter, especially for connectivity analysis. ...

MARY ANN LIEBERT, INC2021

Exploring MEG brain fingerprints: Evaluation, pitfalls, and interpretations

Sélima Zahar, Dimitri Nestor Alice Van De Ville, Alessandra Griffa, Enrico Amico, Ekansh Sareen

Individual characterization of subjects based on their functional connectome (FC), termed “FC fingerprinting”, has become a highly sought-after goal in contemporary neuroscience research. Recent functional magnetic resonance imaging (fMRI) studies have dem ...

2021

Compilation and Design Space Exploration of Dataflow Programs for Heterogeneous CPU-GPU Platforms

Aurélien François Gilbert Bloch

Today's continued increase in demand for processing power, despite the slowdown of Moore's law, has led to an increase in processor count, which has resulted in energy consumption and distribution problems. To address this, there is a growing trend toward ...

EPFL2023

Computational approaches to decode grasping force and velocity level in upper-limb amputee from intraneural peripheral signals

Silvestro Micera, Ivo Strauss, Giacomo Valle

Objective. Recent results have shown the potentials of neural interfaces to provide sensory feedback to subjects with limb amputation increasing prosthesis usability. However, their advantages for decoding motor control signals over current methods based o ...

IOP Publishing Ltd2021

Cortical cell assemblies and their underlying connectivity: an in silico study

Michael Reimann, András Ecker, Daniela Egas Santander, James Bryden Isbister, Sirio Bolaños Puchet

Recent developments in experimental techniques have enabled simultaneous recordings from thousands of neurons, enabling the study of functional cell assemblies. However, determining the patterns of synaptic connectivity giving rise to these assemblies rema ...

2024

Online interoperable resources for building hippocampal neuron models via the Hippocampus Hub

Felix Schürmann, Armando Romani

To build biophysically detailed models of brain cells, circuits, and regions, a data-driven approach is increasingly being adopted. This helps to obtain a simulated activity that reproduces the experimentally recorded neural dynamics as faithfully as possi ...

2023

Clustering and control for adaptation uncovers time-warped spike time patterns in cortical networks in vivo

James Bryden Isbister

How information in the nervous system is encoded by patterns of action potentials (i.e. spikes) remains an open question. Multi-neuron patterns of single spikes are a prime candidate for spike time encoding but their temporal variability requires further c ...

Nature Research2021

Principles of Network Plasticity in Neocortical Microcircuits

András Ecker

Synaptic plasticity underlies our ability to learn and adapt to the constantly changing environment. The phenomenon of synapses changing their efficacy in an activity-dependent manner is often studied in small groups of neurons in vitro or indirectly throu ...

EPFL2023