214 Open source projects that are alternatives of or similar to auryn

A brian2 extension to simulate spiking neural networks on GPUs

Brain Dynamics Programming in Python

Brain models implementation with BrainPy

spiking-neural-networks

CARLsim is an efficient, easy-to-use, GPU-accelerated software framework for simulating large-scale spiking neural network (SNN) models with a high degree of biological detail.

Python library for easy creation and running of spiking neural networks in tensorflow.

Traveling Salesman Problem Using Parallel Genetic Algorithms

Event-Based Angular Velocity Regression with Spiking Networks

The primary source code repository for PHCpack, a software package to solve polynomial systems with homotopy continuation methods.

Algorithms implemented in CUDA + resources about GPGPU

Parallel Matrix Multiplication Using OpenMP, Phtreads, and MPI

TerraME is a programming environment for spatial dynamical modelling

Shape Aware Parallel Mesh Simplification Algorithm

WRENCH: Cyberinfrastructure Simulation Workbench

The Human Neocortical Neurosolver (HNN) is a software tool that gives researchers/clinicians the ability to develop/test hypotheses on circuit mechanisms underlying EEG/MEG data.

JAX-based Spiking Neural Network framework

A package for data-driven validation of neuron and ion channel models using SciUnit

A large-scale spiking model of the vision-related areas of macaque cortex.

Códigos feitos para o curso de Multithreading com Java, no canal RinaldoDev do YouTube.

RBM implemented with spiking neurons in Python. Contrastive Divergence used to train the network.

SPH simulation in Vulkan compute shader.

Manage AWS ParallelCluster through an easy to use web interface

coursera

Learning and practice of high performance computing (CUDA, Vulkan, OpenCL, OpenMP, TBB, SSE/AVX, NEON, MPI, coroutines, etc. )

corebench - run your benchmarks against high performance computing servers with many CPU cores

Cell centred code for explicit solid dynamics in OpenFOAM

Synaptic Plasticity with Online Reinforcement learning

Rules-based engine for life sims, with time travel

FreeFEM website

Constrained Large Deformation Diffeomorphic Image Registration (CLAIRE)

R package to provide foreach looping construct

Massively Scalable Clustering

A JavaScript interpreter for Paws.

This repository will host models, modules, algorithms and applications developed by the INRC Community to run on the Intel Loihi Platform.

Deep learning for spiking neural networks

Simulation of spiking neural networks (SNNs) using PyTorch.

Light-weight header-only library for parallel function calls and continuations in C++ based on Eric Niebler's talk at CppCon 2019.

A High-Performance Data Science Toolkit for the Earth Sciences

GARDENIA: Graph Analytics Repository for Designing Efficient Next-generation Accelerators

DRACO: Byzantine-resilient Distributed Training via Redundant Gradients

Java implementation of the IEEE-1278.1 Distributed Interactive Simulation (DIS) application protocol v6 and v7 💥

FreeFEM user documentation

Parallel Hyperparameter Tuning in Python

OpenN@S: Open-source software to NAS automatic VHDL code generation

A collection of mathematically validated modules (EDP) for FreeFEM

implement distributed machine learning with Pytorch + OpenMPI

Training spiking networks with hybrid ann-snn conversion and spike-based backpropagation

Quad/octree building for FMMs in Python and OpenCL

Climate science package for Julia

Nuerapse simulations for SNNs

Self Driving Cars Longitudinal and Lateral Control Design

Massively parallel FEM code for phase-field for fracture by Dolbow Lab at Duke University

Domain-specific compiler for Finite Difference/Volume/Element Earth-system models in Fortran

Julia Devito inversion.

Fast and easy parallel mapreduce on HPC clusters

Data encoders

tools for scalable and non-intrusive parameter estimation, uncertainty analysis and sensitivity analysis

Analysis kit for large-scale structure datasets, the massively parallel way

SPH simulation in OpenGL compute shader.

Short undergraduate course taught at University of Pennsylvania on computational and theoretical neuroscience. Provides an introduction to programming in MATLAB, single-neuron models, ion channel models, basic neural networks, and neural decoding.