HelioX: A GPU-Native Framework for Simulation and Training of Biophysically Detailed Networks
HelioX provides a GPU-native simulation-and-training stack for biophysically detailed neural networks, with substantial improvements in throughput, memory efficiency, and scalability.
May 10, 2026
HelioX - A GPU-Native Framework for Simulation and Training of Biophysically Detailed Networks
Accepted at ICML 2026. HelioX is a GPU-native framework for simulation and training of biophysically detailed neural networks. It targets the mismatch between irregular dendritic computation and conventional deep learning stacks, and provides an end-to-end pipeline for both forward simulation and gradient-based training. Highlights: Multi-stream GPU execution for ionic current calculation, ODE construction, and conductance update Efficient spike handling path designed for sparse spike events End-to-end differentiable training for deep biophysical neural architectures Strong runtime and scalability gains over traditional simulators in large-scale settings
May 10, 2026