Investigating Resource-efficient Neutron/Gamma Classification ML Models Targeting eFPGAs

arXiv:2404.14436v1 Announce Type: new
Abstract: There has been considerable interest and resulting progress in implementing machine learning (ML) models in hardware over the last several years from the particle and nuclear physics communities. A big driver has been the release of the Python package, hls4ml, which has enabled porting models specified and trained using Python ML libraries to register transfer level (RTL) code. So far, the primary end targets have been commercial FPGAs or synthesized custom blocks on ASICs. However, …

abstract arxiv big classification communities cs.lg driver hardware hep-ex machine machine learning ml models nuclear nucl-ex package particle physics physics.ins-det progress python release targeting type