Author

Gopalakrishnan Srinivasan

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#machine learning Preprint Nov 2025

NeuroFlex: Lossless Element-Level ANN-SNN Co-Execution for Efficient Sparse Inference

NeuroFlex is the first accelerator to assign every output element independently to ANN or SNN execution mode with zero accuracy loss, and extends integer-exact ANN-SNN equivalence from layers to individual output elements, thereby enabling mode switching with no conversion error.

Varun Manjunath, P. Ramesh, Gopalakrishnan Srinivasan · 0 citations

Preprint Aug 2026

APEX: A Dual-Sparsity Accelerator for Precise and Efficient SNN Inference

APEX is presented, a dual-sparsity SNN inference accelerator that integrates the PASC-IF neuron into the LoAS hardware framework, and guarantees mathematical equivalence between the converted SNN and the source ANN, thereby achieving ANN-equivalent accuracy at significantly reduced timesteps.

D. Venkatesh, S. Radhakrishnan, Rajshekhar Rakshit et al. · 0 citations