3 papers
cs.NE2025
PASCAL: Precise and Efficient ANN- SNN Conversion using Spike Accumulation and Adaptive Layerwise Activation
Pranav Ramesh, Gopalakrishnan Srinivasan
Spiking Neural Networks (SNNs) have been put forward as an energy-efficient alternative to Artificial Neural Networks (ANNs) since they perform sparse Accumulate operations instead…
cs.NE2025
NeuroFlex: Column-Exact ANN-SNN Co-Execution Accelerator with Cost-Guided Scheduling
Varun Manjunath, Pranav Ramesh, Gopalakrishnan Srinivasan
NeuroFlex is a column-level accelerator that co-executes artificial and spiking neural networks to minimize energy-delay product on sparse edge workloads with competitive accuracy.…
cs.LG2024
QuAKE: Speeding up Model Inference Using Quick and Approximate Kernels for Exponential Non-Linearities
Sai Kiran Narayanaswami, Gopalakrishnan Srinivasan, Balaraman Ravindran
As machine learning gets deployed more and more widely, and model sizes continue to grow, improving computational efficiency during model inference has become a key challenge. In m…