5 papers
NeuroFlex: Lossless Element-Level ANN-SNN Co-Execution for Efficient Sparse Inference
Varun Manjunath, Pranav Ramesh, Gopalakrishnan Srinivasan
Sparse DNN accelerators specialize in ANN or SNN execution, leaving energy or latency on the table when workload characteristics vary within a layer. Hybrid accelerator designs tha…
Sal: Multi-modal Verification of Replicated Data Types
Pranav Ramesh, Vimala Soundarapandian, KC Sivaramakrishnan
Designing correct replicated data types (RDTs) is challenging because replicas evolve independently and must be merged while preserving application intent. A promising approach is…
NeuroFlex: Lossless Element-Level ANN-SNN Co-Execution for Efficient Sparse Inference
Varun Manjunath, Pranav Ramesh, Gopalakrishnan Srinivasan
Sparse DNN accelerators specialize in ANN or SNN execution, leaving energy or latency on the table when workload characteristics vary within a layer. Hybrid accelerator designs tha…
The Easy Path to Robustness: Coreset Selection using Sample Hardness
Pranav Ramesh, Arjun Roy, Deepak Ravikumar +2
Designing adversarially robust models from a data-centric perspective requires understanding which input samples are most crucial for learning resilient features. While coreset sel…
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…