2 papers
cs.AR2026
TESSERA: A Workload-Driven Simulation and Design-Space Exploration Framework for Heterogeneous NPUs
Arghadip Das, Hoseok Kim, Soomin Lee +3
AI model architectures are diversifying rapidly. While CNNs and transformers rely on dense matrix multiplication, emerging architectures (state-space models, fast Fourier transform…
cs.AR2026
BIDENT: Heterogeneous Operator-level Mapping for Efficient Edge Inference
Hoseok Kim, Arghadip Das, Soumendu Ghosh +2
Modern edge System-on-Chips (SoCs) integrate increasingly heterogeneous processing units (PUs) such as CPUs, GPUs, and NPUs, yet current inference stacks still map entire models to…