Model Compression Through Pruning And Structured Sparsity Support

Lightweight ML inference for mobile and edge devices.

Unique: Runtime support for pruned and sparsified models that skip zero-valued weights and use sparse tensor formats, enabling compression beyond quantization for models trained with sparsity constraints.

vs others: Complementary to quantization for additional compression; however, requires training-time support and sparse tensor format standardization which are not fully documented.