Author

Priyadarshini Panda

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Preprint Aug 2026

Celty: SpMspV GPU Kernel and SIMT Co-Design for Efficient Dual-Sparse LLM Inference

Celty, a co-designed sparse format, GPU kernel, and SIMT microarchitecture for efficient spMspV in LLM inference is proposed, which introduces a Run-Length Compressed CSC format that enables vectorized loading of compressed weight columns and exploits both sparsity sources to skip unnecessary memory accesses.

Ruokai Yin, Priyadarshini Panda · 0 citations

Preprint Jul 2026

KronQ: LLM Quantization via Kronecker-Factored Hessian

KronQ, a PTQ framework that challenges the assumption that all output channels contribute equally to the layer-wise reconstruction objective by introducing the gradient covariance into the quantization pipeline, and introduces bidirectional incoherence processing.

Donghyun Lee, Yuhang Li, Ruokai Yin et al. · 0 citations