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cs.LG2026
Mira: Memory-Efficient MoE Inference Using Adaptive Caching and Predictive Expert Staging
Sanjali Yadav, Bahar Asgari
Mixture-of-Experts (MoE) models are a compelling architecture for scaling model capacity, making them especially attractive for deployment on resource-constrained, single-GPU syste…
cs.LG2025
Mustafar: Promoting Unstructured Sparsity for KV Cache Pruning in LLM Inference
Donghyeon Joo, Helya Hosseini, Ramyad Hadidi +1
We demonstrate that unstructured sparsity significantly improves KV cache compression for LLMs, enabling sparsity levels up to 70% without compromising accuracy or requiring fine-t…
cs.LG2024
Misam: Using ML in Dataflow Selection of Sparse-Sparse Matrix Multiplication
Sanjali Yadav, Bahar Asgari
Sparse matrix-matrix multiplication (SpGEMM) is a critical operation in numerous fields, including scientific computing, graph analytics, and deep learning. These applications expl…