Conference Talk: Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity

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Presented our full-paper research on Flash-LLM at the 50th International Conference on Very Large Data Bases (VLDB 2024). The presentation detailed a highly-efficient algorithm-system co-design that effectively leverages unstructured sparsity on modern Tensor Cores, offering a powerful and cost-effective remedy to overcome the memory wall for large generative model inference.