Abstract: Sparse matrix multiplication is widely used in various practical applications. Different accelerators have been proposed to speed up sparse matrix-dense vector multiplication (SpMV), sparse ...
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FLUTE: A CUDA Kernel Designed for Fused Quantized Matrix Multiplications to Accelerate LLM Inference
Large Language Models (LLMs) face deployment challenges due to latency issues caused by memory bandwidth constraints. Researchers use weight-only quantization to address this, compressing LLM ...
I have investigated the symptoms of this in some detail but have not tried to find the cause: In short it seems like matrix multiplications with largeish numbers fails inconsistently in windows, and ...
A new technical paper titled “Scalable MatMul-free Language Modeling” was published by UC Santa Cruz, Soochow University, UC Davis, and LuxiTech. “Matrix multiplication (MatMul) typically dominates ...
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