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University of California, San Diego
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Transforming context ahead of time can slash time-to-first-token by nearly 12x, revolutionizing LLM agent efficiency.
FlashCP achieves up to 1.63x faster training for large language models by eliminating redundant communication and optimizing workload balance.
Forget GPU-centric designs: AMMA slashes attention latency by 15x and energy consumption by 7x with a memory-centric architecture for long-context LLMs.
