SANTA replaces full value-cache multiply-accumulates with stochastic gather-and-add sampling from the attention distribution to reduce memory bandwidth while preserving an unbiased estimator.
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A systematic review finds research on the sustainability of LLM-generated code to be limited, fragmented, and without accepted frameworks for measurement or benchmarking.
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Stochastic Sparse Attention for Memory-Bound Inference
SANTA replaces full value-cache multiply-accumulates with stochastic gather-and-add sampling from the attention distribution to reduce memory bandwidth while preserving an unbiased estimator.
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Sustainable Code Generation Using Large Language Models: A Systematic Literature Review
A systematic review finds research on the sustainability of LLM-generated code to be limited, fragmented, and without accepted frameworks for measurement or benchmarking.