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Fast Polynomial Transcendentals for LLMs
Author1, Author2, Author3, Author4, Author5
performance optimizationlarge language modelspolynomial functions
2610.00049
Builder Relevance
20h ago70%
Abstract
This paper explores the acceleration of special-function-unit operations in large language models using short polynomial programs.
Reality Card
Core Claim
The implementation of degree-3 and degree-4 bfloat16 polynomial programs improves training-step throughput by up to 8.0% in specific tasks.
Method / Result
Complete training-step throughput improved by 8.0% for routed-expert Swish-gated linear unit (SwiGLU).
Limitations
The evaluation is limited to specific tasks and may not generalize across all LLM applications.
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