The author details their experience porting Andrej Karpathy's microgpt, a concise Python implementation of a GPT-2-like neural network, to the data-parallel language Futhark. The goal was to improve scalability beyond Python's limitations while maintaining code similarity. This first part focuses on translating the forward pass, including data structures and core operations like linear transformations, softmax, and RMS normalization. The Futhark port achieves better scaling but is slightly less concise due to explicit typing. AI
IMPACT Demonstrates potential for improved performance and scalability of LLM implementations using data-parallel languages like Futhark.
RANK_REASON The article describes a technical porting effort of an existing AI model implementation to a new programming language, which falls under research and development.
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