NeuronMLP applies SVD-based compression and Trainium-specific tiling and caching to MLP layers, delivering 1.35x kernel speedup and 1.21x end-to-end inference speedup at 0.05 compression ratio versus AWS NKI baseline.
Meta’s second generation ai chip: Model-chip co-design and productionization experiences
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CL 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
NeuronMLP: Efficient LLM Inference via Singular Value Decomposition Compression and Tiling on AWS Trainium
NeuronMLP applies SVD-based compression and Trainium-specific tiling and caching to MLP layers, delivering 1.35x kernel speedup and 1.21x end-to-end inference speedup at 0.05 compression ratio versus AWS NKI baseline.