The content discusses the limitations of monolithic neural networks in NLP and introduces the MAMMOTH toolkit designed for training modular machine translation systems. It emphasizes the importance of modularity in handling scalability issues, especially in multilingual settings. The toolkit aims to provide efficient computation across clusters of GPUs and covers various architectures and use cases. By showcasing its performance on NVIDIA V100 and A100 clusters, the authors demonstrate nearly ideal scaling with different parameter-sharing schemes. Additionally, environmental costs are considered, highlighting the carbon footprint of running benchmarking experiments.
toiselle kielelle
lähdeaineistosta
arxiv.org
Syvällisempiä Kysymyksiä