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Can Large Language Models Write Parallel Code?
Large language models are increasingly becoming a popular tool for software development.
Modeling Parallel Programs using Large Language Models
In this paper, we show how large language models (LLMs) can be applied to tasks specific to high performance and scientific codes.
A Survey and Empirical Evaluation of Parallel Deep Learning Frameworks
This phenomenon has spurred the development of algorithms for distributed training of neural networks over a larger number of hardware accelerators.
Integrating Deep Learning in Domain Sciences at Exascale
This paper discusses the necessities of an HPC deep learning framework and how those needs can be provided (e. g., as in MagmaDNN) through a deep integration with existing HPC libraries, such as MAGMA and its modular memory management, MPI, CuBLAS, CuDNN, MKL, and HIP.
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