Busy GPUs: Sampling and pipelining method speeds up deep learning on large graphs

New technique significantly reduces training and inference time on extensive datasets to keep pace with fast-moving data in finance, social networks, and fraud detection in cryptocurrency.

algorithms artificial intelligence computer chips computer modeling computer science and technology data deep learning gpus graphs machine learning mit-ibm watson ai lab mit schwarzman college of computing research sampling school of engineering sustainable computing