Held in conjunction with The 48th International Conference on Parallel Processing
Parallel and distributed computing has been making tremendous impacts on the recent advancement of data-oriented machine learning such as deep learning. Accelerating ML workloads with HPC systems can present opportunities to enable more complicated machine learning. However, significant challenges remain to be addressed due to limited computation power against the huge volume of datasets. In this workshop, we bring together researchers in the field of machine learning and facilitate discussions for their experiences, new ideas and the latest trends to leverage HPC for ML, ML for HPC and ML applications in HPC.