Is Your AI Data Pre-processing Fast Enough? Speed It Up Using rocAL

AMD’s rocAL (ROCm Augmentation Library) is an open-source library for decoding and augmenting images, video and audio to accelerate the loading and preprocessing of data for machine learning applications. In this talk, we will present key components of the data loading path and show how to efficiently combine them to get the most performance for your machine learning workload. With rocAL, you can create flexible hybrid pipelines that can be executed on a CPU or GPU for load balancing. After introducing rocAL and its key features, we will dive deep into some use cases focused on training DNNs for MLPerf benchmarks. Join us to learn how rocAL can significantly speed up your data loading pipeline for both training and inference.