High-Performance Computing (HPC) workloads generate large volumes of data at high-
frequency during their execution, which needs to be captured concurrently at scale. These …

Despite significant advances, training deep learning models remains a time-consuming and
resource-intensive task. One of the key challenges in this context is the ingestion of the …

Network Architecture Search and specifically Regularized Evolution is a common way to
refine the structure of a deep learning model. However, little is known about how models …

Deep Learning (DL) has seen rapid adoption in all domains. Since training DL models is
expensive, both in terms of time and resources, application workflows that make use of DL …