In recent years, with the trend of applying deep learning (DL) in high performance scientific
computing, the unique characteristics of emerging DL workloads in HPC raise great …

AI benchmarking provides yardsticks for benchmarking, measuring and evaluating
innovative AI algorithms, architecture, and systems. Coordinated by BenchCouncil, this …

Scientific communities are increasingly adopting machine learning and deep learning
models in their applications to accelerate scientific insights. High performance computing …

This paper presents some of the current challenges in designing deep learning artificial
intelligence (AI) and integrating it with traditional high-performance computing (HPC) …

Recent years witness a trend of applying large-scale distributed deep learning algorithms
(HPC AI) in both business and scientific computing areas, whose goal is to speed up the …

The plethora of complex Artificial Intelligence (AI) algorithms and available High-
Performance Computing (HPC) power stimulates the expeditious development of AI …

Artificial Intelligence (AI) is being adopted in different domains at an unprecedented scale. A
significant interest in the scientific community also involves leveraging machine learning …

As research and practice in artificial intelligence (AI) grow in leaps and bounds, the
resources necessary to sustain and support their operations also grow at an increasing …

In recent years, there has been a convergence of Big Data (BD), High Performance
Computing (HPC), and Machine Learning (ML) systems. This convergence is due to the …

Nowadays, scientific simulations on high-performance computing (HPC) systems can
generate large amounts of data (in the scale of terabytes or petabytes) per run. When this …