This paper reviews some of the challenges posed by the huge growth of experimental data
generated by the new generation of large-scale experiments at UK national facilities at the …

Artificial intelligence (AI) and machine learning (ML) techniques have existed for years, but
new hardware trends and advances in model training and inference have radically improved …

Today's Internet Services are undergoing fundamental changes and shifting to an intelligent
computing era where AI is widely employed to augment services. In this context, many …

The complexity and diversity of big data and AI workloads make understanding them difficult
and challenging. This paper proposes a new approachto modelling and characterizing big …

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

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 …

Understanding the designs and performance characterizations of hot interconnects on
modern data center and high-performance computing (HPC) clusters is a fruitful research …

The cornerstone for the performance evaluation of computer systems is the benchmark suite.
Among the many benchmark suites used in high-performance computing and multicore …

Huge amounts of data are collected in numerous independent data storage facilities around
the world. However, how the data is distributed between physical locations remains …

We present Phronesis, a learning framework for efficiently modeling the performance of data
analytic workloads as a function of their high-dimensional software configuration …