The dissociation rate (k off) associated with ligand unbinding events from proteins is a
parameter of fundamental importance in drug design. Here we review recent major …

Today's floating-point arithmetic landscape is broader than ever. While scientific computing
has traditionally used single precision and double precision floating-point arithmetics, half …

With the rapid development of deep learning, training Big Models (BMs) for multiple
downstream tasks becomes a popular paradigm. Researchers have achieved various …

Our performance benchmark of HPL-AI on the supercomputer Fugaku was awarded the 55th
Top500. The effective performance was 1.42 EFlop/s, and the world's first achievement to …

The prevalence of scientific workflows with high computational demands calls for their
execution on various distributed computing platforms, including large-scale leadership-class …

HPL-AI, also known as HPL-MxP, is a new benchmark program used to evaluate the upper-
bound performance of AI-related tasks on a specific computing cluster. It solves a large …

Low precision arithmetic, in particular half precision (16‐bit) floating point arithmetic, is now
available in commercial hardware. Using lower precision can offer significant savings in …

Many artificially intelligent systems solve complex health-and agriculture-related problems
that require great computational power. Such systems are used for tracking medical records …

In this work, fundamental performance, power, and energy characteristics of the full
SPEChpc 2021 benchmark suite are assessed on two different clusters based on Intel Ice …

With the emergence of mixed precision capabilities in hardware, iterative refinement
schemes for solving linear systems $ Ax= b $ have recently been revisited and reanalyzed in …