Institute of High Performance Computing (IHPC)

A new compression method developed at A*STAR shrinks energy and hardware requirements for complex computational platforms on everyday devices.

A purpose-built machine learning platform takes the guesswork out of catalyst formulations for green energy generation.

A*STAR researchers blend the physics of particle dynamics with complex computational simulations to gauge the risk of catching COVID-19 in different social settings.

A new machine learning model processes datasets from different sources simultaneously, paving the way for major advancements in medicine and beyond.

Materials science and computational techniques come together to advance new design schemes for aerospace alloys.

Machine learning and computational platforms are helping develop robust protocols for manufacturing an emerging class of strong, super lightweight alloys.

In developing a new process to synthesise stable qubits, A*STAR researchers are paving the way toward scalable and practical quantum devices.

A new mathematical model quickly and reliably predicts the origin of disruptive electromagnetic interference emanating from complex electronic circuits.

By linking past observations with future possibilities, a novel framework could help computers predict human actions more accurately.

A new method of spraying metallic powders on the surface of worn-out aircraft components at relatively low temperatures holds promise for the aerospace industry.

Through the years, A*STAR has always stood at the forefront of science and technology and innovation. Here’s how A*STAR came to be and what it has in store in the upcoming decades.

A*STAR’s steady investments in R&D and talent create the ideal conditions for impactful science, says its Chief Executive Officer Frederick Chew.