Many large scale computing efforts remain out of reach. I research novel software and hardware designs to move these challenges forward. Programming language concepts for hybrid memory systems are a logical sequel to my work on storage. AI Accelerators and their software bring a revolution to high-performance computing. Other current topics in hardware design, such as leveraging mixed-precision, are on my radar. I am interested in computing platforms for machine learning and its use in the sciences, as an alternative to traditional simulation, and as a scientific method. I give lectures and keynotes every year, about work I am involved in, often emphasizing the efforts of others.

In 1995 I started to work on distributed file systems, and in 1999, unexpectedly, an opportunity emerged to design a new cluster file system which I named Lustre. Guided almost entirely by the requirements of the largest US government laboratories I led its architecture until 2008. Hundreds of individuals and hundreds of companies have made important contributions to it. It is now a cornerstone of scientific computing as one of the most used HPC software packages. My work on Lustre originated from and led to many other storage projects.

The square kilometer array (SKA) radio telescope poses a grand-challenge in data-intensive computing to convert the input from the antennas into usable scientific data. I worked with the SKA Science Data Processing (SDP) group in the Cavendish Laboratory at Cambridge University to develop the architecture to approach these problems. A more detailed page about this can be found on this site.