Topic: Data Movement and Memory

Multiphysics simulation codes must perform at scale on present and future massively parallel supercomputers, be adaptable and extendable, be sustainable across multiple generations of hardware, and work on general 2D and 3D domains. To this end, the Multiphysics on Advanced Platforms Project incorporates multiple software packages into one integrated code.

A Livermore-developed programming approach helps software to run on different platforms without major disruption to the source code.

The latest issue of LLNL's Science & Technology Review magazine showcases Computing in the cover story alongside a commentary by Bruce Hendrickson.

Highlights include response to the COVID-19 pandemic, high-order matrix-free algorithms, and managing memory spaces.

Researchers develop innovative data representations and algorithms to provide faster, more efficient ways to preserve information encoded in data.

Umpire is a resource management library that allows the discovery, provision, and management of memory on next-generation architectures.

Highlights include debris an shrapnel modeling at NIF, scalable algorithms for complex engineering systems, magnetic fusion simulation, and data placement optimization on GPUs.

Computer scientist Maya Gokhale appreciates the unpredictability and rapid pace of change in her chosen field. “You never know where computing is going to go, and that’s what’s exciting about it,” she says.