The HPC world is full of complexity—from applications to the software components they rely on and the hardware they need to run. With the first three exascale machines, including Livermore’s El Capitan, slated to come online in the next few years, addressing complexity challenges will be a heavier, more urgent lift. Like our current Sierra system, these exascale systems will derive most of their computational power from secondary accelerator processors called GPUs. Traditionally, HPC systems have used only CPUs. With these machines, developers will need to accommodate not just NVIDIA accelerators but also new offerings from AMD and Intel. Harnessing the power of these devices entails using rapidly evolving programming environments, which require new compilers, runtime libraries, and software packages whose relationships are not always well understood. Without automated approaches to integration, developers will fight these software stacks by hand—but manual integration and maintenance are unsustainable.
A new effort kicking off in fiscal year 2021 aims to develop a machine-verifiable model of package compatibility that will enable automated integration, reducing human labor and errors. The Binary Understanding and Integration Logic for Dependencies (BUILD) project will run for three years with computer scientist Todd Gamblin at the helm. He states, “This project will develop techniques that enable rapid integration of HPC software systems, especially for upcoming exascale machines.” The project will build on Spack—the widely adopted package manager with a repository of more than 5,000 packages. Created by Gamblin in 2013 and today supported by a core development team, Spack already incorporates package configuration capabilities with dependency solving techniques.
