Topic: HPC Systems and Software

LLNL participates in the digital ISC High Performance Conference (ISC21) on June 24 through July 2.

Computer scientist Vanessa Sochat isn’t afraid to meet new experiences head on. With a Stanford PhD and a jump-right-in attitude, she joined LLNL to work on the BUILD project, Spack package manager, and other open-source initiatives.

Computing relies on engineers like Stephanie Brink to keep the legacy codes running smoothly. “You’re only as fast as your slowest processor or your slowest function,” says Brink, who works in CASC. By analyzing a legacy code’s performance, Brink and her team can reduce the amount of time it takes to run and allow for more critical science to be accomplished.

Highlights include scalable deep learning, high-order finite elements, data race detection, and reduced order models.

BUILD tackles the complexities of HPC software integration with dependency compatibility models, binary analysis tools, efficient logic solvers, and configuration optimization techniques.

Our researchers will be well represented at the virtual SIAM Conference on Computational Science and Engineering (CSE21) on March 1–5. SIAM is the Society for Industrial and Applied Mathematics with an international community of more than 14,500 individual members.

Proxy apps serve as specific targets for testing and simulation without the time, effort, and expertise that porting or changing most production codes would require.

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

The Maestro Workflow Conductor is a lightweight, open-source Python tool that can launch multi-step software simulation workflows in a clear, concise, consistent, and repeatable manner.

TEIMS manages collaborative tasks, site characterization, risk assessment, decision support, compliance monitoring, and regulatory reporting for the Environmental Restoration Department.

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

Computational Scientist Ramesh Pankajakshan came to LLNL in 2016 directly from the University of Tennessee at Chattanooga. But unlike most recent hires from universities, he switched from research professor to professional researcher.

Highlights include perspectives on machine learning and artificial intelligence in science, data driven models, autonomous vehicle operations, and the OpenMP standard 5.0.

FGPU provides code examples that port FORTRAN codes to run on IBM OpenPOWER platforms like LLNL's Sierra supercomputer.

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

Computer scientist Greg Becker contributes to HPC research and development projects for LLNL’s Livermore Computing division.

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

Users need tools that address bottlenecks, work with programming models, provide automatic analysis, and overcome the complexities and changing demands of exascale architectures.

Highlights include CASC director Jeff Hittinger's vision for the center as well as recent work with PruneJuice DataRaceBench, Caliper, and SUNDIALS.

LLNL's interconnection networks projects improve the communication and overall performance of parallel applications using interconnect topology-aware task mapping.

The PRUNERS Toolset offers four novel debugging and testing tools to assist programmers with detecting, remediating, and preventing errors in a coordinated manner.

LLNL's Advanced Simulation Computing program formed the Advanced Architecture and Portability Specialists team to help LLNL code teams identify and implement optimal porting strategies.

BLT software supports HPC software development with built-in CMake macros for external libraries, code health checks, and unit testing.

Highlights include the latest work with RAJA, the Exascale Computing Project, algebraic multigrid preconditioners, and OpenMP.

Highlights include complex simulation codes, uncertainty quantification, discrete event simulation, and the Unify file system.