CDS&E: HAM3R: Heterogeneous Automated Management of Multiscale Methods and Resources

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To run large and detailed simulations, scientists need to resolve physics at different time scales. Separating each scale into individual simulations and coupling them together greatly lowers the execution time. The process of coupling the simulation is laborious, complex, and error-prone. Achieving performance and energy efficiency requires domain scientists to have deep knowledge of computer architectures and systems, and extensively tune the algorithms and resource requests. The current state-of-the-practice of manual coupling and optimization leads to duplication of programming efforts and solutions that are not portable to new problems and sizes, and to computer architectures and systems. This interdisciplinary project builds technologies, namely HAM3R (Heterogeneous Automated Management of Multiscale Methods and Resources), to automate the coupling and optimize the computing and energy efficiency for multiscale simulations. HAM3R is broadly applicable to multiscale problems in computational chemistry, physics, biology, and materials science. Greater simplicity and flexibility of simulation codes have broad impacts on computational science by reducing the entry barrier to domain scientists. Enabling domain researchers to leverage advanced cyberinfrastructure will accelerate scientific throughput, which can have transformative effects across a spectrum of disciplines. This project broadens the engagement of students and underrepresented groups and user communities. This project develops a versatile software framework (named HAM3R) for predictive resource, workload, fault, and power management that enables automated optimization of performance, scalability, and energy efficiency of multiscale models on heterogeneous HPC systems. HAM3R is a transformative software framework that removes the complexities of coupling multiscale simulations from domain scientists by enabling dynamic coupling of multiscale models that combines an API, library, and runtime to support broad coupling styles and domains. The analysis of computation and data bottlenecks yields enhanced analytical and machine-learned performance models. HAM3R will equip multiscale models with automated resource allocation -- including predictive load-balancing by proactive management of computation, communication, and data movement -- to enable scalability and efficient simulations on heterogeneous HPC systems. This project’s Intellectual Merit advances the following areas: (1) data-centric optimizations to reduce the cost of data motion intra- and inter-scale by migrating computation and using lossy data compression; (2) customized local recovery for process failures; (3) model-predictive load balancing schemes within and across scales that support intelligent resource management and dynamic adaption; and (4) advanced power management across heterogeneous devices to ensure energy-efficient execution. The project demonstrates the capabilities of HAM3R in two different popular multiscale modeling frameworks: coupled molecular dynamics and lattice Boltzmann method simulations via domain decomposition; coupled dissipative particle dynamics and finite element method simulations via heterogeneous multiscale methods.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.