TaLPas: Task-Based Load Balancing and Auto-Tuning in Particle Simulations
Event Type
Project Poster
TimeTuesday, June 23rd4:35pm - 4:37pm
LocationAnalog 2
DescriptionTaLPas provides a solution to fast and robust simulation of many, inter-dependent particle systems in peta- and exascale supercomputing environments. This will be beneficial for a wide range of applications. TaLPas focuses on sampling in molecular dynamics (rare event sampling, sampling of equations of state, etc.).
TaLPas targets
1. the development of an auto-tuning based particle simulation library AutoPas to leverage optimal node-level performance,
2. the development of a scalable workflow manager to optimally distribute inter-dependent particle simulation tasks on HPC compute resources,
3. the investigation of performance prediction methods for particle simulations to support auto-tuning and to feed the workflow manager with accurate runtime predictions,
4. the integration of 1-3, augmented by visualization of the sampling (parameter space exploration) and an approach to resilience. The latter will guarantee robustness at peta- and exascale.
On this poster, we discuss latest work in the project that has just entered its final phase. We discuss the integration of the auto-tuning library AutoPas in the MD code ls1 mardyn and its use in massively parallel, load-balanced simulations. Furthermore, we outline the application of the TaLPas workflow manager for MD sampling in adsorption processes, including latest developments on performance prediction. Besides, visualization aspects are addressed.
Poster PDF