Article in Edited Volumes
Systems of Partial Differential Equations in ExaSlang
Author(s): Schmitt C, Kuckuk S, Hannig F, Teich J, Köstler H, Rüde U, Lengauer C
Title edited volumes: Software for Exascale Computing - SPPEXA 2013-2015
Publishing place: Berlin, Heidelberg, New York
Publication year: 2016
Title of series: Lecture Notes in Computational Science and Engineering
Pages range: 47-67
As HPC systems are becoming increasingly heterogeneous and diverse, writing software that attains maximum performance and scalability while remaining portable as well as easily composable is getting more and more challenging. Additionally, code that has been aggressively optimized for certain execution platforms is usually not easily portable to others without either losing a great share of performance or investing many hours by re-applying optimizations. One possible remedy is to exploit the potential given by technologies such as domain-specific languages (DSLs) that provide appropriate abstractions and allow the application of technologies like automatic code generation and auto-tuning. In the domain of geometric multigrid solvers, project ExaStencils follows this road by aiming at providing highly optimized and scalable numerical solvers, specifically tuned for a given application and target platform. Here, we introduce its DSL ExaSlang with data types for local vectors to support computations that use point-local vectors and matrices. These data types allow an intuitive modeling of many physical problems represented by systems of partial differential equations (PDEs), e.g., the simulation of flows that include vector-valued velocities.
FAU Authors / FAU Editors How to cite
APA: Schmitt, C., Kuckuk, S., Hannig, F., Teich, J., Köstler, H., Rüde, U., & Lengauer, C. (2016). Systems of Partial Differential Equations in ExaSlang. In Software for Exascale Computing - SPPEXA 2013-2015 (pp. 47-67). Berlin, Heidelberg, New York: Springer.
MLA: Schmitt, Christian, et al. "Systems of Partial Differential Equations in ExaSlang." Software for Exascale Computing - SPPEXA 2013-2015 Berlin, Heidelberg, New York: Springer, 2016. 47-67.