Legion is a data-centric parallel programming system for writing portable high performance programs targeted at distributed heterogeneous architectures. Legion presents abstractions which allow programmers to describe properties of program data (e.g. independence, locality). By making the Legion programming system aware of the structure of program data, it can automate many of the tedious tasks programmers currently face, including correctly extracting task- and data-level parallelism and moving data around complex memory hierarchies. A novel mapping interface provides explicit programmer controlled placement of data in the memory hierarchy and assignment of tasks to processors in a way that is orthogonal to correctness, thereby enabling easy porting and tuning of Legion applications to new architectures.

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About Legion

Legion is developed as an open source project, with major contributions from LANL, NVIDIA Research, SLAC, and Stanford. This research was supported by the Exascale Computing Project (17-SC-20-SC), a collaborative effort of two U.S. Department of Energy organizations (Office of Science and the National Nuclear Security Administration) responsible for the planning and preparation of a capable exascale ecosystem, including software, applications, hardware, advanced system engineering, and early testbed platforms, in support of the nation’s exascale computing imperative. Additional support has been provided to LANL and SLAC via the Department of Energy Office of Advanced Scientific Computing Research and to NVIDIA, LANL and Stanford from the U.S. Department of Energy National Nuclear Security Administration Advanced Simulation and Computing Program. Previous support for Legion has included the U.S. Department of Energy’s ExaCT Combustion Co-Design Center and the Scientific Data Management, Analysis and Visualization (SDMAV) program, DARPA, the Army High Performance Computing Research Center, and NVIDIA, and grants from OLCF, NERSC, and the Swiss National Supercomputing Centre (CSCS).

Legion Contributors