Static scheduling algorithms for allocating directed task graphs to multiprocessors
ACM Computing Surveys (CSUR)
Uintah: A Massively Parallel Problem Solving Environment
HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing
A component-based parallel infrastructure for the simulation of fluid–structure interaction
Engineering with Computers
An Eulerian-Lagrangian approach for simulating explosions of energetic devices
Computers and Structures
Parallel space-filling curve generation through sorting: Research Articles
Concurrency and Computation: Practice & Experience
Dynamic topology aware load balancing algorithms for molecular dynamics applications
Proceedings of the 23rd international conference on Supercomputing
A component-based architecture for parallel multi-physics PDE simulation
Future Generation Computer Systems
The cactus framework and toolkit: design and applications
VECPAR'02 Proceedings of the 5th international conference on High performance computing for computational science
Uintah: a scalable framework for hazard analysis
Proceedings of the 2010 TeraGrid Conference
A hybrid heuristic-genetic algorithm for task scheduling in heterogeneous processor networks
Journal of Parallel and Distributed Computing
Scalable parallel regridding algorithms for block-structured adaptive mesh refinement
Concurrency and Computation: Practice & Experience
p4est: Scalable Algorithms for Parallel Adaptive Mesh Refinement on Forests of Octrees
SIAM Journal on Scientific Computing
DAG-Based software frameworks for PDEs
Euro-Par'11 Proceedings of the 2011 international conference on Parallel Processing
Concurrency and Computation: Practice & Experience
Radiation modeling using the Uintah heterogeneous CPU/GPU runtime system
Proceedings of the 1st Conference of the Extreme Science and Engineering Discovery Environment: Bridging from the eXtreme to the campus and beyond
Preliminary experiences with the uintah framework on Intel Xeon Phi and stampede
Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery
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Present trends in high performance computing present formidable challenges for applications code using multicore nodes possibly with accelerators and/or co-processors and reduced memory while still attaining scalability. Software frameworks that execute machine-independent applications code using a runtime system that shields users from architectural complexities offer a possible solution. The Uintah framework for example, solves a broad class of large-scale problems on structured adaptive grids using fluid-flow solvers coupled with particle-based solids methods. Uintah executes directed acyclic graphs of computational tasks with a scalable asynchronous and dynamic runtime system for CPU cores and/or accelerators/co-processors on a node. Uintah's clear separation between application and runtime code has led to scalability increases of 1000x without significant changes to application code. This methodology is tested on three leading Top500 machines; OLCF Titan, TACC Stampede and ALCF Mira using three diverse and challenging applications problems. This investigation of scalability with regard to the different processors and communications performance leads to the overall conclusion that the adaptive DAG-based approach provides a very powerful abstraction for solving challenging multi-scale multi-physics engineering problems on some of the largest and most powerful computers available today.