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1 Department of Applied Mathematics, University of Colorado at Boulder, Email: brannick@newton.colorado.edu, mbrezina@math.cudenver.edu, maclachl@colorado.edu, tmanteuf@colorado.edu, stevem@colorado.edu, jruge@colorado.edu 2 Department of Mathematical Sciences, Ball State University, Email: ilivshits@bsu.edu 3 Department of Applied Physics and Applied(More)
Many fundamental and resource-intensive tasks in scientific computing, such as solving linear systems, can be approached through multiple algorithms. Using an algorithm well adapted to characteristics of the task can significantly enhance the performance by reducing resource utilization without compromising the quality of the result. Given the numerous(More)
We introduce a model for communication costs in parallel processing environments, called the "hyperbolic model," which generalizes two-parameter dedicated-link models in an analytically simple way. Dedicated interprocessor links parameterized by a latency and a transfer rate that are independent of load are assumed by many existing communication models;(More)
Hardware accelerators are becoming ubiquitous high performance scientific computing. They are capable of delivering an unprecedented level of concurrent execution contexts. High-level programming languages (e.g., CUDA), profiling tools (e.g., PAPI-CUDA, CUDA Profiler) are paramount to improve productivity, while effectively exploiting the underlying(More)
A computational aeroacoustics code based on the discontinuous Galerkin method is ported to several parallel platforms using MPI. The discontinuous Galerkin method is a compact high-order method that retains its accuracy and robustness on non-smooth unstructured meshes. In its semi-discrete form, the discontinuous Galerkin method can be combined with(More)
Hardware-aware design and optimization is crucial in exploiting emerging architectures for PDE-based computational fluid dynamics applications. In this work, we study optimizations aimed at acceleration of OpenFOAM-based applications on emerging hybrid heterogeneous platforms. OpenFOAM uses MPI to provide parallel multi-processor functionality, which scales(More)
Design and Optimization of OpenFOAM-based CFD Applications for Modern Hybrid and Heterogeneous HPC Platforms Amani AlOnazi The progress of high performance computing platforms is dramatic, and most of the simulations carried out on these platforms result in improvements on one level, yet expose shortcomings of current CFD packages. Therefore, hardware-aware(More)
As processor clock rates become more dynamic and workloads become more adaptive, the vulnerability to global synchronization that already complicates programming for performance in today's petascale environment will be exacerbated. Algebraic multigrid (AMG), the solver of choice in many large-scale PDE-based simulations, scales well in the weak sense, with(More)
OBJECTIVE To determine if T1ρ magnetic resonance imaging (T1ρ MRI) could assess early articular cartilage changes in knees of asymptomatic female collegiate athletes. It was hypothesized that impact cohort would demonstrate greater changes than nonimpact cohort. DESIGN An institutional review board-approved prospective cohort study. Blinded MRI analyses.(More)
PDE-constrained optimization refers to the optimization of systems governed by partial differential equations (PDEs). The simulation problem is to solve the PDEs for the state variables (e.g. displacement, velocity, temperature, electric field, magnetic field, species concentration), given appropriate data (e.g. geometry, coefficients, boundary conditions,(More)