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Energy efficiency in high performance computing (HPC) will be critical to limit operating costs and carbon footprints in future supercomputing centers. Energy efficiency of a computation can be improved by reducing time to completion without a substantial increase in power drawn or by reducing power with a little increase in time to completion. We present an Adaptive Core-specific Runtime (ACR) that...
The simulation of multiscale physics is an important challenge for scientific computing. For this class of problem, large three-dimensional simulations are performed to advance scientific inquiry. On massively parallel computing systems, the volume of data generated by such approaches can become a productivity bottleneck if the raw data generated from the simulation is analyzed in a post-processing...
Power is increasingly the limiting factor in High Performance Computing (HPC). Growing core counts in each generation increase power and energy demands. In the future, strict power and energy budgets will be used to control the operating costs of supercomputer centers. Every node needs to use energy wisely. Energy efficiency can either be improved by taking less time or running at lower power. In...
We present CARRT∗ (Cache-Aware Rapidly Exploring Random Tree∗), an asymptotically optimal sampling-based motion planner that significantly reduces motion planning computation time by effectively utilizing the cache memory hierarchy of modern central processing units (CPUs). CARRT∗ can account for the CPU's cache size in a manner that keeps its working dataset in the cache. The motion planner progressively...
Large-scale simulation can provide a wide range of information needed to develop and validate theoretical models for multiphase flow in porous medium systems. In this paper, we consider a coupled solution in which a multiphase flow simulator is coupled to an analysis approach used to extract the interfacial geometries as the flow evolves. This has been implemented using MPI to target heterogeneous...
Simulations of colliding galaxies or fluid dynamics at immersed flexible boundaries are most accurately and efficiently accomplished using the adaptive fast multipole method (AFMM) to solve an underlying n-body problem whose localized density varies with the time-dependent evolution of the system under study. Parallelization of the AFMM presents a challenging load balancing problem that must be addressed...
Understanding on-node application power and performance characteristics is critical to the push toward exascale computing. In this paper, we present an analysis of factors that impact both performance and energy usage of OpenMP applications. Using hardware performance counters in the Intel Sandy bridge X86-64 architecture, we measure energy usage and power draw for a variety of OpenMP programs: simple...
Task parallelism raises the level of abstraction in shared memory parallel programming to simplify the development of complex applications. However, task parallel applications can exhibit poor performance due to thread idleness, scheduling overheads, and work time inflation -- additional time spent by threads in a multithreaded computation beyond the time required to perform the same work in a sequential...
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