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What does AMR stand for?

AMR stands for Adaptive Mesh Refinement

This definition appears very frequently and is found in the following Acronym Finder categories:

  • Science, medicine, engineering, etc.

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We have 245 other meanings of AMR in our Acronym Attic

Samples in periodicals archive:

They propose state-of-the-art algorithms that are designed to be used in a variety of applications and libraries, covering parallel and distributed Java for heterogeneous systems, the optimization of dense linear algebra algorithms on heterogeneous machines, distributed process networks with COBRA, parallel adaptive mesh refinement with load balancing in a heterogeneous cluster, evaluation of DIET hierarchical metacomputing architecture, and utilization-based techniques for strategically mapping heterogeneous applications into the HiPer-D heterogeneous computing system.
Key Topics Covered: * Introduction: Enabling Large-Scale Computational Science Motivations, Requirements, and Challenges - Manish Parashar and Xiaolin Li * Part I Adaptive Applications in Science and Engineering * Adaptive Mesh Refinement MHD Simulations of Tokamak Refueling - Ravi Samtaney * Parallel Computing Engines for Subsurface Imaging Technologies - Tian-Chyi J.
5, leveraging Ansoft's industry-leading adaptive mesh refinement technology, allows users to find layout problems quickly and warns of possible bond wire and via electromigration damage prior to the fabrication of a prototype.
The system performed best in its class and second overall on two tests: performing more than twice as fast as the leading Itanium system on the HPC Challenge random updates to memory test, which is important for adaptive mesh refinement codes such as SAGE, Partisan and CTH; and exceeding the performance of a comparably sized IBM p655 with Federation switch by more than 8 times on the global floating point execution test (FFTE benchmark), which is a useful measure of the total communications capacity of the network and affects codes such as molecular dynamic and climate prediction models.