A data center is a centralized location for all the resources of an organization. Data centers consist of servers, storage, and other network equipment necessary for the business requirements of an organization. Data centers have many end-user systems connected to them and resources are allocated on demand. Data are accessed and manipulated in a centralized location. This setup provides reliability and accessibility to the overall infrastructure making it more effective.
For conventional imaging systems, GEO space objects cannot be resolved due to their 40 Mm distance. There exists a strong need to obtain high resolution images of GEO objects and to accomplish this task, investigation into the suitability of ISAL is currently underway. A critical component in determining this suitability is to accurately model the atmospheric impacts on LADAR pulses. Conventional knowledge says that while the atmosphere churns, wind is the predominant cause of temporal evolution which simplifies all modeling and simulation into the frozen flow hypothesis. The concern is that the frozen flow hypothesis based phase screen generation techniques fail to accurately predict the temporal development of optical phase. This thesis proposes a new approach and provides a detailed derivation of a new temporally evolving Zernike polynomial based atmospheric phase screen generation model. This new model is experimentally verified, and utilized to analyze atmospheric impacts on mixing efficiencies. It is shown that this new turbulent flow model more accurately predicts mixing efficiency than that of the basic frozen flow approximation.
The resolutions of interests in atmospheric simulations require prohibitively large computational resources. Adaptive mesh refinement (AMR) tries to mitigate this problem by putting high resolution in crucial areas of the domain. We investigate the performance of a tree-based AMR algorithm for the high order discontinuous Galerkin method on quadrilateral grids with non- conforming elements. We perform a detailed analysis of the cost of AMR by comparing this to uniform reference simulations of two standard atmospheric test cases: density current and rising thermal bubble. The analysis shows up to 15 times speed-up of the AMR simulations with the cost of mesh adaptation below 1of the total runtime. We pay particular attention to the implicit-explicit (IMEX) time integration methods and show that the ARK2 method is more robust with respect to dynamically adapting meshes than BDF2. Preliminary analysis of preconditioning reveals that it can be an important factor in the AMR overhead. The compiler optimizations provide signi cant runtime reduction and positively a ect the e ectiveness of AMR allowing for speed-ups greater than it would follow from the simple performance model.