Browsing by Subject "Optimization algorithms"

Now showing 1 - 4 of 4

Open Access
Autopipelining for data stream processing
(Institute of Electrical and Electronics Engineers, 2013) Tang, Y.; Gedik, B.
Stream processing applications use online analytics to ingest high-rate data sources, process them on-the-fly, and generate live results in a timely manner. The data flow graph representation of these applications facilitates the specification of stream computing tasks with ease, and also lends itself to possible runtime exploitation of parallelization on multicore processors. While the data flow graphs naturally contain a rich set of parallelization opportunities, exploiting them is challenging due to the combinatorial number of possible configurations. Furthermore, the best configuration is dynamic in nature; it can differ across multiple runs of the application, and even during different phases of the same run. In this paper, we propose an autopipelining solution that can take advantage of multicore processors to improve throughput of streaming applications, in an effective and transparent way. The solution is effective in the sense that it provides good utilization of resources by dynamically finding and exploiting sources of pipeline parallelism in streaming applications. It is transparent in the sense that it does not require any hints from the application developers. As a part of our solution, we describe a light-weight runtime profiling scheme to learn resource usage of operators comprising the application, an optimization algorithm to locate best places in the data flow graph to explore additional parallelism, and an adaptive control scheme to find the right level of parallelism. We have implemented our solution in an industrial-strength stream processing system. Our experimental evaluation based on microbenchmarks, synthetic workloads, as well as real-world applications confirms that our design is effective in optimizing the throughput of stream processing applications without requiring any changes to the application code. © 1990-2012 IEEE.
Open Access
Determining F2 layer parameters via optimization using IRI model and IONOLAB TEC estimations
(IEEE, 2011) Şahin, O.; Sezen, U.; Arıkan, F.; Arıkan, Orhan
We know that F2 layer of the ionosphere is most important layer in the progaration of high frequency (HF) waves. In this study, The relation of the height (HmF2) and the critical frequency (FoF2) of F2 layer-among the parameters of the Internation Reference Ionesphere (IRI) model-to the Total Electron Content (TEC) structure of ionosphere is investigated within their defined parametric range. These two parameters are then optimized using IONOLAB TEC estimations. Performance of the optimization algorithm is examined seperately for the cases of processing daily (24-hour) and hourly TEC data. It is observed that using hourly data produce results with much smaller errors. By using this optimization method, the height and the critical frequency of F2 layer are obtained for countries located on low and high latitudes including Turkey for the same quite day. Results are compared with ionosonde data and it is observed that error norms were in an acceptable range. By this way it is attained the more realistic electrical structure of ionosphere.
Open Access
Optimization of F2 layer parameters using IRI-Plas model and IONOLAB Total Electron Content
(IEEE, 2011) Sahin O.; Sezen, U.; Arikan F.; Arıkan, Orhan; Aktug, B.
In this study, the relation of the maximum ionization height (HmF2) and the critical frequency (FoF2) of F2 layer is examined within their parametric range through the International Reference Ionosphere extended towards the plasmasphere (IRI-Plas) model and the IONOLAB-TEC (Total Electron Content) observations. HmF2 and FoF2 are optimized using an iterational loop through Non-Linear Least Squares method by also using a physical relation constraint between these two parameters. Performance evaluation of optimization algorithm is performed separately for the cases running IRI-Plas with optimized parameters and TEC input; only with optimized parameters; only with TEC and finally with no optimized parameter and TEC input. As a conclusion, it is seen that using optimized parameters and TEC together as input produces best IRI-TEC estimates. But also using only optimized parameters (without TEC update) gives estimates with also very low RMS errors and is suitable to use in optimizations. HmF2 and FoF2 estimates are obtained separately for a quiet day, positively corrupted day, negatively corrupted day, a northern latitude and a southern latitude. HmF2 and FoF2 estimation results are compared with ionosonde data where available. This study enables the modification and update of empirical and deterministic IRI Model to include instantaneous variability of the ionosphere. © 2011 IEEE.
Open Access
Signal processing problems and algorithms in display side of 3DTV
(IEEE, 2006-10) Ulusoy, E.; Esmer, Gökhan Bora; Özaktaş, Haldun M.; Onural, Levent; Gotchev, A.; Uzunov, V.
Two important signal processing problems in the display side of a holographic 3DTV are the computation of the diffraction field of a 3D object from its abstract representation, and determination of the best display configuration to synthesize some intended light distribution. To solve the former problem, we worked on the computation of ID diffraction patterns from discrete data distributed over 2D space. The problem is solved using matrix pseudo-inversion which dominates the computational complexity. Then, the light field synthesis problem by a deflectable mirror array device (DMAD) is posed as a constrained linear optimization problem. The formulation makes direct application of common optimization algorithms quite easy. The simulations indicate that developed methods are promising. ©2006 IEEE.