Browsing by Subject "Efficient implementation"

Now showing 1 - 6 of 6

Open Access
Accuracy: The Frequently Overlooked Parameter in the Solution of Extremely Large Problems
(IEEE, 2011) Ergul, O.; Gürel, Levent
We investigate error sources and their effects on the accuracy of solutions of extremely large electromagnetics problems with parallel implementations of the multilevel fast multipole algorithm (MLFMA). Accuracy parameters and their effects on the accuracy of MLFMA solutions are studied for large-scale problems discretized with hundreds of millions of unknowns. We show that some error sources are more dominant and should be suppressed for more accurate solutions; identifying less-effective error sources may allow us to derive more efficient implementations. Based on our analysis, we determine a set of benchmark problems that can be used to compare the accuracy of solvers for large-scale computations. A benchmarking tool is provided at www.cem.bilkent.edu.tr/ benchmark.
Open Access
Cluster searching strategies for collaborative recommendation systems
(2013) Altingovde, I. S.; Subakan, Ö. N.; Ulusoy, Özgür
In-memory nearest neighbor computation is a typical collaborative filtering approach for high recommendation accuracy. However, this approach is not scalable given the huge number of customers and items in typical commercial applications. Cluster-based collaborative filtering techniques can be a remedy for the efficiency problem, but they usually provide relatively lower accuracy figures, since they may become over-generalized and produce less-personalized recommendations. Our research explores an individualistic strategy which initially clusters the users and then exploits the members within clusters, but not just the cluster representatives, during the recommendation generation stage. We provide an efficient implementation of this strategy by adapting a specifically tailored cluster- skipping inverted index structure. Experimental results reveal that the individualistic strategy with the cluster-skipping index is a good compromise that yields high accuracy and reasonable scalability figures. © 2012 Elsevier Ltd. All rights reserved.
Open Access
Cost-efficient approximation of linear systems with repeated and multi-channel filtering configurations
(IEEE, 1998-05) Kutay, Mehmet Alper; Erden, M. F.; Özaktaş, Haldun M.; Arıkan, Orhan; Candan, Ç.; Güleryüz, Ö.
It is possible to obtain either exact realizations or useful approximations of linear systems or matrix-vector products arising in many different applications, by synthesizing them in the form of repeated or multi-channel filtering operations in fractional Fourier domains, resulting in much more efficient implementations with acceptable decreases in accuracy. By varying the number and configuration of filter blocks, which may take the form of arbitrary flow graphs, it is possible to trade off between accuracy and efficiency in the desired manner. The proposed scheme constitutes a systematic way of exploiting the information inherent in the regularity or structure of a given linear system or matrix, even when that structure is not readily apparent.
Open Access
Dynamic lot sizing with multiple suppliers, backlogging and quantity discounts
(Elsevier Ltd, 2017) Ghaniabadi, M.; Mazinani, A.
This paper studies the dynamic lot sizing problem with supplier selection, backlogging and quantity discounts. Two known discount types are considered separately, incremental and all-units quantity discounts. Mixed integer linear programming (MILP) formulations are presented for each case and solved using a commercial optimization software. In order to timely solve the problem, a recursive formulation and its efficient implementation are introduced for each case which result in an optimal and a near optimal solution for incremental and all-units quantity discount cases, respectively. Finally, the execution times of the MILP models and forward dynamic programming models obtained from the recursive formulations are presented and compared. The results demonstrate the efficiency of the dynamic programming models, as they can solve even large-sized instances quite timely. © 2017
Open Access
An efficient bandit algorithm for general weight assignments
(IEEE, 2017) Gökçesu, Kaan; Ergen, Tolga; Çiftçi, S.; Kozat, Süleyman Serdar
In this paper, we study the adversarial multi armed bandit problem and present a generally implementable efficient bandit arm selection structure. Since we do not have any statistical assumptions on the bandit arm losses, the results in the paper are guaranteed to hold in an individual sequence manner. The introduced framework is able to achieve the optimal regret bounds by employing general weight assignments on bandit arm selection sequences. Hence, this framework can be used for a wide range of applications.
Open Access
An FPGA implementation architecture for decoding of polar codes
(IEEE, 2011) Pamuk, Alptekin
Polar codes are a class of codes versatile enough to achieve the Shannon bound in a large array of source and channel coding problems. For that reason it is important to have efficient implementation architectures for polar codes in hardware. Motivated by this fact we propose a belief propagation (BP) decoder architecture for an increasingly popular hardware platform; Field Programmable Gate Array (FPGA). The proposed architecture supports any code rate and is quite flexible in terms of hardware complexity and throughput. The architecture can also be extended to support multiple block lengths without increasing the hardware complexity a lot. Moreover various schedulers can be adapted into the proposed architecture so that list decoding techniques can be used with a single block. Finally the proposed architecture is compared with a convolutional turbo code (CTC) decoder for WiMAX taken from a Xilinx Product Specification and seen that polar codes are superior to CTC codes both in hardware complexity and throughput. © 2011 IEEE.