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Active set partitioning scheme for extending the lifetime of large wireless sensor networks
(Bilkent University, 2010)Wireless Sensor Networks consist of spatially distributed and energyconstrained autonomous devices called sensors to cooperatively monitor physical or environmental conditions such as temperature, sound, vibration, ... 
Adaptation of multiwaymerge sorting algorithm to MIMD architectures with an experimental study
(Bilkent University, 2002)Sorting is perhaps one of the most widely studied problems of computing. Numerous asymptotically optimal sequential algorithms have been discovered. Asymptotically optimal algorithms have been presented for varying ... 
Adaptive source routing and route generation for multicomputers
(Bilkent University, 1995)Scalable multicomputers are based upon interconnection networks that typically provide multiple communication routes between any given pair of processor nodes. In such networks, the selection of the routes is an important ... 
Application of map/reduce paradigm in supercomputing systems
(Bilkent University, 2013)Map/Reduce is a framework first introduced by Google in order to rapidly develop big data analytic applications on distributed computing systems. Even though the Map/Reduce paradigm had a game changing impact on certain ... 
Asymptotically optimal assignments in ordinal evaluations of proposals
(Bilkent University, 2009)In ordinal evaluations of proposals in peer review systems, a set of proposals is assigned to a fixed set of referees so as to maximize the number of pairwise comparisons of proposals under certain referee capacity and ... 
Balance preserving mincut replication set for a Kway hypergraph partitioning
(Bilkent University, 2010)Replication is a widely used technique in information retrieval and database systems for providing faulttolerance and reducing parallelization and processing costs. Combinatorial models based on hypergraph partitioning ... 
A bipartite graph model for placement, scheduling and replication in data grids
(Bilkent University, 2012)Data grids provide geographically distributed resources for applications that generate and utilize large data sets. However, there are some issues that hinder to ensure fast access to data and low turnaround time for the ... 
Cache locality exploiting methods and models for sparse matrixvector multiplication
(Bilkent University, 2009)The sparse matrixvector multiplication (SpMxV) is an important kernel operation widely used in linear solvers. The same sparse matrix is multiplied by a dense vector repeatedly in these solvers to solve a system of ... 
Clustering based approach for efficient AATX computations
(Bilkent University, 200109) 
CoDet : a new algorithm for containment and near duplicate detection in text corpora
(Bilkent University, 2012)In this thesis, we investigate containment detection, which is a generalized version of the well known nearduplicate detection problem concerning whether a document is a subset of another document. In textbased ... 
Coloring for distributedmemoryparallel GaussSeidel algorithm
(Bilkent University, 201909)GaussSeidel is a wellknown iterative method for solving linear system of equations. The computations performed on GaussSeidel sweeps are sequential in nature since each component of new iterations depends on previously ... 
Comparison of image space subdivision algorithms for parallel volume rendering
(Bilkent University, 1995)In many scientific applications, results are presented as unstructured volumetric data sets. Direct Volume Rendering (DVR) is a powerful way of visualizing these volumetric data sets. However, it involves intensive ... 
A constructive multiway circuit partitioning algorithm based on minimum degree ordering
(Bilkent University, 1994)Circuit partitioning has many important applications in VLSI. Circuit partitioning problem can be most properly modeled as hypergraph partitioning. In this work, we propose a novel kv/ay hypergraph partitioning heuristic ... 
Decomposing linear programs for parallel solution
(Bilkent University, 1996)Many current research efforts are based on better exploitation of sparsity— common in most large scaled problems—for computational efEciency. This work proposes different methods for permuting sparse matrices to block ... 
Efficient parallel digital signal processing algorithms for hypercubeconnected multicomputers
(Bilkent University, 1992)In this thesis, efficient parallelization of Digital Signal Processing (DSP) algorithms, (FFT, FHT and FCT), on multicomputers implementing the hypercube interconnection topology are investigated. The proposed ... 
Exploiting replicated data for communication load balancing in imagespace parallel direct volume rendering of unstructured grids
(Bilkent University, 2009)The focus of this work is on parallel volume rendering applications in which renderings with different parameters are successively repeated over the same dataset. The only reason for intertask interaction is the existence ... 
Graph/hypergraph partitioning models for simultaneous load balancing on computation and data
(Bilkent University, 201812)In the literature, several successful partitioning models and methods have been proposed and used for computational load balancing of irregularly sparse applications on distributedmemory architectures. However, the ... 
High level synthesis based FPGA implementation of Matricized Tensor Times KhatriRao Product to accelerate canonical polyadic decomposition
(Bilkent University, 201910)Tensor factorization has many applications such as network anomaly detection, structural damage detection and music genre classification. Most time consuming part of the CPDALS based tensor factorization is the Matricized ... 
Hybrid parallelization of Stochastic Gradient Descent
(Bilkent University, 202202)The purpose of this study is to investigate the eﬃcient parallelization of the Stochastic Gradient Descent (SGD) algorithm for solving the matrix completion problem on a highperformance computing (HPC) platform in ... 
Improving the performance of similarity joins using graphics processing unit
(Bilkent University, 2012)The similarity join is an important operation in data mining and it is used in many applications from varying domains. A similarity join operator takes one or two sets of data points and outputs pairs of points whose ...