Výsledky vyhľadávania - one-sided factorization algorithms

One-sided Dense Matrix Factorizations on a Multicore with Multiple GPU Accelerators Autor Yamazaki, Ichitaro, Tomov, Stanimire, Dongarra, Jack

“… In this paper, we propose two extensions of both right-looking (LU and QR) and left-looking (Cholesky) one-sided factorization algorithms to utilize the computing power of current heterogeneous architectures…”
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Adaptive block size for dense QR factorization in hybrid CPU–GPU systems via statistical modeling Autor Chen, Ray-Bing, Tsai, Yaohung M., Wang, Weichung

“…? We investigate this topic by proposing a dense QR factorization algorithm with adaptive block sizes on a hybrid system that contains a central processing unit (CPU…”
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Hierarchical DAG Scheduling for Hybrid Distributed Systems Autor Wei Wu, Bouteiller, Aurelien, Bosilca, George, Faverge, Mathieu, Dongarra, Jack

“… and the expression of algorithm parallelism, resulting in sub-optimal effective performance. Task-based programming paradigms have the capability to alleviate some of the programming challenges on distributed hybrid many-core architectures…”
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Separation of the Factorization Norm and Randomized Communication Complexity Autor Cheung, Tsun-Ming, Hatami, Hamed, Hosseini, Kaave, Shirley, Morgan

“…In an influential paper, Linial and Shraibman (STOC '07) introduced the factorization norm as a powerful tool for proving lower bounds against randomized and quantum communication complexities…”
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Rounding error and perturbation bounds for the symplectic QR factorization Autor Singer, Sanja, Singer, Saša

“…To compute the eigenvalues of a skew-symmetric matrix A, we can use a one-sided Jacobi-like algorithm to enhance accuracy…”
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Comparative study of one-sided factorizations with multiple software packages on multi-core hardware Autor Agullo, Emmanuel, Hadri, Bilel, Ltaief, Hatem, Dongarrra, Jack

“…), and against equivalent commercial software offerings (MKL, ESSL and PESSL). Our experiments were conducted on one-sided linear algebra factorizations (LU, QR and Cholesky…”
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New Fast and Accurate Jacobi SVD Algorithm. II Autor DRMAC, Zlatko, VESELIC, Kresimir

“…This paper presents a new one-sided Jacobi SVD algorithm for triangular matrices computed by revealing QR factorizations…”
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Constructing Strong Linearizations of Matrix Polynomials Expressed in Chebyshev Bases Autor Lawrence, Piers W., Pérez, Javier

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Co-clustering over multiple dynamic data streams based on non-negative matrix factorization Autor Sang, Chun-Yan, Sun, Di-Hua

“… Most of the early work in this area focused on one-sided clustering, i.e., clustering data streams based on feature correlation…”
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Soft error resilient QR factorization for hybrid system with GPGPU Autor Du, Peng, Luszczek, Piotr, Tomov, Stan, Dongarra, Jack

“… ► Performance impact to the baseline MAGMA QR implementation is low. ► Similar methods can be applied to other one-sided factorization like Cholesky and LU factorization…”
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Two-dimensional data partitioning for non-negative matrix tri-factorization Autor Yan, Jiaxing, Liu, Hai, Lei, Zhiqi, Rao, Yanghui, Liu, Guan, Xie, Haoran, Tao, Xiaohui, Wang, Fu Lee

“… Unlike Non-negative Matrix Factorization (NMF) methods applicable to one-sided clustering only, NMTF introduces an additional factor matrix and uses the inherent duality of data to realize the mutual promotion of sample clustering and feature…”
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On efficient factorization of standard fuzzy concept lattices and attribute-oriented fuzzy concept lattices Autor Konecny, Jan

“… Secondly, we scale the input data in such a way that the factor lattice can be computed as a one-sided fuzzy-crisp concept lattice…”
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Multi-threading and one-sided communication in parallel LU factorization Autor Husbands, Parry, Yelick, Katherine

“…Dense LU factorization has a high ratio of computation to communication and, as evidenced by the High Performance Linpack (HPL…”
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Accelerating the SVD bi-diagonalization of a batch of small matrices using GPUs Autor Dong, Tingxing, Haidar, Azzam, Tomov, Stanimire, Dongarra, Jack

“…•A batched BLAS design based on device function and big-tile setting was proposed on the GPU.•The batched BLAS approach is used to optimize solving the batched…”
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Robust collaborative clustering approach with adaptive local structure learning Autor Tang, Jiayi, Feng, Hui

“…Different from one-sided clustering technique based on sample similarity, collaborative clustering captures the sample clustering structure and feature clustering structure by mining the duality…”
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Multi-view anchor graph regularization induced unbiased learning for positive and unlabeled problem Autor Zhao, Jie, Li, Xiao, Xu, Yitian, Yuan, Min

“…) problem, where negative label information is absent. Most semi-supervised algorithms struggle to effectively address PU problems, and a universal model for multi-view positive and unlabeled (PU…”
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OvNMTF Algorithm: an Overlapping Non-Negative Matrix Tri-Factorization for Coclustering Autor de Freitas, Waldyr L., Peres, Sarajane M., Freire, Valdinei, Brunialti, Lucas Fernandes

“…Coclustering algorithms are an alternative to classic one-sided clustering algorithms…”
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One-sided Matrix Completion from Two Observations Per Row Autor Cao, Steven, Liang, Percy, Valiant, Gregory

“…? We study one such problem setting, that of "one-sided" matrix completion, where our goal is to recover the right singular vectors of \(X…”
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Extremes of Markov-additive Processes with One-sided Jumps, with Queueing Applications Autor Dieker, A. B., Mandjes, M.

“…Through Laplace transforms, we study the extremes of a continuous-time Markov-additive process with one-sided jumps and a finite-state background Markovian state-space, jointly with the epoch at which the extreme is ‘attained…”
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W-Cycle SVD: A Multilevel Algorithm for Batched SVD on GPUs Autor Xiao, Junmin, Pang, Yunfei, Xue, Qing, Shui, Chaoyang, Meng, Ke, Ma, Hui, Li, Mingyi, Zhang, Xiaoyang, Tan, Guangming

“… In real-world applications, the computational bottleneck of matrix factorization is on small matrices, and many GPU-accelerated batched SVD algorithms have been developed recently for higher performance…”
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