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Comparing Different Approaches for Solving Large Scale Power-Flow Problems With the Newton-Raphson Method

IEEE ACCESS 2021年 9卷 56604-56615页

作者： D'orto, Manolo Sjoblom, Svante Chien, Lung Sheng Axner, Lilit Gong, Jing KTH Royal Inst Technol Sch Elect Engn & Comp Sci PDC Ctr High Performance Comp S-10044 Stockholm Sweden Svenska Kraftnat S-17224 Sundbyberg Sweden NVIDIA Corp Santa Clara CA 95050 USA Uppsala Univ Dept Informat Technol ENCCS S-75105 Uppsala Sweden

This paper focuses on using the Newton-Raphson method to solve the power-fiow problems. Since the most computationally demanding part of the Newton-Raphson method is to solve the linear equations at each iteration, this study investigates different approaches to solve the linear equations on both central processing unit (CPU) and graphical processing unit (GPU). Six different approaches have been developed and evaluated in this paper: two approaches of these run entirely on CPU while other two of these run entirely on GPU, and the remaining two are hybrid approaches that run on both CPU and GPU. All six direct linear solvers use either LU or QR factorization to solve the linear equations. Two different hardware platforms have been used to conduct the experiments. The performance results show that the CPU version with LU factorization gives better performance compared to the GPU version using standard library called cuSOLVER even for the larger power-fiow problems. Moreover, it has been proven that the best performance is achieved using a hybrid method where the Jacobian matrix is assembled on GPU, the preprocessing with a sparse high performance linear solver called KLU is performed on the CPU in the first iteration, and the linear equation is factorized on the GPU and solved on the CPU. Maximum speed up in this study is obtained on the largest case with 25000 buses. The hybrid version shows a speedup factor of 9:6 with a NVIDIA P100 GPU while 13:1 with a NVIDIA V100 GPU in comparison with baseline CPU version on an Intel Xeon Gold 6132 CPU.

关键词： High performance computing Newton method parallel algorithms power engineering computing power-flow direct solver

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Improved MPC algorithms for Edit Distance and Ulam Distance

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IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 2021年第11期32卷 2764-2776页

作者： Boroujeni, Mahdi Ghodsi, Mohammad Seddighin, Saeed Sharif Univ Technol Dept Comp Engn Tehran *** Iran Inst Res Fundamental Sci Sch Comp Sci Tehran *** Iran Toyota Technol Inst Chicago Chicago IL 60637 USA

Edit distance is one of the most fundamental problems in combinatorial optimization to measure the similarity between strings. Ulam distance is a special case of edit distance where no character is allowed to appear more than once in a string. Recent developments have been very fruitful for obtaining fast and parallel algorithms for both edit distance and Ulam distance. In this work, we present an almost optimal MPC (massively parallel computation) algorithm for Ulam distance and improve MPC algorithms for edit distance. Our algorithm for Ulam distance is almost optimal in the sense that (1) the approximation factor of our algorithm is 1 + epsilon, (2) the round complexity of our algorithm is constant, (3) the total memory of our algorithm is almost linear ((O) over tilde (epsilon)(n)), and (4) the overall running time of our algorithm is almost linear which is the best known for Ulam distance. We also improve the work of Hajiaghayi et al. for edit distance in terms of total memory. The best previously known MPC algorithm for edit distance requires (O) over tilde (n(2x))machines when the memory of each machine is bounded by (O) over tilde (n(1-x)). In this work, we improve the number of machines to (O) over tilde (n((9/5x)) while keeping the memory limit intact. Moreover, the round complexity of our algorithm is constant and the total running time of our algorithm is truly subquadratic. However, our improvement comes at the expense of a constant factor in the approximation guarantee of the algorithm. This improvement is inspired by the recent techniques of Boroujeni et al. and Chakraborty et al. for obtaining truly subquadratic time algorithms for edit distance.

关键词： MapReduce parallel algorithms approximation algorithms ulam distance edit distance

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parallel Polynomial Permanent Mod Powers of 2 and Shortest Disjoint Cycles 46

Parallel Polynomial Permanent Mod Powers of 2 and Shortest D...

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46th International Symposium on Mathematical Foundations of Computer Science, MFCS 2021

作者： Datta, Samir Jaiswal, Kishlaya Chennai Mathematical Institute India

ISBN: (纸本)9783959772013

We present a parallel algorithm for permanent mod 2k of a matrix of univariate integer polynomials. It places the problem in ⊕L ⊆ NC2. This extends the techniques of Valiant [26], Braverman, Kulkarni and Roy [3] and Björklund and Husfeldt [2] and yields a (randomized) parallel algorithm for shortest two disjoint paths improving upon the recent (randomized) polynomial time algorithm [2]. We also recognize the disjoint paths problem as a special case of finding disjoint cycles, and present (randomized) parallel algorithms for finding a shortest cycle and shortest two disjoint cycles passing through any given fixed number of vertices or edges. © Samir Datta and Kishlaya Jaiswal;licensed under Creative Commons License CC-BY 4.0 46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021).

关键词： parallel algorithms

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Cloud-Ready Acceleration of Formal Method Techniques for Cyber-Physical Systems

IEEE DESIGN & TEST

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IEEE DESIGN & TEST 2021年第5期38卷 25-34页

作者： Khaled, Mahmoud Zamani, Majid Tech Univ Munich Munich Germany Univ Colorado Comp Sci Dept Boulder CO USA Ludwig Maximilian Univ Munich Munich Germany

Editor's notes: Controller synthesis using formal specifications has shown considerable promise in recent years. However, it is computationally very expensive. This article shows how cloud computing can come to th... 详细信息

关键词： Kernel Cloud computing parallel algorithms Task analysis Acceleration Copper Formal Methods Cyber-Physical Systems Internet of Things High Performance Computing parallel algorithms Cloud Computing OpenCL Message Passing Interface (MPI) GPGPU FPGA

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Examination of Semi-Analytical Solution Methods in the Coarse Operator of Parareal Algorithm for Power System Simulation

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IEEE TRANSACTIONS ON POWER SYSTEMS 2021年第6期36卷 5068-5080页

作者： Park, Byungkwon Sun, Kai Dimitrovski, Aleksandar Liu, Yang Simunovic, Srdjan Oak Ridge Natl Lab Computat Sci & Engn Div Oak Ridge TN 37830 USA Univ Cent Florida Dept ECE Orlando FL 32816 USA Univ Tennessee Dept EECS Knoxville TN 37996 USA

With continuing advances in high-performance parallel computing platforms, parallel algorithms have become powerful tools for development of faster than real-time power system dynamic simulations. In particular, it has been demonstrated in recent years that parallel-in-time (Parareal) algorithms have the potential to achieve such an ambitious goal. The selection of a fast and reasonably accurate coarse operator of the Parareal algorithm is crucial for its effective utilization and performance. This paper examines semi-analytical solution (SAS) methods as the coarse operators of the Parareal algorithm and explores performance of the SAS methods to the standard numerical time integration methods. Two promising time-power series-based SAS methods were considered;Adomian decomposition method and Homotopy analysis method with a windowing approach for improving the convergence. Numerical performance case studies on 10-generator 39-bus system and 327-generator 2383-bus system were performed for these coarse operators over different disturbances, evaluating the number of Parareal iterations, computational time, and stability of convergence. All the coarse operators tested with different scenarios have converged to the same corresponding true solution (if they are convergent) and the SAS methods provide comparable computational speed, while having more stable convergence to the true solution in many cases.

关键词： Synthetic aperture sonar Power system stability Power system dynamics Numerical models Mathematical model Heuristic algorithms Computational modeling High-performance computing parallel algorithms power system dynamic simulations semi-analytical solution methods transient stability

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Design of parallel Algorithm of Transfer Learning based on Weak Classifier 16

Design of Parallel Algorithm of Transfer Learning based on W...

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16th IEEE International Conference on Intelligent Systems and Knowledge Engineering, ISKE 2021

作者： Hui, Zong Guanqun, Tian Qiankun, Zhao Long, Hong Huaiyin Institute of Technology College of Computer Science and Technology Huaian China Nanjing University of Posts and Telecommunications College of Computer Science and Technology Nanjing China

ISBN: (纸本)9781665405539

In the TrAdaBoost method that based on sample transfer learning, weak classifier is the kernel of its design. Aiming at the problem of high time cost for the serial algorithm of weak classifier, a parallel algorithm of weak classifier is designed and applied to the prediction of diabetes in this paper. Experiments are performed on a computer with an 8-core processor, the speedup ratio of the TrAdaBoost algorithm after the parallelization of the weak classifier is 5.14, and the classification accuracy of diabetes prediction is 79%, which means this design can make an auxiliary diagnosis for patients. © 2021 IEEE.

关键词： parallel algorithms

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Multiwindow discrete Gabor transform using parallel lattice structures

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IET SIGNAL PROCESSING 2020年第7期14卷 420-426页

作者： Li, Rui Tao, Liang Keung Kwan, Hon Anhui Sci & Technol Univ Coll Informat & Network Engn 1501 Huangshan Rd Bengbu 233100 Anhui Peoples R China Anhui Univ Sch Comp Sci & Technol 111 Jiulong Rd Hefei 233100 Anhui Peoples R China Univ Windsor Dept Elect & Comp Engn 401 Sunset Ave Windsor ON N9B 3P4 Canada

The multiwindow discrete Gabor transform (M-DGT) is an effective time-frequency analysis tool to analyse time-varying signals containing components with multiple frequencies. In this study, fast block time-recursive methods for computing the M-DGT coefficients of a signal and the reconstruction of the signal from the transform coefficients are presented with steps as listed, respectively, in algorithms 1 and 2, and their implementations using unified parallel lattice structures are also given. The proposed algorithms consisting of algorithms 1 and 2 for respective forward and inverse transforms are compared to (i) those of the existing serial algorithms in terms of computational complexity and time;and (ii) those of the existing parallel algorithms in terms of hardware complexity. The results indicate that the proposed algorithm is fast in computing M-DGT coefficients of a signal and reconstructing the signal with a reduced hardware complexity.

关键词： discrete transforms parallel algorithms computational complexity signal reconstruction time-frequency analysis transforms signal sampling existing serial algorithms computational complexity existing parallel algorithms M-DGT coefficients multiwindow discrete Gabor effective time-frequency analysis tool time-varying signals time-recursive methods transform coefficients unified parallel lattice structures respective forward transforms inverse transforms

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Multi-GPU Design and Performance Evaluation of Homomorphic Encryption on GPU Clusters

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IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 2021年第2期32卷 379-391页

作者： Al Badawi, Ahmad Veeravalli, Bharadwaj Lin, Jie Xiao, Nan Kazuaki, Matsumura Khin Mi Mi, Aung ASTAR Inst Infocomm Res I2R Singapore 138632 Singapore Natl Univ Singapore Dept Elect & Comp Engn Singapore 117576 Singapore Barcelona Supercomp Ctr BSC Barcelona Spain

We present a multi-GPU design, implementation and performance evaluation of the Halevi-Polyakov-Shoup (HPS) variant of the Fan-Vercauteren (FV) levelled Fully Homomorphic Encryption (FHE) scheme. Our design follows a data parallelism approach and uses partitioning methods to distribute the workload in FV primitives evenly across available GPUs. The design is put to address space and runtime requirements of FHE computations. It is also suitable for distributed-memory architectures, and includes efficient GPU-to-GPU data exchange protocols. Moreover, it is user-friendly as user intervention is not required for task decomposition, scheduling or load balancing. We implement and evaluate the performance of our design on two homogeneous and heterogeneous NVIDIA GPU clusters: K80, and a customized P100. We also provide a comparison with a recent shared-memory-based multi-core CPU implementation using two homomorphic circuits as workloads: vector addition and multiplication. Moreover, we use our multi-GPU Levelled-FHE to implement the inference circuit of two Convolutional Neural Networks (CNNs) to perform homomorphically image classification on encrypted images from the MNIST and CIFAR - 10 datasets. Our implementation provides 1 to 3 orders of magnitude speedup compared with the CPU implementation on vector operations. In terms of scalability, our design shows reasonable scalability curves when the GPUs are fully connected.

关键词： Homomorphic encryption parallel algorithms multi-GPU clusters performance evaluation

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A Split Execution Model for SpTRSV

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IEEE TRANSACTIONS ON parallel AND DISTRIBUTED SYSTEMS 2021年第11期32卷 2809-2822页

作者： Ahmad, Najeeb Yilmaz, Buse Unat, Didem Koc Univ Dept Comp Sci & Engn TR-34450 Istanbul Turkey Istinye Univ Dept Comp Sci TR-34010 Istanbul Turkey

Sparse Triangular Solve (SpTRSV) is an important and extensively used kernel in scientific computing. parallelism within SpTRSV depends upon matrix sparsity pattern and, in many cases, is non-uniform from one computational step to the next. In cases where the SpTRSV computational steps have contrasting parallelism characteristics- some steps are more parallel, others more sequential in nature, the performance of an SpTRSV algorithm may be limited by the contrasting parallelism characteristics. In this work, we propose a split-execution model for SpTRSV to automatically divide SpTRSV computation into two sub-SpTRSV systems and an SpMV, such that one of the sub-SpTRSVs has more parallelism than the other. Each sub-SpTRSV is then computed using different SpTRSV algorithms, which are possibly executed on different platforms (CPU or GPU). By analyzing the SpTRSV Directed Acyclic Graph (DAG) and matrix sparsity features, we use a heuristics-based approach to (i) automatically determine the suitability of an SpTRSV for split-execution, (ii) find the appropriate split-point, and (iii) execute SpTRSV in a split fashion using two SpTRSV algorithms while managing any required inter-platform communication. Experimental evaluation of the execution model on two CPU-GPU machines with a matrix dataset of 327 matrices from the SuiteSparse Matrix Collection shows that our approach correctly selects the fastest SpTRSV method (split or unsplit) for 88 percent of matrices on the Intel Xeon Gold (6148) + NVIDIA Tesla V100 and 83 percent on the Intel Core I7 + NVIDIA G1080 Ti platform achieving speedups up to 10x and 6.36x respectively.

关键词： Sparse matrices parallel algorithms Computational modeling Kernel Graphics processing units Fats Phased arrays Sparse triangular solve CPU-GPU computing heterogeneous computing sparse linear systems SpTRSV SpTS

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A novel task scheduling approach for dependent non-preemptive tasks using fuzzy logic

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IET COMPUTERS AND DIGITAL TECHNIQUES 2021年第3期15卷 214-222页

作者： Hassan, Heba E. Nagib, Gihan Ibrahiem, Khaled Hosny Fayoum Univ Fac Engn Al Fayyum Egypt

Multiprocessor task scheduling problem is a pressing problem that affects systems' performance and is still being investigated by the researchers. Finding the optimal schedules is considered to be a computationally hard problem. Recently, researchers have used fuzzy logic in the field of task scheduling to achieve optimal performance, but this area of research is still not well investigated. In addition, there are various scheduling algorithms that used fuzzy logic but most of them are often performed on uniprocessor systems. This article presents a new proposed algorithm in which the priorities of the tasks are derived from the fuzzy logic and bottom level parameter. This approach is designed to find task schedules with optimal or sub-optimal lengths in order to achieve high performance for a multiprocessor environment. With respect to the proposed algorithm, the precedence constraints between the non-preemptive tasks and their execution times are known and described by a directed acyclic graph. The number of processors is fixed, the communication costs are negligible and the processors are homogeneous. The suggested technique is tested and compared with the Prototype Standard Task Graph Set.

关键词： computational complexity directed graphs fuzzy logic multiprocessing systems parallel algorithms processor scheduling

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