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29th Australasian Conference on Information Security and Privacy (ACISP)

作者： Chen, Chao Zhang, Fangguo Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou 510006 Peoples R China Guangdong Prov Key Lab Informat Secur Technol Guangzhou 510006 Peoples R China

ISBN: (纸本)9789819750245;9789819750252

Pairings are useful tools in cryptography and efficient implementations play a critical role in their usage, where Miller's algorithms are the main method for all pairings. As an alternative approach, elliptic nets were first employed to evaluate Tate pairings and generalized to the hyperelliptic nets for Tate pairings on hyperelliptic curves. In this work, for hyperelliptic pairings derived from rational functions, we establish the unitary formulae in terms of hyperelliptic nets. Afterwards, for genus-2 hyperelliptic pairings, we construct a parallel Double-and-Add algorithm on the minimal block. In particular, all terms in new blocks, having irrelevant formulae on current blocks, can be evaluated with 12 processors in parallel, thus the explicit loop cost reduces to 4M' (multiplications in extension fields) with 276 parallel processors. As an additional merit, Double and Double-Add algorithms invoke analogous operations such that our method avoids extra additions in Miller's algorithms.

关键词： Hyperelliptic Nets Hyperelliptic Curves Tate Pairings Ate Pairings parallel algorithms

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parallel algorithms for Solving Mass Transfer Equations in the "Fracture Set – Matrix System" 10th

Parallel Algorithms for Solving Mass Transfer Equations in...

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10th Russian Supercomputing Days Conference, RuSCDays 2024

作者： Uzyanbaev, Ravil Poveshchenko, Yury Podryga, Viktoriia Polyakov, Sergey Bobreneva, Yuliya Rahimly, Parvin Gubaydullin, Irek Institute of Petrochemistry and Catalysis of the Ufa Federal Research Center of the Russian Academy of Sciences Ufa Russia Ufa State Petroleum Technological University Ufa Russia Keldysh Institute of Applied Mathematics of the Russian Academy of Sciences Moscow Russia MADI 64 Leningradskii Pr. Moscow125319 Russia

ISBN: (纸本)9783031784583

A mathematical model is developed and numerical modeling is performed to solve a scientific and industrial problem in the field of studying mass transfer processes in the "fracture set - matrix" system in a carbonate reservoir. The model is presented in a two-dimensional formulation, which is characterized by the presence of two subsystems with different sets of filtration parameters. The IMPES (implicit in pressure and explicit in saturation) and IMPIS (implicit in pressure and saturation) integration methods are used to numerically solve the system. An implicit finite-difference scheme is constructed for equations regarding pressure, when solving it, the saturations are set as fixed. Based on the solution of this scheme, the pressure in the fracture system and matrix is determined, and then the system is solved with respect to saturations. The explicit and implicit finite-difference schemes are considered to determine saturations. For a task on an industrial scale, significant resources are required to solve it. A parallel algorithm is proposed to speed up calculations with involves decomposing the computational domain into a lattice of domains of equal cardinality. Block-parallel processing is used when solving the implicit scheme. A series of computational experiments are performed to test the approach for both IMPES and IMPIS methods. Based on the obtained calculations, a comparative analysis of explicit and implicit methods for calculating equations for saturations is carried out. The calculation results confirm the effectiveness of the proposed fully implicit parallel algorithm. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： parallel algorithms

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parallel algorithms for Equilevel Predicates 24

Parallel Algorithms for Equilevel Predicates

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25th International Conference on Distributed Computing and Networking, ICDCN 2024

作者： Garg, Vijay K Streit, Robert P The University of Texas at Austin AustinTX United States

ISBN: (纸本)9798400716737

We define a new class of predicates called equilevel predicates on a distributive lattice which eases the analysis of parallel algorithms. Many combinatorial problems such as the vertex cover problem, the bipartite matching problem, and the minimum spanning tree problem can be modeled as detecting an equilevel predicate. The problem of detecting an equilevel problem is NP-complete, but equilevel predicates with the helpful property can be detected in polynomial time in an online manner. An equilevel predicate has the helpful property with a polynomial time algorithm if the algorithm can return a nonempty set of indices such that advancing on any of them can be used to detect the predicate. Furthermore, the refined independently helpful property allows online parallel detection of such predicates in NC. When the independently helpful property holds, advancing on all the specified indices in parallel can be used to detect the predicate in polylogarithmic time. We also define a special class of equilevel predicates called solitary predicates. Unless NP= RP, this class of predicate also does not admit efficient algorithms. Earlier work has shown that solitary predicates with the efficient advancement can be detected in polynomial time. We introduce two properties called the antimonotone advancement and the efficient rejection which yield the detection of solitary predicates in NC. Finally, we identify the minimum spanning tree, the shortest path, and the conjunctive predicate detection as problems satisfying such properties, giving alternative certifications of their NC memberships as a result. © 2024 Owner/Author.

关键词： parallel algorithms

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parallel algorithms Align with Neural Execution 2

Parallel Algorithms Align with Neural Execution

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2nd Learning on Graphs Conference

作者： Engelmayer, Valerie Georgiev, Dobrik Velickovic, Petar Univ Augsburg Augsburg Germany Univ Cambridge Cambridge England Google DeepMind London England

Neural algorithmic reasoners are parallel processors. Teaching them sequential algorithms contradicts this nature, rendering a significant share of their computations redundant. parallel algorithms however may exploit their full computational power, therefore requiring fewer layers to be executed. This drastically reduces training times, as we observe when comparing parallel implementations of searching, sorting and finding strongly connected components to their sequential counterparts on the CLRS framework. Additionally, parallel versions achieve (often strongly) superior predictive performance.

关键词： parallel algorithms

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High-Performance Computing and parallel algorithms for Urban Water Demand Forecasting

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algorithms 2025年第4期18卷 182-182页

作者： Myllis, Georgios Tsimpiris, Alkiviadis Aggelopoulos, Stamatios Vrana, Vasiliki G. Int Hellen Univ Dept Comp Informat & Telecommun Engn Serres 62124 Greece Int Hellen Univ Dept Agr Thessaloniki 57001 Greece Int Hellen Univ Dept Business Adm Serres 62124 Greece

This paper explores the application of parallel algorithms and high-performance computing (HPC) in the processing and forecasting of large-scale water demand data. Building upon prior work, which identified the need for more robust and scalable forecasting models, this study integrates parallel computing frameworks such as Apache Spark for distributed data processing, Message Passing Interface (MPI) for fine-grained parallel execution, and CUDA-enabled GPUs for deep learning acceleration. These advancements significantly improve model training and deployment speed, enabling near-real-time data processing. Apache Spark's in-memory computing and distributed data handling optimize data preprocessing and model execution, while MPI provides enhanced control over custom parallel algorithms, ensuring high performance in complex simulations. By leveraging these techniques, urban water utilities can implement scalable, efficient, and reliable forecasting solutions critical for sustainable water resource management in increasingly complex environments. Additionally, expanding these models to larger datasets and diverse regional contexts will be essential for validating their robustness and applicability in different urban settings. Addressing these challenges will help bridge the gap between theoretical advancements and practical implementation, ensuring that HPC-driven forecasting models provide actionable insights for real-world water management decision-making.

关键词： High-Performance Computing (HPC) parallel algorithms water demand forecasting Apache Spark Message Passing Interface (MPI) machine learning time-series analysis real-time data processing urban water management computational efficiency deep learning models data imputation scalability anomaly detection distributed computing frameworks

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parallel algorithms for Computing Jaccard Weights on Graphs using Linear Algebra

Parallel Algorithms for Computing Jaccard Weights on Graphs ...

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IEEE High Performance Extreme Computing Virtual Conference (HPEC)

作者： Hassani, Elaheh Hussain, Md Taufique Azad, Ariful Indiana Univ Bloomington IN 47405 USA

ISBN: (纸本)9798350308600

Jaccard similarity between a pair of vertices in a graph measures the relative overlap among their adjacent vertices. This metric is used to estimate the strength of existing edges and predict new edges between pairs of disconnected vertices. Computing Jaccard similarity for all pairs of vertices or for all edges is computationally expensive. Existing sequential and parallel algorithms are either too slow or do not scale well for large scale graphs. We present a shared-memory parallel algorithm for computing Jaccard weights. Our algorithm relies on sparse linear algebraic operations that utilize masking, semirings, vector iterators, and other GraphBLAS features for performance. Our implementation, albeit simple, outperforms recent state-of-the-art implementations by a factor of up to 20x and exhibits an average speedup of 9x.

关键词： parallel algorithms

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parallel algorithms for Simulation of the Suspension Transport in Coastal Systems Based on the Explicit-Implicit and Splitting Schemes 17th

Parallel Algorithms for Simulation of the Suspension Tran...

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17th International Scientific Conference on parallel Computational Technologies, PCT 2023

作者： Sukhinov, A.I. Chistyakov, A.E. Sidoryakina, V.V. Kuznetsova, I. Yu. Atayan, A.M. Porksheyan, M.V. Don State Technical University Rostov-on-Don Russia Southern Federal University Rostov-on-Don Russia

ISBN: (纸本)9783031388637

We consider two difference schemes that describe the convective-diffusion transfer and settling of multifractional suspensions in coastal systems. The first is based on an explicit-implicit scheme with reduced cost of arithmetic operations. This difference scheme uses an explicit approximation of the diffusion-convection operator (on the lower time layer) along the horizontal directions and an implicit approximation along the vertical direction. We determine the admissible values of the time step for this scheme from the conditions of monotonicity, solvability, and stability. We deem appropriate the use of this scheme, which naturally leads to a parallel algorithm, on grids having a relatively moderate number of nodes along each of the indicated horizontal directions, up to several hundred. The admissible value of the time step in this case is in the interval from s to 1 s. The second is an additive scheme obtained by splitting the original spatial three-dimensional problem into a chain of two-dimensional ones in the horizontal directions and a one-dimensional problem in the vertical direction of the task. In this case, the allowable time step can be increased to several hundred seconds. We consider in detail the parallel implementation, based on the decomposition of the grid domain, of the set of two-dimensional diffusion-convection problems included in the chain. The speedup of the algorithm was estimated on the K60 computer cluster, installed at the Keldysh Institute of Applied Mathematics (Russian Academy of Sciences). © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： parallel algorithms

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Linear parallel algorithms to compute strong and branching bisimilarity

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SOFTWARE AND SYSTEMS MODELING 2023年第2期22卷 521-545页

作者： Martens, Jan Groote, Jan Friso van den Haak, Lars B. Hijma, Pieter Wijs, Anton Eindhoven Univ Technol Groene Loper 5 NL-5612 AE Eindhoven Netherlands Vrije Univ Amsterdam Boelelaan 1105 NL-1081 HV Amsterdam Netherlands

We present the first parallel algorithms that decide strong and branching bisimilarity in linear time. More precisely, if a transition system has n states, m transitions and |Act| action labels, we introduce an algorithm that decides strong bisimilarity in O(n + |Act|) time on max(n, m) processors and an algorithm that decides branching bisimilarity in O(n + |Act|) time using up to max(n(2), m, |Act|n) processors.

关键词： Strong bisimulation Branching bisimulation RCPP parallel algorithms PRAM

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Distributed-Memory parallel algorithms for Sparse Matrix and Sparse Tall-and-Skinny Matrix Multiplication 24

Distributed-Memory Parallel Algorithms for Sparse Matrix and...

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2024 International Conference for High Performance Computing, Networking, Storage and Analysis

作者： Ranawaka, Isuru Hussain, Md Taufique Block, Charles Gerogiannis, Gerasimos Torrellas, Josep Azad, Ariful Indiana Univ Bloomington IN 47405 USA Univ Illinois Champaign IL USA

ISBN: (数字)9798350352917

ISBN: (纸本)9798350352924;9798350352917

We consider a sparse matrix-matrix multiplication (SpGEMM) setting where one matrix is square and the other is tall and skinny. This special variant, TS-SpGEMM, has important applications in multi-source breadth-first search, influence maximization, sparse graph embedding, and algebraic multi-grid solvers. Unfortunately, popular distributed algorithms like sparse SUMMA deliver suboptimal performance for TS-SpGEMM. To address this limitation, we develop a novel distributed-memory algorithm tailored for TS-SpGEMM. Our approach employs customized 1D partitioning for all matrices involved and leverages sparsity-aware tiling for efficient data transfers. In addition, it minimizes communication overhead by incorporating both local and remote computations. On average, our TS-SpGEMM algorithm attains 5x performance gains over 2D and 3D SUMMA. Furthermore, we use our algorithm to implement multi-source breadth-first search and sparse graph embedding algorithms and demonstrate their scalability up to 512 Nodes (or 65,536 cores) on NERSC Perlmutter.

关键词： Three-dimensional displays Shape Scalability Performance gain Data transfer Partitioning algorithms Sparse matrices Distributed algorithms parallel algorithms Optimization

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Practical parallel algorithms for Near-Optimal Densest Subgraphs on Massive Graphs

Practical Parallel Algorithms for Near-Optimal Densest Subgr...

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Symposium on Algorithm Engineering and Experiments (ALENEX)

作者： Sukprasert, Pattara Liu, Quanquan C. Dhulipala, Laxman Shun, Julian Databricks San Francisco CA 94105 USA Northwestern Univ Evanston IL 60208 USA Univ Calif Berkeley Simons Inst Berkeley CA USA Univ Maryland College Pk MD 20742 USA MIT CSAIL 77 Massachusetts Ave Cambridge MA 02139 USA

ISBN: (纸本)9781611977929

The densest subgraph problem has received significant attention, both in theory and in practice, due to its applications in problems such as community detection, social network analysis, and spam detection. Due to the high cost of obtaining exact solutions, much attention has focused on designing approximate densest subgraph algorithms. However, existing approaches are not able to scale to massive graphs with billions of edges. In this paper, we introduce a new framework that combines approximate densest subgraph algorithms with a pruning optimization. We design new parallel variants of the state-of-the-art sequential Greedy++ algorithm, and plug it into our framework in conjunction with a parallel pruning technique based on k-core decomposition to obtain parallel (1+epsilon)-approximate densest subgraph algorithms. On a single thread, our algorithms achieve 2.6-34x speedup over Greedy++, and obtain up to 22.37x self-relative parallel speedup on a 30core machine with two-way hyper-threading. Compared with the state-of-the-art parallel algorithm by Harb et al. [NeurIPS'22], we achieve up to a 114x speedup on the same machine. Finally, against the recent sequential algorithm of Xu et al. [PACMMOD'23], we achieve up to a 25.9x speedup. The scalability of our algorithms enables us to obtain near-optimal density statistics on the hyperlink2012 (with roughly 113 billion edges) and clueweb (with roughly 37 billion edges) graphs for the first time in the literature.

关键词： parallel algorithms

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