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Local and parallel finite element methods based on two-grid discretizations for the unsteady mixed Stokes-Darcy model with the Beavers-Joseph interface condition
In this paper, some local and parallel finite element methods based on two-grid discretizations are provided and studied for the non-stationary...
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Joint Calibrationless Reconstruction and Segmentation of Parallel MRI
The volume estimation of brain regions from MRI data is a key problem in many clinical applications, where the acquisition of data at high spatial...
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FLSGD: free local SGD with parallel synchronization
Synchronous parameters algorithms with data parallelism have been successfully utilized to accelerate the distributed training of deep neural...
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Perfect (Parallel) Broadcast in Constant Expected Rounds via Statistical VSS
We study broadcast protocols in the information-theoretic model under optimal conditions, where the number of corruptions t is at most one-third of...
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Analyzing Parallel Applications for Unnecessary I/O Semantics that Inhibit File System Performance
Scalability and performance of I/O intensive parallel applications are major concerns in modern High Performance Computing (HPC) environments. Almost...
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Parallel grid-based density peak clustering of big trajectory data
With the widespread adoption of data intensive applications such as navigation systems for mobile devices and unmanned vehicles, analyzing trajectory...
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Quantum Annealing to Solve the Unrelated Parallel Machine Scheduling Problem
Quantum computing has emerged in recent years as an alternative to classical computing, which could improve the latter in solving some types of...
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The Impact of Importance-Aware Dataset Partitioning on Data-Parallel Training of Deep Neural Networks
Deep neural networks used for computer vision tasks are typically trained on datasets consisting of thousands of images, called examples. Recent...
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A Reversible Debugger for Imperative Parallel Programs with Contracts
We present a reversible debugger for imperative parallel programs with block structures. A program runs in the runtime of abstract machines executed...
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High-Level Parallel Ant Colony Optimization with Algorithmic Skeletons
Parallel implementations of swarm intelligence algorithms such as the ant colony optimization (ACO) have been widely used to shorten the execution...
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Fast and parallel decomposition of constraint satisfaction problems
Constraint Satisfaction Problems (CSP) are notoriously hard. Consequently, powerful decomposition methods have been developed to overcome this...
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Higher Target Relevance Parallel Machine Translation with Low-Frequency Word Enhancement
Non-autoregressive translation (NAT) has received a surge of interest due to its success in inference speed by predicting all tokens independently...
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Optimization Focused on Parallel Fuzzy Deep Belief Neural Network for Opinion Mining
In this work, we propose a new parallel fuzzy deep belief neural network for sentiment analysis. We have applied several preprocessing tasks to...
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Novel parallel hybrid genetic algorithms on the GPU for the generalized assignment problem
The emergence of GPU-CPU heterogeneous architecture has led to a significant paradigm shift in parallel programming. How to effectively implement...
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A symbiosis between population based incremental learning and LP-relaxation based parallel genetic algorithm for solving integer linear programming models
Solving Integer Linear Programming (ILP) models generally lies in the category of NP-hard problems and finding the optimal answer for large models is...
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Parallel approaches to improve the speed of chaotic-maps-based encryption using GPU
Chaos-based cryptography has become a major interest for providing effective, fast and secure encryption in the recent few years. Chaos-based...
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Round-Preserving Parallel Composition of Probabilistic-Termination Cryptographic Protocols
An important benchmark for multi-party computation protocols (MPC) is their round complexity . For several important MPC tasks, such as broadcast,...
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Effective learning with a personal AI tutor: A case study
Effective learning strategies based on principles like personalization, retrieval practice, and spaced repetition are often challenging to implement...
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Maximum Flows in Parametric Graph Templates
Execution graphs of parallel loop programs exhibit a nested, repeating structure. We show how such graphs that are the result of nested repetition...
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CUDAQuat: new parallel framework for fast computation of quaternion moments for color images applications
Quaternion moments are widely used in several applications, such as image classification, object recognition, and multimedia security. The...
