Parallel AlgorithmsData PartitioningCandidate SetsAssociation rule discovery techniques have gradually been adapt-ed to parallel systems in order to take advantage of the higher speed and greater storage capacit
Practical, Theoretical or Mathematical/ distributed processing fast Fourier transforms interpolation mathematics computing parallel algorithms polynomials/ parallel algorithms algebraic operations polynomial equations distributed memory multicomputer interpolation fast Fourier transforms Toeplitz linear systems/ C4240 Progr...
This parameter applies to parallel execution in exclusive mode as well as in a Real Application Clusters environment. PARALLEL_THREADS_PER_CPU specifies the default degree of parallelism for the instance and determines the parallel adaptive and load balancing algorithms. The parameter describes the num...
Neurodynamic optimization algorithms, which have demonstrated strong convergence and robust performance in fields such as pattern recognition [42,43] and automation [44,45] in recent years, may have potential advantages in disease prediction. Thus, we proposed a novel neurodynamic learning design formula...
2.4 Algorithms ealization heGPPGaworks sshowninFig.2. 2.5 ConvergenceAnalysisofGPPGA hem inre sonsofinducingtheprem tureof — 9 4 — C EN ai-yi g (陈海英) etalm / rid-basedpseud -parallel e etic lg rithna d ts 11licati Fig.2 FlowchartofGPPGA commonGAareasfollows. !Randominitializat...
3. Obstacle-Aware Parallel Legalization Algorithms In this section, we illustrate poAbacus and poTetris. Pseudocode 1 describes the basic Abacus algorithm that operates without considering obstacles. The cells are first ordered according to the x-coordinate (increasing fashion) (line 1). The ...
algorithms Article A Novel Parallel Auto-Encoder Framework for Multi-Scale Data in Civil Structural Health Monitoring Ruhua Wang 1,*, Ling Li 1 and Jun Li 2 1 School of Electrical Engineering, Computing and Mathematics Science, Curtin University, Kent Street, Bentley, WA 6102, Australia; L.Li...
The neural architectures could be automatically designed by algorithms with better performance than the ones designed by human experts. Support Ultra-Large-Scale Training of Deep Neural Networks PaddlePaddle has made breakthroughs in ultra-large-scale deep neural networks training. It launched the world'...
Such algorithms are easy to implement but on the negative side, the intermediate nodes leave the output channel unused until the whole package is received, which loses considerable time. In this method, the overall multi-hop transfer time relates to the number of hops, which in turn is ...
conform to the kinematic con- The A* algorithm is one of the most commonly used path planning algorithms; it is a heuristic graph search algorithm that combines the principles of Dijkstra's algorithm with heuristic functions, enabling it to find the shortest path in directed or weighted graphs....