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Features include mixed precision training, single-GPU, multi-GPU, and multi-node training as well as custom model parallelism. The DeepSpeed source code is licensed under MIT License and available on GitHub. [5] The team claimed to achieve up to a 6.2x throughput improvement, 2.8x faster convergence, and 4.6x less communication. [6]
All local search algorithms use a function that evaluates the quality of assignment, for example the number of constraints violated by the assignment. This amount is called the cost of the assignment. The aim of local search is that of finding an assignment of minimal cost, which is a solution if any exists. Point A is not a solution, but no ...
Local search is an anytime algorithm; it can return a valid solution even if it's interrupted at any time after finding the first valid solution. Local search is typically an approximation or incomplete algorithm because the search may stop even if the current best solution found is not optimal. This can happen even if termination happens ...
Variable neighborhood search (VNS), [1] proposed by Mladenović & Hansen in 1997, [2] is a metaheuristic method for solving a set of combinatorial optimization and global optimization problems. It explores distant neighborhoods of the current incumbent solution, and moves from there to a new one if and only if an improvement was made.
The greedy randomized adaptive search procedure (also known as GRASP) is a metaheuristic algorithm commonly applied to combinatorial optimization problems. GRASP typically consists of iterations made up from successive constructions of a greedy randomized solution and subsequent iterative improvements of it through a local search . [ 1 ]
Location search optimization (LSO) [1] is the process of improving the visibility of a website or a webpage by reaching more readers through location-enabled devices. The LSO is a new step in a line of web optimization methods, which began with search engine optimization (SEO) to boost search rankings, and social media optimization (SMO) to make content more sharable.
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Iterated Local Search [1] [2] (ILS) is a term in applied mathematics and computer science defining a modification of local search or hill climbing methods for solving discrete optimization problems. Local search methods can get stuck in a local minimum, where no improving neighbors are available. A simple modification consists of iterating ...