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A computational algorithm that uses repeated random sampling to obtain numerical results.

Algorithms to process graphs, such as finding the shortest path, with parallelism to increase efficiency.

A graphics rendering technique that simulates the physical behavior of light to produce high-quality images, parallelized to improve speed.

A programming model for processing large data sets with a parallel, distributed algorithm on a cluster.

A form of simulation where the state of the system changes at discrete points in simulated time.

A bridging model for designing parallel algorithms that involves a sequence of supersteps.

An algorithm that calculates all the prefixes of a binary operation in parallel.

Parallel algorithms to search for an element in a data structure simultaneously.

A simulation of a dynamical system of particles, usually under the influence of physical forces, such as gravity.

Parallel algorithms to order elements in a list or array simultaneously.

A type of decentralized distributed system that provides a lookup service similar to a hash table.

A computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality.

An optimization heuristic that mimics the process of natural selection.

An iterative method for optimizing an objective function with suitable smoothness properties.

A numerical method for solving problems in engineering and mathematical physics that can be parallelized for efficiency.

A probabilistic technique for solving computational problems that can be reduced to finding good paths through graphs.

A method for solving complex problems by breaking them down into simpler subproblems.

A mathematical transform that decomposes a function of time (a signal) into its constituent frequencies.

Parallel training of deep learning models consisting of multiple layers for feature extraction and classification.