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We introduce an object-oriented framework that scales across nodes on Graphics Processing Unit (GPU) clusters yet shields users from the underlying complexities of a distributed optimization algorithm, allowing them to easily implement custom Monte Carlo routines (e.g. permutation testing, bootstrapping, etc.).
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