• Scope (Distributed Computing): Implemented a programme to vectorise, then, parallelise a plain code for the Ant Colony Optimisation algorithm.
• Case: 8 agents were used to solve the Traveling Salesman Problem for up to 8000 cities.
• The package used: Python (NumPy, Multiprocessing).
• Used built-in NumPy methods (e.g. np.argmax) for vectorisation.
• Used a Queue object to parallelise the workload on 8 processes.
• Results: achieved an average performance speedup of around 108.
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Distributed Computing project: Implemented a programme to vectorise, then, parallelise a plain code for the Ant Colony Optimisation algorithm.
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