Discuss the various strategies for achieving fine-grained parallelism in concurrent algorithms and applications, such as task parallelism, data parallelism, and speculative parallelism, and their respective advantages and trade-offs in terms of scalability, overhead, and complexity?

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Finegrained parallelism refers to breaking down a computational task into smaller units of work that can be executed concurrently to improve performance Various strategies exist for achieving finegrai... View the full answer