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Related Questions
- What are the key factors that affect the efficiency of parallelization in Bayesian optimization?
- Can Bayesian optimization be parallelized using multi-threading or multi-processing approaches?
- How does the choice of hardware architecture (e.g., CPU, GPU, TPU) impact the performance of Bayesian optimization?
- What is the optimal number of parallel threads or processes for Bayesian optimization, and how does it depend on the problem size?
- Can Bayesian optimization be scaled up using distributed computing frameworks, and if so, what are the benefits and challenges?
- How does the memory requirement for Bayesian optimization impact its parallelization, and what strategies can be used to mitigate memory bottlenecks?
- Can Bayesian optimization be parallelized using specialized hardware accelerators, such as FPGAs or ASICs, and what are the advantages and disadvantages of this approach?
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