Latin Hypercube Sampling and Bootstrapping

Hello!

I am doing a research project using Monte Carlo Simulations with an embedded double bootstrap procedure, using a simple log-normal distribution as the base model. However, because double bootstrapping is a very time and memory consuming procedure, employing a classical Monte Carlo Simulation approach with some 10 000 iterations does not help. Now, the use of Latin Hypercube Sampling has been shown to reduce the number of iterations required for convergence. Accordingly, my question is as follows:

1) What is the difference between bootstrapping and Latin Hypercube Sampling?

2)May I replace the use of the classic Monte Carlo Framework with the Latin Hypercube Sampling framework, and still perform the embedded double bootstrap within the Latin Hypercube scenario?

I would appreciate an answer as soon as possible please! Thanking you in advance:

M.T.