Parallel adaptive algorithms for the approximation of a multi-dimensional integral over an hyper-rectangular region are described. Algorithms with centralized global region collection are compared to algorithms using local region collections. The latter algorithms should result in better scalability since global communication is avoided. Both types of algorithms are compared to quasi-Monte Carlo integration. Tests are performed using Genz's test functions and speed-up results are given.