We propose a new SVD algorithm based on the split-and-merge strategy, which possesses an embarrassingly parallel structure and thus can be efficiently implemented on a distributed or multicore machine. The new algorithm can also be implemented in serial for online eigen-analysis. The new algorithm is particularly suitable for big data problems: its embarrassingly parallel structure renders it usable for feature screening, while this has been beyond the ability of the existing parallel SVD algorithms.