title: Fastest save and load options for a numpy array
body: <p>I have a script that generates two-dimensional <code>numpy</code> arrays with <code>dtype=float</code> and shape on the order of <code>(1e3, 1e6)</code>.  Right now I'm using <code>np.save</code> and <code>np.load</code> to perform IO operations with the arrays.  However, these functions take several seconds for each array.  Are there faster methods for saving and loading the entire arrays (i.e., without making assumptions about their contents and reducing them)?  I'm open to converting the arrays to another type before saving as long as the data are retained exactly.</p>