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Details: - Fixed an innocuous bug that manifested when running the testsuite on extremely small matrices with randomization via the "powers of 2 in narrow precision range" option enabled. When the randomization function emits a perfect 0.0 to fill a 1x1 matrix, the testsuite will then compute 0.0/0.0 during the normalization process, which leads to NaN residuals. The solution entails smarter implementaions of randv, randnv, randm, and randnm, each of which will compute the 1-norm of the vector or matrix in question. If the object has a 1-norm of 0.0, the object is re-randomized until the 1-norm is not 0.0. Thanks to Kiran Varaganti for reporting this issue (#413). - Updated the implementation of randm_unb_var1() so that it loops over a call to the randv_unb_var1() implementation directly rather than calling it indirectly via randv(). This was done to avoid the overhead of multiple calls to norm1v() when randomizing the rows/columns of a matrix. - Updated comments. Change-Id: I0e3d65ff97b26afde614da746e17ed33646839d1