  Hierarchical Matrix (H-matrix) is an approximation technique which splits a
target dense matrix into multiple submatrices, and where a selected portion of
submatrices are low-rank approximated. The technique substantially reduces both
time and space complexity of dense matrix vector multiplication, and hence has
been applied to numerous practical problems.
  In this paper, we aim to accelerate the H-matrix vector multiplication by
introducing mixed precision computing, where we employ both binary64 (FP64) and
binary32 (FP32) arithmetic operations. We propose three methods to introduce
mixed precision computing to H-matrix vector multiplication, and then evaluate
them in a boundary element method (BEM) analysis. The numerical tests examine
the effects of mixed precision computing, particularly on the required
simulation time and rate of convergence of the iterative (BiCG-STAB) linear
solver. We confirm the effectiveness of the proposed methods.
