  A new general purpose Monte Carlo event generator with self-adapting grid
consisting of simplices is described. In the process of initialization, the
simplex-shaped cells divide into daughter subcells in such a way that: (a) cell
density is biggest in areas where integrand is peaked, (b) cells elongate
themselves along hyperspaces where integrand is enhanced/singular. The grid is
anisotropic, i.e. memory of the axes directions of the primary reference frame
is lost. In particular, the algorithm is capable of dealing with distributions
featuring strong correlation among variables (like ridge along diagonal). The
presented algorithm is complementary to others known and commonly used in the
Monte Carlo event generators. It is, in principle, more effective then any
other one for distributions with very complicated patterns of singularities -
the price to pay is that it is memory-hungry. It is therefore aimed at a small
number of integration dimensions (<10). It should be combined with other
methods for higher dimension. The source code in Fortran77 is available from
http://home.cern.ch/~jadach
