  This article reports on first results of the KONWIHR-II project OMI4papps at
the Leibniz Supercomputing Centre (LRZ). The first part describes Apex-MAP, a
tunable synthetic benchmark designed to simulate the performance of typical
scientific applications. Apex-MAP mimics common memory access patterns and
different computational intensity of scientific codes. An approach for
modelling LRZ's application mix is given whichh makes use of performance
counter measurements of real applications running on "HLRB II", an SGI Altix
system based on 9728 Intel Montecito dual-cores.
  The second part will show how the Apex-MAP benchmark could be used to
simulate the performance of two mathematical kernels frequently used in
scientific applications: a dense matrix-matrix multiplication and a sparse
matrix-vector multiplication. The performance of both kernels has been
intensively studied on x86 cores and hardware accelerators. We will compare the
predicted performance with measured data to validate our Apex-MAP approach.
