OMI4papps: Optimisation, Modelling and Implementation for Highly Parallel Applications

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 which 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. 1 Performance Modelling Using the Apex-MAP Benchmark A simple synthetic benchmark with tunable hardware independent parameters that mimics the behaviour of typical scientific applications is very useful for the evaluation of new hardware platforms for a certain job mix. Mapping application performance data measured on a production system to specific parameter combinations of the synthetic benchmark allows to model the performance of a wide spectrum of applications with a simple approach. Volker Weinberg · Matthias Brehm · Iris Christadler Leibniz-Rechenzentrum der Bayerischen Akademie der Wissenschaften, Boltzmannstr. 1, 85748 Garching bei München, Germany e-mail: {volker.weinberg, matthias.brehm,iris.christadler}@lrz.de