Modelling the runtime of the gaussian computational chemistry application and assessing the impacts of microarchitectural variations

This paper explores the use of a simple linear performance model, that determines execution time based instruction and cache miss counts, for describing the behaviour of two-electron integral evaluation algorithm in the Gaussian computational chemistry package. Four different microarchitecture platforms are considered with a total of seven individual microprocessors. Both Hartree-Fock and hybrid Hartree-Fock/Density Functional Theory electronic structure methods are assessed. In most cases the model is found to be accurate to within 3%. Least agreement is for an Athlon64 system (ranging from 1.8% to 6.5%) and a periodic boundary computation on an Opteron where errors of up to 6.8% are observed. These errors arise as the model does not account for the intricacies of out-of-order execution, on-chip write-back buffers and prefetch techniques that modern microprocessors implement. The parameters from the linear performance model are combined with instruction and cache miss counts obtained from functional cache simulation to predict the effect of cache modification on total execution time. Variations in level 1 and 2 linesize and level 2 total size are considered, we find there is some benefit if linesizes are increased (L1: 8%, L2: 4%). Increasing the level 2 cache size is also predicted to be beneficial, although the cache blocking approach already implemented in the Gaussian integral evaluation code was found to be working well.