How pre-multicore methods and algorithms perform in multicore era

Many classical methods and algorithms developed when single-core CPUs dominated the parallel computing landscape, are still widely used in the changed multicore world. Two prominent examples are load balancing, which has been one of the main techniques for minimization of the computation time of parallel applications since the beginning of parallel computing, and model-based power/energy measurement techniques using performance events. In this paper, we show that in the multicore era, load balancing is no longer synonymous to optimization and present recent methods and algorithms for optimization of parallel applications for performance and energy on modern HPC platforms, which do not rely on load balancing and often return imbalanced but optimal solutions.

We also show that some fundamental assumptions about performance events, which have to be true for the model-based power/energy measurement tools to be accurate, are increasingly difficult to satisfy as the number of CPU cores increases. Therefore, energy-aware computing methods relying on these tools will be increasingly difficult to verify.