Fine Grain Scheduling for Sparse Solver on Manycore Architectures

The emergence of many-cores architectures introduces variations in computation costs, which makes precise cost models hard to realize. Static schedulers based on cost models, like the one used in the sparse direct solver textscPaStiX, are no longer adapted. We describe the dynamic scheduler developed for the super-nodal method of textscPaStiX to correct the imperfections of the static model. The solution presented exploit the elimination tree of the problem to keep the data locality during the execution.

Conference paper