We study preconditioning techniques used in conjunction with the conjugate gradient method for solving multi-length-scale symmetric positive definite linear systems originating from the quantum Monte Carlo simulation ...We study preconditioning techniques used in conjunction with the conjugate gradient method for solving multi-length-scale symmetric positive definite linear systems originating from the quantum Monte Carlo simulation of electron interaction of correlated materials.Existing preconditioning techniques are not designed to be adaptive to varying numerical properties of the multi-length-scale systems.In this paper, we propose a hybrid incomplete Cholesky(HIC) preconditioner and demonstrate its adaptivity to the multi-length-scale systems.In addition,we propose an extension of the compressed sparse column with row access(CSCR) sparse matrix storage format to efficiently accommodate the data access pattern to compute the HIC preconditioner.We show that for moderately correlated materials,the HIC preconditioner achieves the optimal linear scaling of the simulation.The development of a linear-scaling preconditioner for strongly correlated materials remains an open topic.展开更多
基金supported by the National Natural Science Foundation of China(6117030961202098+2 种基金91130024)the Key Project of Development Foundation of Science and Technology of CAEP(2011A0202012: 2012A0202008)the Foundation of National Key Laboratory of Computational Physics
基金supported in part by the US National Science Foundation grant 0611548in part by the US Department of Energy grant DE-FC02-06ER25793
文摘We study preconditioning techniques used in conjunction with the conjugate gradient method for solving multi-length-scale symmetric positive definite linear systems originating from the quantum Monte Carlo simulation of electron interaction of correlated materials.Existing preconditioning techniques are not designed to be adaptive to varying numerical properties of the multi-length-scale systems.In this paper, we propose a hybrid incomplete Cholesky(HIC) preconditioner and demonstrate its adaptivity to the multi-length-scale systems.In addition,we propose an extension of the compressed sparse column with row access(CSCR) sparse matrix storage format to efficiently accommodate the data access pattern to compute the HIC preconditioner.We show that for moderately correlated materials,the HIC preconditioner achieves the optimal linear scaling of the simulation.The development of a linear-scaling preconditioner for strongly correlated materials remains an open topic.
