APDCM 2018 Keynote

摘要

Mixed integer programming (MIP) problem is a general form to model combinatorial optimization problems and has many industrial applications. The performance of MIP solvers, software packages to solve MIPs, has improved tremendously in the last two decades and these solvers have been used to solve many real-word problems. However, against the backdrop of modern computer technology, parallelization is of pivotal importance. In this way, ParaSCIP, which uses an academic code SCIP as base MIP solver, and ParaXpress, which uses the commercial MIP solver Xpress, are the most successful parallel MIP solver in terms of solving previously unsolvable instances from the well-known benchmark instance set MIPLIB by using supercomputers. ParaSCIP has solved two instances from MIPLIB2003 and 12 from MIPLIB2010 for the first time to optimality by using up to 80,000 cores of supercomputers and ParaXpress has solved two open instances from MIPLIB2010. ParaSCIP and ParaXpress have been developed by using the Ubiquity Generator (UG) framework, which is a general software package to parallelize any state-of-the-art branch-and-bound based solver. Moreover, UG is being used to parallelize PIPSSBB, a solver for stochastic MIPs. In this talk, we will introduce and show the ground design of UG framework and UG Synthesizer (UGS), which is a new framework to flexibly realize any combinations of algorithm portfolios and racing to solve MIPs on a distributed computing environment. They can instantiate a massively parallel MIP solver with the potential to harness over a million CPU cores to solve a single MIP on supercomputers.