Hello Andrew, my understanding is that the ILOG claim of >= 1.7 times faster for multithreading is on multicore CPUs. I suppose the majority of PCs nowadays has 2 to 4 cores.
A much more radical possibility for parallelization is offered by using the Graphic processor of the computer with its single instruction multiple data capabilities. For libraries see http://www.khronos.org/opencl/ http://www.nvidia.com/object/cuda_home.html For implementations see: http://www.jakobbieling.de/university/diploma/thesis.pdf http://ws3.re.mipt.ru/mediawiki/index.php/Simplex_Method The idea here was to handle identification of the next column/row to enter the base using the CPU and the matrix multiplications using the GPU. Best regards Xypron Andrew Makhorin wrote: > >> I see two fields of applications for threading in GLPK. > >> ILOG describes that many MIPs can be solved >= 1.7 times >> faster using multiple threads and shared memory. >> http://www.ilog.com/optimization/the-right-hand-side/1/TA_Parallel_CPLEX_Dong.html >> http://www.ilog.com/optimization/the-right-hand-side/1/TA_Parallel_CPLEX_Dong.html > > Probably if a machine has more than one cpu. However, it is a brute > force approach. (It would help if the machine has 2^n processors, where > n is the number of binary variables :) Try to solve gesa2 or gesa3 > from miplib without and with mir cuts. That what's I mean. > > -- View this message in context: http://www.nabble.com/GLPK-re-endrant-tp24256046p24327716.html Sent from the Gnu - GLPK - Help mailing list archive at Nabble.com. _______________________________________________ Help-glpk mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-glpk
