Ali Baharev a écrit : > Hi, > > Once upon a time, I had a discussion with one of the GPULib developers > and he told me GPUs were not good for the simplex method, because the > gain is not so significant for sparse matrix-vector operations. (Or at > least it was what i understood.)
Moreover, the RAM dedicated for GPU's is different, as it is not totally data-safe. Some bits may change during time, potentially introducing errors in computations. You cannot implement an exact solver using such hardware. In addition, GPUs were historically been designed for computing on single precision computations. Double precision has recently been included on most modern GPUs, though. Finally, modern CPU's also have SIMD instructions (SSE/SSE2/... on Intel's, Altivec on POWER's) which can be used for data-parallel operations on a single core. C compilers provide the possibility to uses such instructions directly in C, through special "function calls" called 'intrinsics'. Though, already-existing software such as GLPK would require heavy re-rengineering (most data structures and algorithms would require to be redesigned) to support such a programming model. -- François Galea INRIA - Saclay - Batiment N Parc Orsay Université 4 rue J. Monod F-91893 Orsay Cedex Tél. : +33 1 72 92 59 24 _______________________________________________ Help-glpk mailing list [email protected] http://lists.gnu.org/mailman/listinfo/help-glpk
