From: lilia Date: Wed, 12 Feb 2014 09:38:17 +0000 (+0100) Subject: 12-02-2014 1 X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/GMRES_For_Journal.git/commitdiff_plain/9b7d35fd78aada44f863f3613f6e57b3fe5f9b15?ds=inline;hp=d164a3ea8701e61dd439dcf53021079d7116d8f6 12-02-2014 1 --- diff --git a/GMRES_Journal.tex b/GMRES_Journal.tex index cd0af72..37acbcc 100644 --- a/GMRES_Journal.tex +++ b/GMRES_Journal.tex @@ -944,7 +944,7 @@ torso3 & 57.469 s & 16.828 s & {\bf 3.415} & 926.588 s -Another very important issue, which might be ignored by too many people, is that the communications have a greater influence on a cluster of GPUs than on a cluster of CPUs. There are two reasons for that. The first one comes from the fact that with a cluster of GPUs, the CPU/GPU data transfers slow down communications between two GPUs that are not on the same machines. The second one is due to the fact that with GPUs the ratio of the computation time over the communication time decreases since the computation time is reduced. So the impact of the communications between GPUs might be a very important issue that can limit the scalability of a parallel algorithms. +Another very important issue, which might be ignored by too many people, is that the communications have a greater influence on a cluster of GPUs than on a cluster of CPUs. There are two reasons for that. The first one comes from the fact that with a cluster of GPUs, the CPU/GPU data transfers slow down communications between two GPUs that are not on the same machines. The second one is due to the fact that with GPUs the ratio of the computation time over the communication time decreases since the computation time is reduced. So the impact of the communications between GPUs might be a very important issue that can limit the scalability of parallel algorithms. %%--------------------%% %% SECTION 7 %%