: In scalable parallel machines, processors can make local memory accesses much faster than they can make remote memory accesses. In addition, when a number of remote accesses must...
Distributed learning is a problem of fundamental interest in machine learning and cognitive science. In this paper, we present asynchronous distributed learning algorithms for two...
Abstract. Many parallel scienti c applications have dynamic and irregular computational structure. However, most such applications exhibit persistence of computational load and com...
Milind A. Bhandarkar, Robert Brunner, Laxmikant V....
Pipelining has been used in the design of many PRAM algorithms to reduce their asymptotic running time. Paul, Vishkin, and Wagener (PVW) used the approach in a parallel implementat...
Failures of any type are common in current datacenters, partly due to the higher scales of the data stored. As data scales up, its availability becomes more complex, while differe...
Nicolas Bonvin, Thanasis G. Papaioannou, Karl Aber...