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...
Simulation of large-scale networks requires enormous amounts of memory and processing time. One way of speeding up these simulations is to distribute the model over a number of co...
The parallel realization of adaptive finite element methods (FEM) has to deal with several irregular and dynamic algorithmic properties caused by adaptive mesh refinement (AMR). ...
This paper proposes a novel way to use virtual memorymapped communication (VMMC) to reduce the failover time on clusters. With the VMMC model, applications’ virtual address spac...
This paper describes improvements to the Mach microkernel’s support for efficient application startup across multiple nodes in a cluster or massively parallel processor. Signifi...
Dejan S. Milojicic, David L. Black, Steven J. Sear...