—Simulating spiking neural networks is of great interest to scientists wanting to model the functioning of the brain. However, large-scale models are expensive to simulate due to...
Andreas Fidjeland, Etienne B. Roesch, Murray Shana...
Datacenter networks typically have many paths connecting each host pair to achieve high bisection bandwidth for arbitrary communication patterns. Fully utilizing the bisection ban...
Computation without stable states is a computing paradigm different from Turing's and has been demonstrated for various types of simulated neural networks. This publication t...
The solution of continuous and discrete-time Markovian models is still challenging mainly when we model large complex systems, for example, to obtain performance indexes of paralle...
In this paper we present a general hybrid systems modeling framework to describe the flow of traffic in communication networks. To characterize network behavior, these models use...