Edge computing is an emerging paradigm for the increasing computing and networking
demands from end devices to smart things. Edge computing allows the computation to be …

k nearest neighbours (kNN) queries are fundamental in many applications, ranging from
data mining, recommendation system and Internet of Things, to Industry 4.0 framework …

" Brian" is a simulator for spiking neural networks (http://www. briansimulator. org). The focus
is on making the writing of simulation code as quick and easy as possible for the user, and …

" Brian" is a new simulator for spiking neural networks, written in Python (http://brian. di. ens.
fr). It is an intuitive and highly flexible tool for rapidly developing new models, especially …

To extend the exponential performance scaling of future chip multiprocessors, improving
energy efficiency has become a first-class priority. Single-chip heterogeneous computing …

The multiplication of a sparse matrix by a dense vector (SpMV) is a centerpiece of scientific
computing applications: it is the essential kernel for the solution of sparse linear systems and …

The introduction of General-Purpose computation on GPUs (GPGPUs) has changed the
landscape for the future of parallel computing. At the core of this phenomenon are massively …

Graphics processing units are capable of impressive computing performance up to
518Gflops peak performance. Various groups have been using these processors for general …

With the potential of quantum algorithms to solve intractable classical problems, quantum
computing is rapidly evolving, and more algorithms are being developed and optimized …

Deep learning has become widely used in complex AI applications. Yet, training a deep
neural network (DNNs) model requires a considerable amount of calculations, long running …