The new image encryption architecture presented in this paper employs a novel circular
inter–intra pixels bit-level permutation strategy. This strategy aims to reduce redundancies …

All-Path Shortest-Path Problem (APSP) algorithm implemented on two currently used
architectures, a mono-core one and on a many-core one, is compared with the …

Abstract Various forms of Deep Neural Network (DNN) architectures are used as Deep
Learning tools for neural inspired computational systems. The computational power, the …

The practice of parallel computing emphasizes frequently used patterns. Some of them can
be accelerated using appropriate networks of simple circuits. We propose a solution, based …

This paper presents a low-maintenance, short development-cycle programming framework
(MRAFW) which allows writing and running software for a custom heterogeneous pseudo …

We present novel implementations of the Fast Fourier Transform on the massively parallel
Connex Array™(CA) circuit. The estimated performance is 19 GFlops (BenchFFT metric) of …

Spectral clustering is a Machine Learning technique intensively used in Big Data
applications. It makes extensive use of linear algebra. This article introduces the concept of …

The ubiquitousness of the parallel computational resources emerges in the rapid growing
market of system-onchip. Both, complex and intense computations are requested for solving …

We say multi-processor if there is more than one processor, while many-processor is used to
designate a system uith big-n processors. We claim fhaf fhe theoretical foundation for the fuo …

We regard the MapReduce mechanism as a unifying principle in the domain of computer
science. Going back to the roots of AI and circuits, we show that the MapReduce mechanism …