Parallel Processing Letters

An enzyme system organized in a flow device with three parallel channels was used to mimic a reversible Double Feynman Gate (DFG) with three input and three output signals. Reversible conversion of NAD⁺ and NADH cofactors was used to perform XOR logic operations, while biocatalytic oxidation of NADH resulted in Identity operation working in parallel. The first biomolecular realization of a DFG gate is promising for integrating into complex biomolecular networks operating in future unconventional biocomputing systems, as well as for novel biosensor applications.

Chemistry as an unconventional computing medium presently lacks a systematic approach to gather, store, and sort data over time. To build more complicated systems in chemistries, the ability to look at data in the past would be a valuable tool to perform complex calculations. In this paper we present the first implementation of a chemical delay line providing information storage that can reliably capture information over an extended period of time. The delay line is capable of parallel operations in a single instruction, multiple data (SIMD) fashion.

Using mass action and Michaelis-Menten kinetics, we describe the chemical delay line implementation featuring enzymes acting as a means to reduce copy errors. We also discuss how information is randomly accessible from any element on the delay line. Our work shows how the chemical delay line retains and provides a value from a previous cycle. The system's modularity allows for integration with existing chemical systems. We exemplify the delay line capabilities by integration with a threshold asymmetric signal perceptron to demonstrate how it learns all 14 linearly separable binary functions over a sliding window of size two. The delay line has applications in biomedical diagnosis and treatment, such as smart drug delivery.

This paper overviews work on the use of simple chemical reactions to calculate Voronoi diagrams and undertake other related geometric calculations. This work highlights that this type of specialised chemical processor is a model example of a parallel processor. For example increasing the complexity of the input data within a given area does not increase the computation time. These processors are also able to calculate two or more Voronoi diagrams in parallel. Due to the specific chemical reactions involved and the relative strength of reaction with the substrate (and cross-reactivity with the products) these processors are also capable of calculating Voronoi diagrams sequentially from distinct chemical inputs.

The chemical processors are capable of calculating a range of generalised Voronoi diagrams (either from circular drops of chemical or other geometric shapes made from adsorbent substrates soaked in reagent) , skeletonisation of planar shapes and weighted Voronoi diagrams (e.g., additively weighted Voronoi diagrams, Multiplicitavely weighted Crystal growth Voronoi diagrams). The paper will also discuss some limitations of these processors.

These chemical processors constitute a class of pattern forming reactions which have parallels with those observed in natural systems. It is possible that specialised chemical processors of this general type could be useful for synthesising functional structured materials.

The giant amoeboid organism true slime mould Physarum polycephalum dynamically adapts its body plan in response to changing environmental conditions and its protoplasmic transport network is used to distribute nutrients within the organism. These networks are efficient in terms of network length and network resilience and are parallel approximations of a range of proximity graphs and plane division problems. The complex parallel distributed computation exhibited by this simple organism has since served as an inspiration for intensive research into distributed computing and robotics within the last decade. P. polycephalum may be considered as a spatially represented parallel unconventional computing substrate, but how can this ‘computer’ be programmed? In this paper we examine and catalogue individual low-level mechanisms which may be used to induce network formation and adaptation in a multi-agent model of P. polycephalum. These mechanisms include those intrinsic to the model (particle sensor angle, rotation angle, and scaling parameters) and those mediated by the environment (stimulus location, distance, angle, concentration, engulfment and consumption of nutrients, and the presence of simulated light irradiation, repellents and obstacles). The mechanisms induce a concurrent integration of chemoattractant and chemorepellent gradients diffusing within the 2D lattice upon which the agent population resides, stimulating growth, movement, morphological adaptation and network minimisation. Chemoattractant gradients, and their modulation by the engulfment and consumption of nutrients by the model population, represent an efficient outsourcing of spatial computation. The mechanisms may prove useful in understanding the search strategies and adaptation of distributed organisms within their environment, in understanding the minimal requirements for complex adaptive behaviours, and in developing methods of spatially programming parallel unconventional computers and robotic devices.

In the past decade, we have witnessed the rapid development of a increasing body of research focused on Physarum polycephalum, which has been employed to solve many complicated problems in real-world applications. In this paper, we give an overview towards the developments of Physarum-inspired models for graph-optimization problems. Specifically, we reported the applications of Physarum in the following graph-optimization problems: influential nodes identification, shortest path tree problem, biobjective shortest path problem, improved Physarum algorithm and approximating the transport network.

During the past decades, computer science experts were inspired from the study of biological organisms. Moreover, bio-inspired algorithms were produced that many times can give excellent solutions with low computational cost in complex engineering problems. In our case, the plasmodium of Physarum polycephalum is capable of finding the shortest path solution between two points in a labyrinth. In this study, we implement a Cellular Automata (CA) model in hardware, which attempts to describe and, moreover, mimic the behavior of the plasmodium in a maze. Beyond the successful implementation of the CA-based Physarum model in software, in order to take full advantage of the inherent parallelism of CA, we focus on a Field Programmable Gate Array (FPGA) implementation of the proposed model. Namely, two different implementations were considered here. Their difference is on the desired precision produced by the numerical representation of CA model parameters. Based on the corresponding results of the shortest path in the labyrinth,the modeling efficiency of both approaches was compared depending on the resulting error propagation. The presented FPGA implementations succeed to take advantage of the CA's inherit parallelism and improve the performance of the CA algorithm when compared with software in terms of computational speed and power consumption. As a result, the implementations presented here, can also be considered as a preliminary CA-based Physarum polycephalum IP core which produces a biological inspired solution to the shortest-path problem.

The relation between scatters of time and energy is well known in Classical and Quantum Physics, but the interpretations of such relation are not well understood. What is the meaning of a time scatter in a measurement? What is the meaning of the correlated energy gap? Why should they combine to give a value greater or equal to a theoretical lower bound? In this paper, we discuss uncertainty in measurement from the computational point of view and introduce the archetype of a generic stochastic oracle to a Turing machine.

We define a kind of simple actions of labelled transition systems. These actions cannot be atomic; consequently, their compositions cannot be inductive. Their informal meaning is that in one simple action we can suppose the maximum of its modifications. Such actions are called hybrid. Then we propose two formal theories on hybrid actions (the hybrid actions are defined there as non-well-founded terms and non-well-founded formulas): group theory and Boolean algebra. Both theories possess many unusual properties such as the following one: the same member of this group theory behaves as multiplicative zero in respect to one members and as multiplicative unit in respect to other members.