Search results for "unconventional computing"
showing 7 items of 7 documents
Nanomagnetic Self-Organizing Logic Gates
2021
The end of Moore's law for CMOS technology has prompted the search for low-power computing alternatives, resulting in several promising proposals based on magnetic logic[1-8]. One approach aims at tailoring arrays of nanomagnetic islands in which the magnetostatic interactions constrain the equilibrium orientation of the magnetization to embed logical functionalities[9-12]. Despite the realization of several proofs of concepts of such nanomagnetic logic[13-15], it is still unclear what the advantages are compared to the widespread CMOS designs, due to their need for clocking[16, 17] and/or thermal annealing [18,19] for which fast convergence to the ground state is not guaranteed. In fact, i…
Tractional Motion Machines: Tangent-Managing Planar Mechanisms as Analog Computers and Educational Artifacts
2012
Concrete and virtual machines play a central role in the both Unconventional Computing (machines as computers) and in Math Education (influence of artifacts on reaching/producing abstract thought). Here we will examine some fallouts in these fields for the Tractional Motion Machines, planar mechanisms based on some devices used to plot the solutions of differential equations by the management of the tangent since the late 17th century.
The promise of spintronics for unconventional computing
2021
Novel computational paradigms may provide the blueprint to help solving the time and energy limitations that we face with our modern computers, and provide solutions to complex problems more efficiently (with reduced time, power consumption and/or less device footprint) than is currently possible with standard approaches. Spintronics offers a promising basis for the development of efficient devices and unconventional operations for at least three main reasons: (i) the low-power requirements of spin-based devices, i.e., requiring no standby power for operation and the possibility to write information with small dynamic energy dissipation, (ii) the strong nonlinearity, time nonlocality, and/o…
Accelerating bioinformatics applications via emerging parallel computing systems [Guest editorial]
2015
The papers in this issue focus on advanced parallel computing systems for bioinformatics applications. This papers provide a forum to publish recent advances in the improvement of handling bioinformatics problems on emerging parallel computing systems. These systems can be characterized by exploiting different types of parallelism, including fine-grained versus coarse-grained and thread-level parallelism versus datalevel parallelism versus request-level parallelism. Hence, parallel computing systems based on multi- and many-core CPUs, many-core GPUs, vector processors, or FPGAs offer the promise to massively accelerate many bioinformatics algorithms and applications, ranging from computeint…
Real-time low level feature extraction for on-board robot vision systems
2006
Robot vision systems notoriously require large computing capabilities, rarely available on physical devices. Robots have limited embedded hardware, and almost all sensory computation is delegated to remote machines. Emerging gigascale integration technologies offer the opportunity to explore alternative computing architectures that can deliver a significant boost to on-board computing when implemented in embedded, reconfigurable devices. This paper explores the mapping of low level feature extraction on one such architecture, the Georgia Tech SIMD Pixel Processor (SIMPil). The Fast Boundary Web Extraction (fBWE) algorithm is adapted and mapped on SIMPil as a fixed-point, data parallel imple…
Logic, Computing and Biology
2015
Logic and Computing are appropriate formal languages for Biology, and we may well be surprised by the strong analogy between software and DNA, and between hardware and the protein machinery of the cell. This chapter examines to what extent any biological entity can be described by an algorithm and, therefore, whether the Turing machine and the halting problem concepts apply. Last of all, I introduce the concepts of recursion and algorithmic complexity, both from the field of computer science, which can help us understand and conceptualise biological complexity.
A Survey on Technologies Which Make Bitcoin Greener or More Justified
2022
According to recent estimates, one bitcoin transaction consumes as much energy as 1.5 million Visa transactions. Why is bitcoin using so much energy? Most of the energy is used during the bitcoin mining process, which serves at least two significant purposes: a) distributing new cryptocurrency coins to the cryptoeconomy and b) securing the Bitcoin blockchain ledger. In reality, the comparison of bitcoin transactions to Visa transactions is not that simple. The amount of transactions in the Bitcoin network is not directly connected to the amount of bitcoin mining power nor the energy consumption of those mining devices; for example, it is possible to multiply the number of bitcoin transactio…