From morphogenetic data to performative behaviour

This paper presents part of CORK’EWS, a research work developed within the framework of the Digital Architecture Advanced Program 2012/13 at ISCTE-IUL. The main goal of this investigation was to develop a parametric, customizable and adaptive wall system designed for environmental performance. Moreover, the system is based on standard industrial products: expanded cork blocks produced by Amorim Insulation industries. CAD/CAM resources were the essential tools of the research process, where fundamental and practical knowledge is integrated to understand the microstructure morphological properties of the raw material – cork – and its derivate – natural expanded cork. These properties were upscale and adapted to create a wall with an optimized solar control environmental performance. The result is a digitally fabricated prototype of a new customizable industrial product, adaptable to specific environmental conditions and installation setups being therefore easily commercialized. From microstructural morphology to macroscale construction, the research explores new application possibilities through morphogenesis and opens new possible markets for these customizable products.info:eu-repo/semantics/acceptedVersio

NeuroFlow: A General Purpose Spiking Neural Network Simulation Platform using Customizable Processors

© 2016 Cheung, Schultz and Luk.NeuroFlow is a scalable spiking neural network simulation platform for off-the-shelf high performance computing systems using customizable hardware processors such as Field-Programmable Gate Arrays (FPGAs). Unlike multi-core processors and application-specific integrated circuits, the processor architecture of NeuroFlow can be redesigned and reconfigured to suit a particular simulation to deliver optimized performance, such as the degree of parallelism to employ. The compilation process supports using PyNN, a simulator-independent neural network description language, to configure the processor. NeuroFlow supports a number of commonly used current or conductance based neuronal models such as integrate-and-fire and Izhikevich models, and the spike-timing-dependent plasticity (STDP) rule for learning. A 6-FPGA system can simulate a network of up to ~600,000 neurons and can achieve a real-time performance of 400,000 neurons. Using one FPGA, NeuroFlow delivers a speedup of up to 33.6 times the speed of an 8-core processor, or 2.83 times the speed of GPU-based platforms. With high flexibility and throughput, NeuroFlow provides a viable environment for large-scale neural network simulation

A Universalist strategy for the design of Assistive Technology

Assistive Technologies are specialized products aiming to partly compensate for the loss of autonomy experienced by disabled people. Because they address special needs in a highly-segmented market, they are often considered as niche products. To improve their design and make them tend to Universality, we propose the EMFASIS framework (Extended Modularity, Functional Accessibility, and Social Integration Strategy). We first elaborate on how this strategy conciliates niche and Universalist views, which may appear conflicting at first sight. We then present three examples illustrating its application for designing Assistive Technologies: the design of an overbed table, an upper-limb powered orthose and a powered wheelchair. We conclude on the expected outcomes of our strategy for the social integration and participation of disabled people

VirtFogSim: A parallel toolbox for dynamic energy-delay performance testing and optimization of 5G Mobile-Fog-Cloud virtualized platforms

It is expected that the pervasive deployment of multi-tier 5G-supported Mobile-Fog-Cloudtechnological computing platforms will constitute an effective means to support the real-time execution of future Internet applications by resource- and energy-limited mobile devices. Increasing interest in this emerging networking-computing technology demands the optimization and performance evaluation of several parts of the underlying infrastructures. However, field trials are challenging due to their operational costs, and in every case, the obtained results could be difficult to repeat and customize. These emergingMobile-Fog-Cloud ecosystems still lack, indeed, customizable software tools for the performance simulation of their computing-networking building blocks. Motivated by these considerations, in this contribution, we present VirtFogSim. It is aMATLAB-supported software toolbox that allows the dynamic joint optimization and tracking of the energy and delay performance of Mobile-Fog-Cloud systems for the execution of applications described by general Directed Application Graphs (DAGs). In a nutshell, the main peculiar features of the proposed VirtFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the placement of the application tasks and the allocation of the needed computing-networking resources under hard constraints on acceptable overall execution times, (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall system; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operational environments, as those typically featuring mobile applications; (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering, and (v) itsMATLAB code is optimized for running atop multi-core parallel execution platforms. To check both the actual optimization and scalability capabilities of the VirtFogSim toolbox, a number of experimental setups featuring different use cases and operational environments are simulated, and their performances are compared

High-Performance Cloud Computing: A View of Scientific Applications

Scientific computing often requires the availability of a massive number of computers for performing large scale experiments. Traditionally, these needs have been addressed by using high-performance computing solutions and installed facilities such as clusters and super computers, which are difficult to setup, maintain, and operate. Cloud computing provides scientists with a completely new model of utilizing the computing infrastructure. Compute resources, storage resources, as well as applications, can be dynamically provisioned (and integrated within the existing infrastructure) on a pay per use basis. These resources can be released when they are no more needed. Such services are often offered within the context of a Service Level Agreement (SLA), which ensure the desired Quality of Service (QoS). Aneka, an enterprise Cloud computing solution, harnesses the power of compute resources by relying on private and public Clouds and delivers to users the desired QoS. Its flexible and service based infrastructure supports multiple programming paradigms that make Aneka address a variety of different scenarios: from finance applications to computational science. As examples of scientific computing in the Cloud, we present a preliminary case study on using Aneka for the classification of gene expression data and the execution of fMRI brain imaging workflow.Comment: 13 pages, 9 figures, conference pape

Collective intelligence for OER sustainability

To thrive, the Open Educational Resource (OER) movement, or a given initiative, must make sense of a complex, changing environment. Since “sustainability” is a desirable systemic capacity that our community should display, we consider a number of principles that sharpen the concept: resilience, sensemaking and complexity. We outline how these motivate the concept of collective intelligence (CI), we give examples of what OER-CI might look like, and we describe the emerging Cohere CI platform we are developing in response to these requirements