GPU-based implementation of real-time system for spiking neural networks

Real-time simulations of biological neural networks (BNNs) provide a natural platform for applications in a variety of fields: data classification and pattern recognition, prediction and estimation, signal processing, control and robotics, prosthetics, neurological and neuroscientific modeling. BNNs possess inherently parallel architecture and operate in continuous signal domain. Spiking neural networks (SNNs) are type of BNNs with reduced signal dynamic range: communication between neurons occurs by means of time-stamped events (spikes). SNNs allow reduction of algorithmic complexity and communication data size at a price of little loss in accuracy. Simulation of SNNs using traditional sequential computer architectures results in significant time penalty. This penalty prohibits application of SNNs in real-time systems. Graphical processing units (GPUs) are cost effective devices specifically designed to exploit parallel shared memory-based floating point operations applied not only to computer graphics, but also to scientific computations. This makes them an attractive solution for SNN simulation compared to that of FPGA, ASIC and cluster message passing computing systems. Successful implementations of GPU-based SNN simulations have been already reported. The contribution of this thesis is the development of a scalable GPU-based realtime system that provides initial framework for design and application of SNNs in various domains. The system delivers an interface that establishes communication with neurons in the network as well as visualizes the outcome produced by the network. Accuracy of the simulation is emphasized due to its importance in the systems that exploit spike time dependent plasticity, classical conditioning and learning. As a result, a small network of 3840 Izhikevich neurons implemented as a hybrid system with Parker-Sochacki numerical integration method achieves real time operation on GTX260 device. An application case study of the system modeling receptor layer of retina is reviewed

Tool for supporting collaborative writing in diverged documents

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2007.Includes bibliographical references (p. 83-89).This thesis builds on theory from the fields of computer supported cooperative work and computer supported collaborative writing and the example of work in the free and open source software development communities to describe "cooperation in parallel" - a mode of collaborative writing among parties with diverged goals and distinct documents. It examines the social and technological requirements of cooperation in parallel for writing and considers the effectiveness of existing technologies ability to address them. It then presents the design and evaluation of TextNet: a wiki for document writing that uses techniques from software development including branch creation and tracking features and introduces a text-specific interface for merging changes and representing and resolving conflicts. It concludes by arguing that TextNet makes important steps toward the support cooperation in parallel for writing.by Benjamin Mako Hill.S.M

Efficient Implementation of Stochastic Inference on Heterogeneous Clusters and Spiking Neural Networks

Neuromorphic computing refers to brain inspired algorithms and architectures. This paradigm of computing can solve complex problems which were not possible with traditional computing methods. This is because such implementations learn to identify the required features and classify them based on its training, akin to how brains function. This task involves performing computation on large quantities of data. With this inspiration, a comprehensive multi-pronged approach is employed to study and efficiently implement neuromorphic inference model using heterogeneous clusters to address the problem using traditional Von Neumann architectures and by developing spiking neural networks (SNN) for native and ultra-low power implementation. In this regard, an extendable high-performance computing (HPC) framework and optimizations are proposed for heterogeneous clusters to modularize complex neuromorphic applications in a distributed manner. To achieve best possible throughput and load balancing for such modularized architectures a set of algorithms are proposed to suggest the optimal mapping of different modules as an asynchronous pipeline to the available cluster resources while considering the complex data dependencies between stages. On the other hand, SNNs are more biologically plausible and can achieve ultra-low power implementation due to its sparse spike based communication, which is possible with emerging non-Von Neumann computing platforms. As a significant progress in this direction, spiking neuron models capable of distributed online learning are proposed. A high performance SNN simulator (SpNSim) is developed for simulation of large scale mixed neuron model networks. An accompanying digital hardware neuron RTL is also proposed for efficient real time implementation of SNNs capable of online learning. Finally, a methodology for mapping probabilistic graphical model to off-the-shelf neurosynaptic processor (IBM TrueNorth) as a stochastic SNN is presented with ultra-low power consumption

Deep Space Network information system architecture study

The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control

Design and Implementation of HD Wireless Video Transmission System Based on Millimeter Wave

With the improvement of optical fiber communication network construction and the improvement of camera technology, the video that the terminal can receive becomes clearer, with resolution up to 4K. Although optical fiber communication has high bandwidth and fast transmission speed, it is not the best solution for indoor short-distance video transmission in terms of cost, laying difficulty and speed. In this context, this thesis proposes to design and implement a multi-channel wireless HD video transmission system with high transmission performance by using the 60GHz millimeter wave technology, aiming to improve the bandwidth from optical nodes to wireless terminals and improve the quality of video transmission. This thesis mainly covers the following parts: (1) This thesis implements wireless video transmission algorithm, which is divided into wireless transmission algorithm and video transmission algorithm, such as 64QAM modulation and demodulation algorithm, H.264 video algorithm and YUV420P algorithm. (2) This thesis designs the hardware of wireless HD video transmission system, including network processing unit (NPU) and millimeter wave module. Millimeter wave module uses RWM6050 baseband chip and TRX-BF01 rf chip. This thesis will design the corresponding hardware circuit based on the above chip, such as 10Gb/s network port, PCIE. (3) This thesis realizes the software design of wireless HD video transmission system, selects FFmpeg and Nginx to build the sending platform of video transmission system on NPU, and realizes video multiplex transmission with Docker. On the receiving platform of video transmission, FFmpeg and Qt are selected to realize video decoding, and OpenGL is combined to realize video playback. (4) Finally, the thesis completed the wireless HD video transmission system test, including pressure test, Web test and application scenario test. It has been verified that its HD video wireless transmission system can transmit HD VR video with three-channel bit rate of 1.2GB /s, and its rate can reach up to 3.7GB /s, which meets the research goal

Game-Based Learning, Gamification in Education and Serious Games

The aim of this book is to present and discuss new advances in serious games to show how they could enhance the effectiveness and outreach of education, advertising, social awareness, health, policies, etc. We present their use in structured learning activities, not only with a focus on game-based learning, but also on the use of game elements and game design techniques to gamify the learning process. The published contributions really demonstrate the wide scope of application of game-based approaches in terms of purpose, target groups, technologies and domains and one aspect they have in common is that they provide evidence of how effective serious games, game-based learning and gamification can be

Performance visualization for parallel programs: task-based, object-oriented approach

Developing and analyzing the performance of concurrent programs on distributed memory concurrent systems is normally a challenging task. Recently, performance visualization gains its importance as a critical tool for programmers. Programmers can have an insight into the development of parallel programs through a performance visualization. Most of the visualization tool to date have been developed for ad-hoc environments in hardware and software, and therefore its lifetime is limited. Since, however, new architectures keep emerging and application domains for distributed memory concurrent computer systems keep growing, the visualization tool should be flexible enough to accommodate unknown future demands of users (eg. new performance perspectives, application-specific views and disparate trace record formats);The Concurrent Object-Oriented ParaGraph (COOPG) is a prototype, general-purpose performance visualization package developed using an object-oriented approach. An object-oriented approach, both in design and implementation, provides a mechanism to build a simple, flexible, effective, and extensible performance visualization tool. The salient features of the COOPG include its flexible adaptability to disparate trace record formats and the incremental extensibility for incorporating user\u27s special-purpose views

Small business innovation research. Abstracts of completed 1987 phase 1 projects

Non-proprietary summaries of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA in the 1987 program year are given. Work in the areas of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robotics, computer sciences, information systems, spacecraft systems, spacecraft power supplies, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

Engineering Design Team Leadership in Undergraduate Design Teams

The objective of this research is to develop an understanding of the emergence and distribution of leadership behaviors in engineering design teams. This research was conducted with undergraduate engineering students and explored leadership behaviors within design teams in a variety of contexts. Undergraduates were selected for the study since they possessed similar education and skills as a novice engineer in industry. A mixed methods approach incorporated qualitative and quantitative techniques including interview, case study, and protocol study instruments. The use of these methods enabled the exploration of leadership in both natural and controlled environments to capitalize on the research advantages of each. Interviews were employed to understand faculty perceptions of leadership in design teams. The case study enabled the identification of leadership in a natural context without the need to control the multitude of variables in collaborative design. The protocol study provided a more focused and controlled study to identify patterns of leadership emergence and distribution of functions within a specific conceptual design activity: function modeling. The teams examined ranged from three to four-member design teams in the protocol study to ten-member teams with behavior resembling multiteam systems in the case studies. The resulting insights provide increased understanding of the emergence of leadership and the distribution of leadership functions within design teams. Interviews manifested faculty perceptions that formal structures are developed early and that informal roles emerge throughout projects, with communication skills playing an important role. Faculty perceptions on leadership covered a broad range of leadership functions including “performing task” and “consideration.” The density of leadership networks during case studies confirmed the emergence of informal leadership functions among designers and indicated variations in function distribution at sampling points. Protocol studies indicated that informal leadership was established early, and that leaders active early remained active throughout these focused sessions. A single instance of variation in protocol study team size demonstrated a structural parity in a three-member team that was not observed in four-member teams. This supports faculty perception that larger and multi-dimensional teams also provided different opportunities for leadership development. This understanding will form the basis for further research into leadership of design teams and may assist in the development of leadership interventions in engineering design teams and design education

Integrated Circuits and Systems for Smart Sensory Applications

Connected intelligent sensing reshapes our society by empowering people with increasing new ways of mutual interactions. As integration technologies keep their scaling roadmap, the horizon of sensory applications is rapidly widening, thanks to myriad light-weight low-power or, in same cases even self-powered, smart devices with high-connectivity capabilities. CMOS integrated circuits technology is the best candidate to supply the required smartness and to pioneer these emerging sensory systems. As a result, new challenges are arising around the design of these integrated circuits and systems for sensory applications in terms of low-power edge computing, power management strategies, low-range wireless communications, integration with sensing devices. In this Special Issue recent advances in application-specific integrated circuits (ASIC) and systems for smart sensory applications in the following five emerging topics: (I) dedicated short-range communications transceivers; (II) digital smart sensors, (III) implantable neural interfaces, (IV) Power Management Strategies in wireless sensor nodes and (V) neuromorphic hardware