25,574 resources related to Distributed Processing
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ICC 2021 - IEEE International Conference on Communications
IEEE ICC is one of the two flagship IEEE conferences in the field of communications; Montreal is to host this conference in 2021. Each annual IEEE ICC conference typically attracts approximately 1,500-2,000 attendees, and will present over 1,000 research works over its duration. As well as being an opportunity to share pioneering research ideas and developments, the conference is also an excellent networking and publicity event, giving the opportunity for businesses and clients to link together, and presenting the scope for companies to publicize themselves and their products among the leaders of communications industries from all over the world.
The Frontiers in Education (FIE) Conference is a major international conference focusing on educational innovations and research in engineering and computing education. FIE 2019 continues a long tradition of disseminating results in engineering and computing education. It is an ideal forum for sharing ideas, learning about developments and interacting with colleagues inthese fields.
The International Conference on Image Processing (ICIP), sponsored by the IEEE SignalProcessing Society, is the premier forum for the presentation of technological advances andresearch results in the fields of theoretical, experimental, and applied image and videoprocessing. ICIP 2020, the 27th in the series that has been held annually since 1994, bringstogether leading engineers and scientists in image and video processing from around the world.
The ICASSP meeting is the world's largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class speakers, tutorials, exhibits, and over 50 lecture and poster sessions.
IEEE INFOCOM solicits research papers describing significant and innovative researchcontributions to the field of computer and data communication networks. We invite submissionson a wide range of research topics, spanning both theoretical and systems research.
The IEEE Aerospace and Electronic Systems Magazine publishes articles concerned with the various aspects of systems for space, air, ocean, or ground environments.
The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...
Covers topics in the scope of IEEE Transactions on Communications but in the form of very brief publication (maximum of 6column lengths, including all diagrams and tables.)
Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.
IEEE Computer Graphics and Applications (CG&A) bridges the theory and practice of computer graphics. From specific algorithms to full system implementations, CG&A offers a strong combination of peer-reviewed feature articles and refereed departments, including news and product announcements. Special Applications sidebars relate research stories to commercial development. Cover stories focus on creative applications of the technology by an artist or ...
19th IEEE International Parallel and Distributed Processing Symposium, 2005
Summary form only given. In this talk the author proposes to give us his understanding of distributed processing, how it differs fundamentally from non-distributed processing, and show that in this world of continually increasing complexity, it is the only paradigm that makes sense. Not surprisingly, the effective (and ineffective) uses of distributed processing are all around us. Several enlightening examples: ...
2013 IEEE International Congress on Big Data, 2013
This paper presents the distributed processing feature for Trade Wind, a cloud deployment and management solution. The main objective of this research is to evaluate performance and feasibility of this feature for big data applications. A prototype has been created and tested in the calculation of monthly average temperature and humidity based on data from a public data set. Preliminary ...
Proceedings of the Second IEEE Symposium on Parallel and Distributed Processing 1990, 1990
Two major issues which must be addressed in the VLSI layout methodology are placement and routing. Traditionally, these two issues are handled separately to reduce the computational complexity. But these two issues are interrelated as routability must be guaranteed for placement in addition to the geometrical constraints. The authors propose a distributed processing approach for solving this integrated routing-placement problem. ...
2015 4th Mediterranean Conference on Embedded Computing (MECO), 2015
Distributed Processing Systems (DPS) take sophisticated tasks as input, and process them in a distributed manner using spread resources. In this paper, we evaluate DPS implemented on low-level System-on-Chip (SoC) interconnection architectures: mesh, concentrated mesh and fat tree. We propose autonomous algorithms for nodes and routers and define efficiency metrics that are used later for evaluation. The evaluation is performed ...
2009 39th IEEE Frontiers in Education Conference, 2009
A new multi-CPU parallel and distributed processing experiment platform using plural FPGA (field programmable gate array) platforms is under development. Students can remotely perform hardware and software experiments combining a number of FPGA-based experiment platforms. The authors have already developed a remote laboratory, namely Cyber Laboratory, which realized an efficient sharing of hardware platforms among on-site and remote-site students, both ...
IEEE Themes - Efficient networking services underpin social networks
IEEE Themes - Five incentive schemes for peer-to-peer networks
Hyperdimensional Biosignal Processing: A Case Study for EMG-based Hand Gesture Recognition - Abbas Rahimi: 2016 International Conference on Rebooting Computing
Keynote 2: Exploring New Technologies for 5G/Future Networks - Dilip Krishnaswamy - India Mobile Congress, 2018
Multiple Sensor Fault Detection and Isolation in Complex Distributed Dynamical Systems
A 6GS/s 9.5 Bit Pipelined Folding-Interpolating ADC with 7.3 ENOB and 52.7dBc SFDR in the 2nd Nyquist Band in 0.25μm SiGe-BiCMOS: RFIC Interactive Forum
Erasing Logic-Memory Boundaries in Superconductor Electronics - Vasili Semenov: 2016 International Conference on Rebooting Computing
The Vienna LTE-A Dowlink Link-Level Simulator
IMS MicroApps: AWR's iFilter
APEC Speaker Highlights: Ron Van Dell
Introduction to Chip Multiprocessor Architecture
ICASSP 2011 Trends in Machine Learning for Signal Processing
ICASSP 2010 - New Signal Processing Application Areas
Hamid R Tizhoosh - Fuzzy Image Processing
ICASSP 2011 Trends in Design and Implementation of Signal Processing Systems
Alan S. Willsky - IEEE Jack S. Kilby Signal Processing Medal, 2019 IEEE Honors Ceremony
IMS 2011 Microapps - Quickwave Electromagnetic Software with CAD Input and GPU Processing
Yahoo's Raghu Ramakrishnan Discusses CAP and Cloud Data Management
Signal Processing on Manifolds
Summary form only given. In this talk the author proposes to give us his understanding of distributed processing, how it differs fundamentally from non-distributed processing, and show that in this world of continually increasing complexity, it is the only paradigm that makes sense. Not surprisingly, the effective (and ineffective) uses of distributed processing are all around us. Several enlightening examples: an effective military, organized religion, the American game of football, and university education. The author discusses each. The author submits that these examples have a unifying theory that could be relevant to microarchitecture. The author describes it as a two-phased approach: preparation and execution. The microarchitect historically has designed central processing units. But to keep pace with current and future design points, including processing power that device technology continues to provide, distributed processing technology becomes essential. Along the way, the author introduces and explains the relevance of my levels of transformation, multichip processors, the refrigerator, and data flow.
This paper presents the distributed processing feature for Trade Wind, a cloud deployment and management solution. The main objective of this research is to evaluate performance and feasibility of this feature for big data applications. A prototype has been created and tested in the calculation of monthly average temperature and humidity based on data from a public data set. Preliminary results show great improvement in terms of time reduction, speedup, and efficiency.
Two major issues which must be addressed in the VLSI layout methodology are placement and routing. Traditionally, these two issues are handled separately to reduce the computational complexity. But these two issues are interrelated as routability must be guaranteed for placement in addition to the geometrical constraints. The authors propose a distributed processing approach for solving this integrated routing-placement problem. The distributed processing network is roughly based on the Hopfield model and is designed to minimize an objective function similar to that used for the traveling salesman problem. Minimization of the objective function provides cell placements such that the total net span is minimized. The idea is based on the notion of slicing the slice sequencing in a hierarchical fashion.<<ETX>>
Distributed Processing Systems (DPS) take sophisticated tasks as input, and process them in a distributed manner using spread resources. In this paper, we evaluate DPS implemented on low-level System-on-Chip (SoC) interconnection architectures: mesh, concentrated mesh and fat tree. We propose autonomous algorithms for nodes and routers and define efficiency metrics that are used later for evaluation. The evaluation is performed by a dedicated experimentation system, in which fully functional DPS is implemented. In this paper, we focus on resource utilization in interconnection networks and also present their energy consumption. Tradeoff between utilization and electrical energy consumption is presented. Research results show that the concentrated mesh is a promising interconnection network suitable to handle the needs of distributed processing systems.
A new multi-CPU parallel and distributed processing experiment platform using plural FPGA (field programmable gate array) platforms is under development. Students can remotely perform hardware and software experiments combining a number of FPGA-based experiment platforms. The authors have already developed a remote laboratory, namely Cyber Laboratory, which realized an efficient sharing of hardware platforms among on-site and remote-site students, both in space-division and time-division fashions. Multi-CPU parallel and distributed processing experiment environment is implemented on a combined use of multiple set of FPGA experiment platforms based on the Cyber Laboratory. Each FPGA platform consists of a FPGA board with a LAN port, host PC as an experiment server, a signal generator, a logic analyzer and a synchronizing mechanism. LAN is used to connect FPGA platforms to organize a parallel system. Therefore, the proposed system can provide each student not only with a CPU hardware design/experiment platform but also with an environment where he/she can conduct parallel and distributed processing as well. The project is at a detailed design phase, and the prototype will be operational in 2010.
Summary form only given. Vast networks of intelligent sensors that are deeply embedded in physical world will revolutionize practices in the life sciences, civil engineering, manufacturing, security, agriculture, ubiquitous computing, and many other areas. They also present a wonderful new venue for parallel and distributed processing. Bandwidth, storage, and energy limitations make in- network processing essential - within the node and among collections of nodes. The algorithms should be resource efficient, but also deal with noise, uncertainly and dynamically changing connectivity. Ideally, application programming is done at the level of unstructured ensembles, rather than individual nodes. To explore these issues, we have built a series of inch- scale wireless sensor platforms, along with an operating system and networking substrate for vast collections of tiny, power-constrained devices - TinyOS. This open experimental platform is being used by hundreds of research projects internationally in a wide range of disciplines. This talk describes the challenges in making networks of such devices robust and programmable, including platform architecture, operating system design, network discovery and routing, and explores novel distributed algorithms developed for such networks.
TINA architecture is defined to be applicable to software applications operating in the network, and one of the more straightforward impacts is on management applications. The object oriented paradigm has been widely accepted as the means for structuring management communications. Moreover network management platforms operating on top of general purpose hardware and software computer systems are already available on the market, thus responding to requirements, such as modularity and flexibility, that are part of the objectives of the TINA architecture. The paper describes the results of the experience of implementing a management application, specifically a connection management application, structured according to object-oriented paradigms and running on multiple interoperable distributed processing environments. Traditionally connection management has been always considered as control operations which are viewed as being different from management. In case of TINA connection management we deal with real-time and dynamic management operations. After a brief introduction on the chosen application scenario and the consequent generic requirements on the connection management system, an implementation case is described especially focusing on software platform aspects and applications interoperability.
In this paper we present a model of cycle of development of a phased array radar with distributed processing to reduce the project development time. To this objective it was developed a new tool that shortened the total time required for the inclusion and modification of new algorithms by evaluating the impact of each one in the distributed processing resources prior to the implementation. This tool avoids the common step of implementing a module, testing it, and then correcting it. It is replaced by iterative steps of high level evaluation, and then with a deployment more likely to work.
Distributed Processing Environment (DPE) refers multiple computers are linked together and forms a computer network to solve a common problem. In DPE many application elements that are spread over numerous computers, but work as a one processing system. DPE may include a local area network and computers are physically close together or it may be link by a wide area network and computers are geographically distant. Processing power of processing units in DPE may vary due to their different configurations. User sends a processing request to DPE in order to get process. A request may include multiple tasks. It is always suitable that all the tasks must be process within least possible time frame along with maximum accuracy of data. Hence performance of the DPE can improve and it can be achieve by reducing processing time. In DPE, a process request may include multiple modules of a single task and proper assignments of these modules on processors involved in distributed processing environment are main aspects to enhance the performance of DPE. If tasks counts are equal to or less than available processors counts, tasks can be assigned without any trouble. Problem arises when the task counts are greater than available processors counts in DPE. The problem of allocation of `m' tasks on `n' number of processors in DPE is discussed here through a optimize task allocation method. The task allocation method, discussed in this research paper assign the tasks to the heterogeneous processing environment to optimize the performance of the DPE. Allocation method presented in this research paper is also ensuring allocation of each task according processor's availability in DPE.
For the operation and management of Complex Pipe Network System in marine engine room, a stable, accurate and intelligent simulation and control theory is presented. By using computer distributed processing technology, a distributed processing approach based on message platform is adopted. It can distribute every pipe network system in engine room to corresponding processing unit according to different functions or fluid's physical properties. The distributed interactive simulation is achieved by “Object Activation” in a unified messaging system on server-side. The key technology are modeling for Complex Pipe Network System, linear calculating for the relation between pressure and flow of fluid, release and access to Remote Object and implementation of distributed processing of computer.
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