Optimizing mobile multimedia using SIMD techniques

Demand for mobile video applications is growing today in wireless handheld platforms. Optimizing instruction set architectures and employing SIMD techniques is a logical approach towards attaining higher performance in mobile multimedia applications. Intel? Wireless MMX™ technology has been designed to accelerate mobile multimedia and applications processing in a power efficient manner. This paper provides an overview of Intel? Wireless MMX™ technology, a 64-bit Single Instruction Multiple Data (SIMD) coprocessor for the Intel? XScale? microarchitecture, and the key features of the architecture that specifically enhance the multi-media performance. Tools and techniques for optimization are also described. Nigel C. Paver has 13 years experience with the ARM architecture, and in the Intel PCA Components group in Austin, Texas, he is responsible for the architecture and implementation of multimedia coprocessors for the Intel XScale micro-architecture. He is also involved in product architecture and definition of Intel PCA processors. Before Intel, Nigel was one of the lead designers of the early AMULET asynchronous ARM microprocessors at the University of Manchester. He was also vice president in a startup company which used asynchronous design techniques to produce a low-power asynchronous DSP core. Nigel holds a Master of Science degree and Ph.D. in computer science from the University of Manchester and a Bachelor of Science degree in electronics from UMIST. Moinul Khan is a multimedia product architect at Intel Corporation PCA Components group. He is responsible PCA graphics and security architecture. His research interests are virtual prototyping, signal processing algorithms and architecture and communications networking. Before joining Intel he was a technology specialist and founding member of a startup at ATDC, Georgia. He worked on his doctoral research at Georgia Center for Advanced Telecommunications Technology at Georgia Institute of Technology. He received his B.Tech form Indian Institute of Technology and MSEE from Georgia Tech. He also worked as a research member for Canadian Institute for Telecommunications Research and Bell Communications Laboratories. Bradley C. Aldrich joined Intel in 1997 where he is currently an architect within the PCA Components Group. His current work includes the development of coprocessor instruction support in addition to image capture and display technologies for XScale based application processors. He was previously a member of the Intel/Analog Devices joint development architecture team responsible for video enhancements for the Micro Signal Architecture. Prior to that he was a video system architect in Intel's Digital Imaging and Video Division working on CMOS sensors, still cameras, and tethered PC based video peripherals. He has also worked as a device engineer for Motorola and as a test engineer for Tektronix. He received a BSEE in 1988 and MSEE in 1994 from the University of Texas at San Antonio.     

Optimizing mobile multimedia using SIMD techniques

Demand for mobile video applications is growing today in wireless handheld platforms. Optimizing instruction set architectures and employing SIMD techniques is a logical approach towards attaining higher performance in mobile multimedia applications. Intel® Wireless MMX? technology has been designed to accelerate mobile multimedia and applications processing in a power efficient manner. This paper provides an overview of Intel® Wireless MMX? technology, a 64-bit Single Instruction Multiple Data (SIMD) coprocessor for the Intel® XScale® microarchitecture, and the key features of the architecture that specifically enhance the multi-media performance. Tools and techniques for optimization are also described.     

A multilevel computing architecture for embedded multimedia applications

We have designed a new architecture that simplifies integration of heterogeneous IP for multimedia and streaming applications. The multilevel computing architecture (MLCA) is a template architecture featuring multiple processing units. This template architecture for SOC systems uses superscalar techniques to exploit task-level parallelism among different processing units. It supports a natural programming model that relieves programmers from explicitly synchronizing tasks and communicating data. code transformations that improve application performance are easy to incorporate in compilers for this architecture.     

Artificial intelligence in multimedia computing

Multimedia Tools and Applications -     

A user-centric network communication broker for multimedia collaborative computing

The development of collaborative multimedia applications today follows a vertical development approach, where each application is built on top of low-level network abstractions such as the socket interface. This stovepipe development process is a major inhibitor that drives up the cost of development and slows down the innovation pace of new generations of communication applications. In this paper, we propose a network communication broker (NCB) that provides a unified higher-level abstraction for the class of multimedia collaborative applications. We demonstrate how NCB encapsulates the complexity of network-level communication control and media delivery, and expedites the development of applications with various communication logics. We investigate the minimum necessary requirements for the NCB abstraction. We identify that the concept of user-level sessions involving multiple parties and multiple media, is critical to designing a reusable NCB to facilitate next-generation multimedia communications. Furthermore, the internal design of NCB decouples the user-level sessions from network-level sessions, so that the NCB framework can accommodate heterogeneous networks, and applications can be easily ported to new network environments. In addition, we demonstrate how the extensible and self-managing design of NCB supports dynamic adaptation in response to changes in network conditions and user requirements.     

Cognitive computing for intelligent multimedia systems

Multimedia Tools and Applications -     

A novel soft computing method for engine RUL prediction

Prognostics is an engineering discipline focused on predicting the Remaining Useful Life (RUL) of a system or a component using raw multimedia (sensor) data. This paper presents a novel machine learning model for this task, which includes a smart ensemble of gradient boosted trees (GBT) and feed-forward neural networks. It incorporates discussions on the poor performance of MLPs and the need of ensemble models. Initial stages of data exploration and pre-processing are also comprehensively documented. Experiments are performed on the four run-to-failure C-MAPSS datasets defined by the 2008 PHM Data Challenge Competition. It concludes by presenting evaluations of multiple prediction models like MLP, SVR, CNN & gradient boosted trees (GBT). Gradient Boosted Trees are efficient in the sense that they produce an encouraging scoring model with minimum effort and also return feature importance information. The proposed method uses stacking ensemble of feed-forward neural networks and gradient boosted trees, as first level learner, and, a single-hidden layer- fully-connected neural network as the meta learner. This ensemble provides better results than any of the models alone or weighted average of their predictions. The proposed method outperforms MLP, SVR, CNN and GBT.

     

A cost-effective cloud computing framework for accelerating multimedia communication simulations

Multimedia communication research and development often requires computationally intensive simulations in order to develop and investigate the performance of new optimization algorithms. Depending on the simulations, they may require even a few days to test an adequate set of conditions due to the complexity of the algorithms. The traditional approach to speed up this type of relatively small simulations, which require several develop–simulate–reconfigure cycles, is indeed to run them in parallel on a few computers and leaving them idle when developing the technique for the next simulation cycle. This work proposes a new cost-effective framework based on cloud computing for accelerating the development process, in which resources are obtained on demand and paid only for their actual usage. Issues are addressed both analytically and practically running actual test cases, i.e., simulations of video communications on a packet lossy network, using a commercial cloud computing service. A software framework has also been developed to simplify the management of the virtual machines in the cloud. Results show that it is economically convenient to use the considered cloud computing service, especially in terms of reduced development time and costs, with respect to a solution using dedicated computers, when the development time is longer than one hour. If more development time is needed between simulations, the economic advantage progressively reduces as the computational complexity of the simulation increases.     

A parallel computing engine for a class of time critical processes

This paper focuses on the efficient parallel implementation of systems of numerically intensive nature over loosely coupled multiprocessor architectures. These analytical models are of significant importance to many real-time systems that have to meet severe time constants. A parallel computing engine (PCE) has been developed in this work for the efficient simplification and the near optimal scheduling of numerical models over the different cooperating processors of the parallel computer. First, the analytical system is efficiently coded in its general form. The model is then simplified by using any available information (e.g., constant parameters). A task graph representing the interconnections among the different components (or equations) is generated. The graph can then be compressed to control the computation/communication requirements. The task scheduler employs a graph-based iterative scheme, based on the simulated annealing algorithm, to map the vertices of the task graph onto a Multiple-Instruction-stream Multiple-Data-stream (MIMD) type of architecture. The algorithm uses a nonanalytical cost function that properly considers the computation capability of the processors, the network topology, the communication time, and congestion possibilities. Moreover, the proposed technique is simple, flexible, and computationally viable. The efficiency of the algorithm is demonstrated by two case studies with good results.     

Data compression in multimedia computing — principles and techniques

Integrated multimedia systems process text, graphics, and other discrete media as well as digital audio, and video data. Considerable amounts of graphics, audio and video data in their uncompressed form, especially moving pictures, require storage and digital network capacities that will not be available in the near future. Nevertheless, local, as well as networked, multimedia applications and systems have become realities. In order to cope with these storage and communication requirements in such integrated multimedia systems, compression technology is essential. This papers starts with a brief motivation of the need for compression and subsequently states the essential requirements for these techniques in the scope of multimedia systems and applications. As most of these techniques apply the same principles, namely, the source, entropy, and hybrid coding fundamentals, these are explained in detail. Based on a general framework of the steps encountered in a compression system — data preparation, processing, quantization, and entropy coding — this paper outlines details about the techniques developed by CCITT (H.261, i.e., px64), in the ISO/IEC (JPEG, MPEG) standardization bodies and the proprietary DVI system.     

A personalized cloud engine for multimedia search based on binary ant colony algorithm

Multimedia Tools and Applications - At present, the search content and results of common multimedia search engines have gradually failed to meet the personalized search requirements of users. The...     

Soft computing techniques and applications for intelligent multimedia systems

Multimedia Tools and Applications -     

Data compression in multimedia computing — standards and systems

Note. There are several ways to order the mentioned Standards of ISO. In the US, for example, one may call ANSI (212-642-4900) or Global Engineering Documents, Washington, DC (800-854-7179)     

Intelligent multimedia big data computing for internet of things

Multimedia Tools and Applications -     

云计算环境下实时流媒体业务的性能研究

由于虚拟化环境不同于常规的物理集群,流媒体业务迁移至云中后会遇到问题。针对这一现象,搭建私有云环境,部署流媒体系统,进行一系列性能测试和研究。实验结果表明,在引入了虚拟化环境后,由于无法有效进行资源隔离以及共存虚拟机的存在,流媒体业务的性能明显下降,分析结果为进一步深入研究云环境下如何有效提高流媒体业务的性能奠定了很好的基础。