An Efficient Transport Protocol for delivery of Multimedia An Efficient Transport Protocol for delivery of Multimedia Content in Wireless Grids

A grid computing system is designed for solving complicated scientific and commercial problems effectively,whereas mobile computing is a traditional distributed system having computing capability with mobility and adopting wireless communications. Media and Entertainment fields can take advantage from both paradigms by applying its usage in gaming applications and multimedia data management. Multimedia data has to be stored and retrieved in an efficient and effective manner to put it in use. In this paper, we proposed an application layer protocol for delivery of multimedia data in wireless girds i.e. multimedia grid protocol (MMGP). To make streaming efficient a new video compression algorithm called dWave is designed and embedded in the proposed protocol. This protocol will provide faster, reliable access and render an imperceptible QoS in delivering multimedia in wireless grid environment and tackles the challenging issues such as i) intermittent connectivity, ii) device heterogeneity, iii) weak security and iv) device mobility.Comment: 20 pages, 15 figures, Peer Reviewed Journa

Automatic visual recognition using parallel machines

Invariant features and quick matching algorithms are two major concerns in the area of automatic visual recognition. The former reduces the size of an established model database, and the latter shortens the computation time. This dissertation, will discussed both line invariants under perspective projection and parallel implementation of a dynamic programming technique for shape recognition. The feasibility of using parallel machines can be demonstrated through the dramatically reduced time complexity. In this dissertation, our algorithms are implemented on the AP1000 MIMD parallel machines. For processing an object with a features, the time complexity of the proposed parallel algorithm is O(n), while that of a uniprocessor is O(n2). The two applications, one for shape matching and the other for chain-code extraction, are used in order to demonstrate the usefulness of our methods. Invariants from four general lines under perspective projection are also discussed in here. In contrast to the approach which uses the epipolar geometry, we investigate the invariants under isotropy subgroups. Theoretically speaking, two independent invariants can be found for four general lines in 3D space. In practice, we show how to obtain these two invariants from the projective images of four general lines without the need of camera calibration. A projective invariant recognition system based on a hypothesis-generation-testing scheme is run on the hypercube parallel architecture. Object recognition is achieved by matching the scene projective invariants to the model projective invariants, called transfer. Then a hypothesis-generation-testing scheme is implemented on the hypercube parallel architecture

Design and resource management of reconfigurable multiprocessors for data-parallel applications

FPGA (Field-Programmable Gate Array)-based custom reconfigurable computing machines have established themselves as low-cost and low-risk alternatives to ASIC (Application-Specific Integrated Circuit) implementations and general-purpose microprocessors in accelerating a wide range of computation-intensive applications. Most often they are Application Specific Programmable Circuiits (ASPCs), which are developer programmable instead of user programmable. The major disadvantages of ASPCs are minimal programmability, and significant time and energy overheads caused by required hardware reconfiguration when the problem size outnumbers the available reconfigurable resources; these problems are expected to become more serious with increases in the FPGA chip size. On the other hand, dominant high-performance computing systems, such as PC clusters and SMPs (Symmetric Multiprocessors), suffer from high communication latencies and/or scalability problems. This research introduces low-cost, user-programmable and reconfigurable MultiProcessor-on-a-Programmable-Chip (MPoPC) systems for high-performance, low-cost computing. It also proposes a relevant resource management framework that deals with performance, power consumption and energy issues. These semi-customized systems reduce significantly runtime device reconfiguration by employing userprogrammable processing elements that are reusable for different tasks in large, complex applications. For the sake of illustration, two different types of MPoPCs with hardware FPUs (floating-point units) are designed and implemented for credible performance evaluation and modeling: the coarse-grain MIMD (Multiple-Instruction, Multiple-Data) CG-MPoPC machine based on a processor IP (Intellectual Property) core and the mixed-mode (MIMD, SIMD or M-SIMD) variant-grain HERA (HEterogeneous Reconfigurable Architecture) machine. In addition to alleviating the above difficulties, MPoPCs can offer several performance and energy advantages to our data-parallel applications when compared to ASPCs; they are simpler and more scalable, and have less verification time and cost. Various common computation-intensive benchmark algorithms, such as matrix-matrix multiplication (MMM) and LU factorization, are studied and their parallel solutions are shown for the two MPoPCs. The performance is evaluated with large sparse real-world matrices primarily from power engineering. We expect even further performance gains on MPoPCs in the near future by employing ever improving FPGAs. The innovative nature of this work has the potential to guide research in this arising field of high-performance, low-cost reconfigurable computing. The largest advantage of reconfigurable logic lies in its large degree of hardware customization and reconfiguration which allows reusing the resources to match the computation and communication needs of applications. Therefore, a major effort in the presented design methodology for mixed-mode MPoPCs, like HERA, is devoted to effective resource management. A two-phase approach is applied. A mixed-mode weighted Task Flow Graph (w-TFG) is first constructed for any given application, where tasks are classified according to their most appropriate computing mode (e.g., SIMD or MIMD). At compile time, an architecture is customized and synthesized for the TFG using an Integer Linear Programming (ILP) formulation and a parameterized hardware component library. Various run-time scheduling schemes with different performanceenergy objectives are proposed. A system-level energy model for HERA, which is based on low-level implementation data and run-time statistics, is proposed to guide performance-energy trade-off decisions. A parallel power flow analysis technique based on Newton\u27s method is proposed and employed to verify the methodology

Semiannual final report, 1 October 1991 - 31 March 1992

A summary of research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, numerical analysis, and computer science during the period 1 Oct. 1991 through 31 Mar. 1992 is presented

THE VLIW-SUPERCISC COMPILER: EXPLOITINGPARALLELISM FROM C-BASED APPLICATIONS

A common approach to decreasing embedded application execution time is creating a homogeneous parallel processor architecture. The parallelism of any such architecture is limited to the number of instructions that can be scheduled in the same cycle. This number of instructions scheduled in a cycle, or instruction-level parallelism (ILP), is limited by the ability to extract parallelism from the application. Other techniques attempt to improve performance with hardware acceleration. Often, segments of highly computational extensive code are extracted and custom hardware is created to replace the software execution. This technique requires many resources and still does not address the segments of code outside of the computationally extensive kernel.To solve this problem, hardware acceleration for computationally intensive segments of code in addition to accelerating the entire application with very long instruction word, VLIW, techniques is proposed. (1) A compilation flow that targets a 4-wide VLIW processor architecture is presented. This system was used to investigate the available speed-up of VLIW architectures. The architecture was modified to combine the VLIW processor with the capability to execute application specific customized instructions. To create the custom instruction hardware, a control and data flow graph (CDFG) framework was created. The CDFG framework was created to provide a framework for compiler transformations and hardware generation. In order to remove control flow from segments of code selected for hardware generation, (2) the technique of hardware predication was developed. Hardware predication allows if-then and if-then-else control flow constructs to be transformed into strict data flow through the use of multiplexors. From the transformed CDFGs, (3) a VHDL generation pass was created that translates the compiler data structures into synthesizable VHDL. The resulting architecture contains the VLIW processor and tightly coupled application specific hardware. This architecture was analyzed for performance changes comparedto the initial VLIW architecture, and a traditional processor. Lastly, (4) the architecture was analyzed for power and energy savings. A post static timing pass was added to the compilation flow for the insertion of hardware to delay early switching of operations.By measuring only the execution of the hardware function and comparing the performance to the equivalent code executed in software, a performance multiplier of up to 322 times is seen when synthesized onto an Altera Stratix II ES2S180F1508C4 FPGA. The average performance increase seen was 63 times faster. For the entire application, the speedup reached nearly 30X and was on average 12X better than a single processor implementation. The power and energy required by the VLIW processor core and the hardware functions for the computational kernels after 160nm OKI standard cell ASIC synthesis show a maximum power savings of 417 times that of execution on the processor with an average of 133 times savings in power consumption. With the increased execution time and the savings in power the energy savings will see a multiplicative effect. The energy improvement is therefore several orders of magnitude for the hardware functions, the savings range from over 1,000X to approximately 60,000X