Single system image: A survey

Single system image is a computing paradigm where a number of distributed computing resources are aggregated and presented via an interface that maintains the illusion of interaction with a single system. This approach encompasses decades of research using a broad variety of techniques at varying levels of abstraction, from custom hardware and distributed hypervisors to specialized operating system kernels and user-level tools. Existing classification schemes for SSI technologies are reviewed, and an updated classification scheme is proposed. A survey of implementation techniques is provided along with relevant examples. Notable deployments are examined and insights gained from hands-on experience are summarized. Issues affecting the adoption of kernel-level SSI are identified and discussed in the context of technology adoption literature

ANALISIS IMPLEMENTASI PC (Personal Computer) CLUSTERING BERBASIS SSI (Single System Image) IMPLEMENTATION ANALYSIS OF CLUSTERING PC (Personal Computer) BASED ON SSI (Single System Image)

ABSTRAKSI: Permintaan akan suatu sistem yang mempunyai HPC (High Performance Computing) merupakan dampak dari perkembangan teknologi komputer. Dengan dukungan teknologi hardware dan software, berbagai aplikasi dapat dikembangkan. HPC diperlukan untuk mendukung berbagai aplikasi yang ada terutama aplikasi yang membutuhkan proses komputasi secara cepat. Dengan adanya HPC ini, proses komputasi dapat diakselerasi sehingga task bisa diselesaikan dengan cepat.Teknologi clustering menawarkan untuk menciptakan suatu sistem yang memiliki HPC. Selain solusi dari sisi teknologi, clustering juga merupakan solusi dari sisi ekonomi karena memerlukan biaya yang murah dibandingkan harus membeli sebuah mainframe. Clustering merupakan kombinasi dari beberapa node yang digunakan untuk menyelesaikan suatu task. Beberapa node tersebut dapat berupa beberapa PC tetapi dapat juga sebuah komputer dengan ratusan atau ribuan processor yang membentuk suatu cluster.Dengan implementasi teknologi clustering berbasis SSI kedalam beberapa PC pada tugas akhir ini, akan diperoleh suatu gabungan beberapa node atau PC menjadi satu kesatuan yaitu kesatuan resource untuk melakukan proses komputasi terhadap suatu task.Hasil dari implementasi ini akan dihasilkan suatu sistem cluster yang memiliki kemampuan menyelesaikan proses komputasi dengan load balancing dan kesatuan management system sehingga resource semua node dapat diatur untuk memperoleh kemampuan komputasi dengan performasi yang tinggi.Kata Kunci : ABSTRACT: The request about the system that have HPC (High Performance Computing) is consequence from the growth of computer technology. By support of hardware and software technology, kinds of application can be developed. HPC is needed to support applications especially application which need computing process quickly. By this HPC, computing process can be accelerated so that the task can be finished quickly.Clustering technology offer to create a system that have HPC. Besides the technology solution, clustering is the economic solution too because need cheap cost than must buy a mainframe. Clustering is a combination of nodes that used to finish the task. That some nodes can be some PCs but also can be a computer with hundreds or thousands of processors that form a cluster.By the implementation of clustering technology base on SSI into some PCs in this thesis, will be got a union some nodes or PCs become one unity that is resource unity to do computing process to the task.The result of this implementation will be resulted a cluster system that heve ability to finish computing process with load balancing and the unity of management system so that resources of all nodes can be organized to get computing ability with high performance.Keyword

Single frame super-resolution image system

The estimation of some unknown quantity information from known observable information can be viewed as a specific statistical process which needs an extra source of information prediction strategy. In this regard, image super-resolution is an important application In this thesis, we proposed a new image interpolation method based on Redundant Discrete Wavelet Transform (RDWT) and self-adaptive processes in which edge direction details are considered to solve single-frame image super-resolution task. Information about sharp variations, both in horizontal and vertical directions derived from wavelet transform sub-bands are considered, followed by detection and modification of the aliasing part in the preliminary output in order to increase the visual effect. By exploiting fundamental properties of images such as property of edge direction, different parts of the source image are considered separately in order to predict the vertical and horizontal details accurately, helping to consummate the whole framework in reconstructing the high-resolution image. Extensive tests of the proposed method show that both objective quality (PSNR) and subjective quality are obviously improved compared to several other state-of-the-art methods. And this work also leaved capacious space for further research, not only theoretical but also practical. Some of the related research applications based on this algorithm strategy are also briefly introduced