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More engaging and accessible solutions that offer outstanding user experience are needed. The virtual desktop infrastructure (VDI) is the first user access part of the cloud. Therefore, the performance of the VDI has a significant influence on the network. The graphics processing unit (GPU) can accelerate performance by assigning each virtual machine a dedicated GPU for performance-boosting to improve the user experience. In this paper, we propose a high-performance VDI using an integration of a GPU on OpenStack with a PCI pass-through. It might have certain benefits over using virtualized hardware, such as lower latency, better performance, and more functionality. The evaluation and comparison of the computer processing unit (CPU) and GPU are presented among the different benchmark tools.

In recent years, Information industry trends gradually towards the clouds. Various clouds are related technologies and applications are growing with the popularity of cloud technology. While cloud virtual desktop is the first user access part of the cloud and the performance of cloud virtual desk of the network and GPU has been implicated. A smooth cloud virtual desktop is a very important issue in this environment. In this study, we proposed an integration of GPU on OpenStack and through PCI Pass-Through way to solve the problem of virtual machine display performance by allocating GPU resources for virtual machine. For the experimental, we will use different benchmarking software to measure the virtual machine. In the experiment, adjust the different number of vCPUs to measure the different cases performance of the FPS virtual machine (Frame per Second). Through this experimentation, we found out there are three different processing drivers for the virtual desktop.

Geologic sequestration of carbon dioxide (CO2) in deep saline aquifers is one of the most feasible techniques for mitigating the greenhouse effect. However, over-optimistic design of CO2 injection scheme may adversely overwhelm the sealing capability of the cap-rock in the saline reservoir. In this study, we have developed a complex three-dimensional heterogeneous model to study the spatial and temporal distribution and storage of CO2 injection into the saline aquifer structure at Taiwan western offshore. For investigating the mechanisms of CO2 migration in a deep saline reservoir, which was hypothesized as a sequestration site, the result of numerical simulations was analyzed. Numerical simulation of CO2 migration in geologic formations can provide key information for predicting CO2 plumes before conducting field-scale operations or pilot tests. In order to avoid the problems of overpressure in the saline reservoir, the case study employs multi-well injection strategies. The sensitivity analyses based on the two different injection strategies in the western sea of Taiwan show that the locations of CO2 plume front might be from hundreds of meters to kilometers.

This work focuses on how to provide the best virtual desktop technology, virtualization performance and hardware in the computer classroom. There are using the three popular virtualization technologies in the same environment to establish the same conditions, pure performance comparison: VMware Horizon, Citrix XenDesktop, and Microsoft VDI. Test software used to the current popular software, system performance including a test CPU and RAM PassMark Performance Test,and observe the vCenter Server performance changes and record statistics, to determine the advantages and disadvantages of various virtualization technologies. Finally, hardware support exclusive GPU virtualization product - Nvidia GRID K2 through GPU virtualization technology sharing and vGPU to carry on VMware vSphere, via Cinebench, YouTube 1080p high-quality video for bandwidth flow test, and use 3DMark Fire Strike Extreme to enhance the performance of virtual desktop, and bring users to enjoy higher-quality cloud services. The results of this study show that virtual desktop technologies are good in different field. On the other hand, the hardware performance breakthrough Moore’s Law of this era, the single CPU has more number of cores, and the memory capacity of the larger single,and provided by the GPU for graphics acceleration processing capabilities, the performance of server has been perfect than the previous. Therefore, the quality of cloud services is also greatly improved. The study shows that the virtual test can be imported into the classroom through the stress test in the experiment. To make sure the its performance and cost are really suitable for classroom imported desktop virtualization system.

Carbon-Dioxide Capture and Storage (CCS) in deep saline aquifers is one of the most feasible techniques for reducing anthropogenic emission of carbon dioxide (CO2). In this paper, a high-performance parallel computing is used to simulate the large-scale and long-term CO2 geologic storage in the saline aquifer (Sleipner Vest field in the Norwegian) based on the ECO2N module of the flow/transport simulator TOUGH2-MP, which is the parallel version of TOUGH2 implemented by the MPI. We have developed a complex three-dimensional heterogeneous model to study the spatial and temporal distribution and storage of CO2 injection into the sands of the Utsira formation, at the Sleipner Vest field in the Norway. Simulation results demonstrate that the high-speed parallel computing enhanced the capability on handling the large-scale model and the long-term studies. Furthermore, in order to avoid the problems of overpressure in the saline reservoir, the case study employs multi-well (ten-well) injection model, which has been proven to be able to reduce the reservoir pressure effectively when compared to the single-well injection model.

A cluster is a collection of independent and cheap machines, used together as a supercomputer to provide a solution. In this paper, a PC cluster consisting of one master node and nine disk-less slave nodes (10 processors), is proposed and built for parallel rendering purposes. The system architecture and benchmark performances of this cluster are also presented. Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. Harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. Also, in this paper, we construct two heterogeneous PC clusters for parallel rendering purpose and install Linux Red Hat 9 on each PC cluster. Then, these clusters are set to the different subnet. Therefore, we use the grid middleware lambdaobus ToolKit, to connect these two clusters to form a grid computing environment on multiple Linux PC clusters. We also install the SUN Grid Engine, to manage and monitor incoming or outgoing computing jobs and schedule the job to achieve high performance computing and high CPU utilization. The system architecture and benchmark performances of this cluster are also presented

Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. The computational analysis of biological sequences is a kind of computation driven science. Cause the biology data growing quickly and these databases are heterogeneous. We can use the grid system sharing and integrating the heterogeneous biology database. As we know, bioinformatics tools can speed up analysis the large-scale sequence data, especially about sequence alignment. The FASTA is a tool for aligning multiple protein or nucleotide sequences. FASTA which we used is a distributed and parallel version. The software uses a message-passing library called MPl (Message Passing Interface) and runs on distributed workstation clusters as well as on traditional parallel computers. A grid computing environment is proposed and constructed on multiple Linux PC clusters by using Globus Toolkit (GT) and SUN Grid Engine (SGE). The experimental results and performances of the bioinformatics tool using on grid system are also presented in this paper.

As Grid Computing is becoming a reality, there is a need for managing and monitoring the available resources worldwide, as well as the need for conveying these resources to the everyday user. This paper describes a resource broker with its main function as to match the available resources to the user’s needs. The use of the resource broker provides a uniform interface to access any of the available and appropriate resources using user’s credentials. The resource broker runs on top of the Globus Toolkit. Therefore, it provides security and current information about the available resources and serves as a link to the diverse systems available in the Grid.

Internet computing and grid technologies promise to change the way we tackle complex problems. They will enable large-scale aggregation and sharing of computational, data and other resources across institutional boundaries. And harnessing these new technologies effectively will transform scientific disciplines ranging from high-energy physics to the life sciences. In this paper, a grid computing environment is proposed and constructed on multiple PC clusters by using Globus Toolkit (GT) and SUN Grid Engine (SGE). The experimental results are also conducted by using the matrix multiplication to demonstrate the performance. On the other hand, the approaches to deal with scheduling and load balancing on multiple heterogeneous PC clusters computer system are not mature. Self-scheduling schemes which are suitable for parallel loops with independent iterations on heterogeneous cluster computer system have been designed in the past. However, these schemes, such as FSS, GSS and TSS, can not achieve load balancing in extremely heterogeneous environment. We propose a heuristic approach based upon a two-phase scheme to solve parallel regular loop scheduling problem on an extremely heterogeneous grid computing environment.

Grid environment allows sharing of a large amount of idle resources of compute and other available information. Accordingly, we have set up the BioGrid for computing resources by combining grid technology with parallel bioinformatics applicable software in erecting the BioGrid computing platform. In one instance for example, biology data which is heterogeneous and grows rapidly, we plan to integrate and share it using grid technology. In this paper, the FASTA applicable software is used to test and analyse the grid environment to reduce time and improve efficacy. The experimental results and performances of the bioinformatics tool use on the grid system are also presented in this paper.