Yuyu Yin

Performance evaluation model of Web servers based on response time

The performance of a Web server is essential to Web services. An accuracy performance model can help us evaluate the performance of a Web server efficiently and effectively. We present evaluation mode—Web Server performance evaluation Model Based on the Response Time (for short, MBRT) to evaluate the peak load of a Web server with given configuration. It based on the special relationship between the response time and the throughput when the requests rate is lower than peak load. Compared to other models, MBRT is simple and effective and has been validated from both theoretical and empirical point of view in real environment.

Power Aware Resource Allocation in Virtualized Environments through VM Behavior Identification

Virtualization technology enables server and service consolidation to save more power and operational costs of large scale computing systems. However, the consolidation nature of virtualization intensifies the power densities in a rack, thus resulting in higher probability of failures and Service Level Agreements violations under constrained power budget. In this paper, we proposed a power aware resource allocation algorithm, named PaRA, to coordinate and tradeoff the power and performance. In order to provide enough information about power characteristics of individual VM and applications, we use agent for workload characterization and estimation. The real actuation of resource allocation is realized within the Virtual Machines Monitor (VMM). We evaluated our algorithm on a real Xen based virtualization environments with 3 VMs. The results show that the proposed approach can achieve a higher SLA satisfaction rate as 99.6 percent in RUBiS web application, and power consumption savings up to 17.6 percent compared to default Xen resource allocator. The results also show the potential of our algorithm to be used in real virtualization environments.

The novel implicit LU-SGS parallel iterative method based on the diffusion equation of a nuclear reactor on a GPU cluster

Abstract GPU not only is used in the field of graphic technology but also has been widely used in areas needing a large number of numerical calculations. In the energy industry, because of low carbon, high energy density, high duration and other characteristics, the development of nuclear energy cannot easily be replaced by other energy sources. Management of core fuel is one of the major areas of concern in a nuclear power plant, and it is directly related to the economic benefits and cost of nuclear power. The large-scale reactor core expansion equation is large and complicated, so the calculation of the diffusion equation is crucial in the core fuel management process. In this paper, we use CUDA programming technology on a GPU cluster to run the LU-SGS parallel iterative calculation against the background of the diffusion equation of the reactor. We divide one-dimensional and two-dimensional mesh into a plurality of domains, with each domain evenly distributed on the GPU blocks. A parallel collision scheme is put forward that defines the virtual boundary of the grid exchange information and data transmission by non-stop collision. Compared with the serial program, the experiment shows that GPU greatly improves the efficiency of program execution and verifies that GPU is playing a much more important role in the field of numerical calculations.