Hongbo Zou

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Increasingly severe I/O bottlenecks on High-End Computing machines are prompting scientists to process simulation output data online while simulations are running and before storing data on disk. There are several options to place data analytics along the I/O path: on compute nodes, on separate nodes dedicated to analytics, or after data is stored on(More)
The remote visual exploration of live data generated by scientific simulations is useful for scientific discovery, performance monitoring, and online validation for the simulation results. Online visualization methods are challenged, however, by the continued growth in the volume of simulation output data that has to be transferred from its source - the(More)
There are many challenges in analyzing and visualizing data from current cutting-edge general relativistic astrophysics simulations. Many of the associated tasks are time-consuming with large performance degradation due to the magnitude and complexity of the data. The Adaptable I/O System (ADIOS) is a componentization of the I/O layer that has demonstrated(More)
Recent technological advances are putting increased pressure on CPU scheduling. On one hand, processors have more cores. On the other hand, I/O systems have become more complex. Intensive research has been conducted on multi/many-core scheduling, however, most of the studies follow the conventional approach and focus on the utilization and load balance of(More)
Increasingly larger scale simulations are generating an unprecedented amount of data. However, the increasing gap between computation and I/O capacity on High End Computing machines makes a severe bottleneck for data analysis. As a solution, in-situ analytics processes output data while simulations are running and before placing data on disk. Data movement(More)
Resource discovery is a basic service in grid computing : gives a description of resources desired and finds the available one to match the description. In computational grid, how to discover resources efficiently has become a crucial factor to evaluate the performance in the whole system. In this paper, we present a bid-based resource discovery algorithm,(More)
a r t i c l e i n f o a b s t r a c t Increasingly larger scale applications are generating an unprecedented amount of data. However, the increasing gap between computation and I/O capacity on High End Computing machines makes a severe bottleneck for data analysis. Instead of moving data from its source to the output storage, in-situ analytics processes(More)
Increasingly larger scale simulations are generating an unprecedented amount of output data, causing researchers to explore new `data staging' methods that buffer, use, and/or reduce such data online rather than simply pushing it to disk. Leveraging the capabilities of data staging, this study explores the potential for data reduction via online data(More)
— Computing is now shifting towards multiprocessing. The fundamental goal of multiprocessing is improved performance through the introduction of additional hardware threads or cores (referred to as " cores " for simplicity). Modern network stacks can exploit parallel cores to allow either message-based parallelism or connection-based parallelism as a means(More)
Vitual Machine (VM) technology encapsulates shared computing resources into secure, stable, isolated and customizable private computing environments. While service-oriented computing becomes more and more a norm of computing, VM becomes a must-have common structure. However, creating and customizing a VM system on different hardware/software environments to(More)