Understanding the behavior of software in execution is a key step in identifying and fixing
performance issues. This is especially important in high performance computing contexts …

With the rapid accumulation of text data produced by data-driven techniques, the task of
extracting" data annotations"—concise, high-quality data summaries from unstructured raw …

Distributed query processing systems such as Apache Hive and Spark are widely-used in
many organizations for large-scale data analytics. Analyzing and understanding the query …

Historically, scientific computing efforts have demonstrated the clear need for, and effective
use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are …

Understanding and tuning the performance of extreme-scale parallel computing systems
demands a streaming approach due to the computational cost of applying offline algorithms …

The recent development in the data analytics field provides a boost in production for modern
industries. Small-sized factories intend to take full advantage of the data collected by …

The ability to monitor and interpret hardware system events and behaviors is crucial to
improving the robustness and reliability of these systems, especially in a supercomputing …

随着科技飞速发展, 超级计算机系统不断向着更大规模迈进, 给系统使用和维护带来困难.
可视化技术以直观易懂的方式展示超级计算机系统的运行状态, 异常情况等 …

The ability to monitor and interpret of hardware system events and behaviors are crucial to
improving the robustness and reliability of these systems, especially in a supercomputing …

Mobile health involves gathering smartphone-sensor data passively from user's phones, as
they live their lives' In-the-wild”, periodically annotating data with health labels. Such data is …