Description
Chairperson: Kevin Sala, BSC
Interactive exploration and analysis of large amounts of data from scientific simulations, in-situ visualization and application control are convincing scenarios for explorative sciences. It is the task of High-Performance Computing (HPC) Centers to enable, support and, of course, simplify these workflows of our users of today's supercomputers. Especially technical work simplifications in...
Python is emerging as a high-productivity language favored by many application scientists and engineers in simulation/modeling, data analytics, and machine learning. Interactive parallel computing is another related trend, especially for analyzing graphs in addition to the above. The CharmTyles project is aimed at addressing these needs while providing a highly efficient and adaptive parallel...
Data is messy. What’s more, the most tantalizing data to study is often that which is new and has not attracted attention yet. This tends to be the messiest. One of the major driving forces in the popularity of interactive programming is the ability to be flexible with an unknown data-space. Environments such as Jupyter Notebooks have become ubiquitous in data analysis for this reason. And...
The Blue Waters system and project was one of the measured and monitored system at scale. Now, over a Petabyte of monitoring, system activity, reliability, security, networking and performance data is available for the researchers to use for its entire operational period of over 9 years. This talk will summarize the types of data available and possible open questions that collaborators may...
With the growth and evolution of supercomputers and the incorporation of diverse technologies, monitoring their usage has become a vital necessity for administrators and users altogether. In this context, LLview monitoring structure, developed by the Jülich Supercomputing Centre, stands out for providing extensive views on the system and job operations. The recently-released new version of...
Process mapping (or process placement) is a useful algorithmic technique to optimize the way applications are launched and executed onto a parallel machine. By taking into account the topology of the machine and the affinity between the processes, process mapping helps reducing the communication time of the whole parallel application. Here, we present TopoMatch, a generic and versatile library...
With an increasing workload diversity and hardware complexity in HPC, the boundaries of today's runtimes are pushed to their limits. This evolution needs to be matched by corresponding increases in the capabilities of system management solutions.
Power management is a key element in the upcoming exascale era. First to allow us to stay within the power budget, but also for the applications...
