Pavel Saviankou

• Dr. rer. nat.
• Researcher at Forschungszentrum Jülich

Software reliability is one of the cornerstones of any successful user experience. Software needs to build up the users’ trust in its fitness for a specific purpose. Software failures undermine this trust and add to user frustration that will ultimately lead to a termination of usage. Even beyond user expectations on the robustness of a software pa...

In the last couple of years, supercomputers became increasingly large and more and more complex. Performance analysis tools need to adapt to the system complexity in order to be used effectively at large scale. Thus, we introduced a plugin infrastructure in Cube 4, the performance report explorer for Score-P and Scalasca, which allows to extend Cub...

The Open image in new window Knights Landing processors offers unique features with regards to memory hierarchy and vectorization capabilities. To improve tool support within these two areas, we present extensions to the Score-P measurement infrastructure and the Cube report explorer. With the Knights Landing edition, Intel introduced a new memory...

Cube v3 has been a powerful tool to examine reports of the parallel performance tool Scalasca, but was basically unable to perform analyses on its own. With Cube v4, we addressed several shortcomings of Cube v3. We generalized the Cube data model, extended the list of supported data types, and allow operations with nontrivial algebras, e.g. for per...

Scalasca is a well-established open-source toolset that supports the performance optimization of parallel programs by measuring and analyzing their runtime behavior. The analysis identifies potential performance bottlenecks – in particular those concerning communication and synchronization – and offers guidance in exploring their causes. The latest...

This paper gives an overview about the Score-P performance measure-ment infrastructure which is being jointly developed by leading HPC performance tools groups. It motivates the advantages of the joint undertaking from both, the de-veloper and the user perspectives, and presents the design and components of the newly developed Score-P performance m...

The rapidly growing number of cores on modern supercomputers imposes scalability demands not only on applications but also on the software tools needed for their development. At the same time, increasing application and system complexity makes the optimization of parallel codes more difficult, creating a need for scalable performance-analysis techn...

Scalasca is an open-source toolset that can be used to analyze the performance behavior of parallel applications and to identify opportunities for optimization. Target applications include simulation codes from science and engineering based on the parallel programming interfaces MPI and/or OpenMP. Scalasca, which has been specifically designed for...

The two- and three-nucleon interaction derived in chiral effective field theory is used to obtain the binding energy of nuclear matter for small densities at next-to-leading (NLO) and next-to-next-to-leading orders (N2LO). The order N2LO is not yet sufficient to push the range of validity of the expansion beyond the empirical Fermi momentum of nuclear...

The two- and three-nucleon interaction derived in chiral effective field theory at next-to-next-to-leading order is used to obtain the binding energy of nuclear matter. Saturation is found at a binding energy per particle E/A = -16.2 \pm 0.3 MeV and a Fermi momentum k_F = 1.30 \pm 0.03 fm^{-1}, where the uncertainty is due to the cut-off dependence...

Effective field theory provides a systematic approach to hardon physics and few-nucleon systems. It allows one to determine the effective two-, three-, and more-nucleon interactions which are consistent with each other. We present a project to derive bulk properties of nuclei from the effective nucleonic interactions.