The instrumentation and measurement framework Score-P, together with analysis tools build on top of its output formats, provides insight into massively parallel HPC applications, their communication, synchronization, I/O, and scaling behaviour to pinpoint performance bottlenecks and their causes.
DataLad is a tool for the joint management of code, data, and their relationship, built on top of the version control systems Git & git-annex. It adapts principles of open-source software development & distribution to address challenges of data management, data sharing, & digital provenance capture.
The Scalasca Trace Tools support performance optimization of parallel programs with a collection of highly scalable trace-based tools for in-depth analyses of concurrent behavior, in particular with respect to communication and synchronization, and offers guidance in exploring their causes.
Cube, which is used as performance report explorer for Scalasca and Score-P, is a generic tool for displaying a multi-dimensional performance space consisting of the dimensions (i) performance metric, (ii) call path, and (iii) system resource.
The PEPC project (Pretty Efficient Parallel Coulomb Solver) is a public tree code that has been developed at Jülich Supercomputing Centre since the early 2000s. Our code is a non-recursive version of the Barnes-Hut algorithm, using a level-by-level approach to both tree construction and traversals.
This AiiDA plugin provides high-throughput automation and FAIR data management for the Jülich KKR codes.
Massive-Parallel Trajectory Calculations (MPTRAC) is a Lagrangian particle dispersion model for the analysis of atmospheric transport processes in the free troposphere and stratosphere.
Cube, which is used as performance report explorer for Scalasca and Score-P, is a generic tool for displaying a multi-dimensional performance space consisting of the dimensions (i) performance metric, (ii) call path, and (iii) system resource.
Cube, which is used as performance report explorer for Scalasca and Score-P, is a generic tool for displaying a multi-dimensional performance space consisting of the dimensions (i) performance metric, (ii) call path, and (iii) system resource.
Heat is a flexible and seamless open-source software for high performance data analytics and machine learning. It provides highly optimized algorithms and data structures for tensor computations using CPUs, GPUs and distributed cluster systems on top of MPI.
JuPedSim is a framework designed to support students and researchers in investigating pedestrian dynamics and conducting research related to the development and validation of new models or model features. It enables the analysis of experiments and facilitates the proper visualization of results.
An open-source Python package, offering advanced AI methods for the identification and segmentation of biomedical objects, such as cells, in image data. Includes trained models that work out-of-the-box for a wide range of use cases.