In recent years, the Massively Parallel Computation (MPC) model has gained significant attention. However, most of distributed and parallel graph algorithms in the MPC model are designed for static ...

NVIDIA’s CUDA is a general purpose parallel computing platform and programming model that accelerates deep learning and other compute-intensive apps by taking advantage of the parallel processing ...

The class schedule, list of staff, the library documentation and the course book are availabe from the tabs above. The schedule includes lecture dates, due dates, links to quizes, and which chapters ...

Abstract: High-dimensional and incomplete (HDI) matrices are commonly encountered in various big data-related applications for illustrating the complex interactions among numerous entities, like the ...

├── notes/ # Theoretical concepts and explanations │ ├── 01_introduction/ # Basics of parallel computing │ ├── 02_gpu_architecture/ # GPU hardware fundamentals │ ├── 03_cuda_basics/ # CUDA programming ...

Ulrich Rüde studied mathematics and computer science, earning an MS from Florida State University and a PhD from TUM. From 1998–2025 he held the Chair of System Simulation at FAU Erlangen–Nürnberg, ...

Abstract: The rise of graph data in various fields calls for efficient and scalable community detection algorithms. In this paper, we present parallel implementations of two widely used algorithms: ...

This course focuses on developing and optimizing applications software on massively parallel graphics processing units (GPUs). Such processing units routinely come with hundreds to thousands of cores ...