High performance computing (HPC)

Summary

Architectures, algorithms, applications in the area of high performance computing.

We run many HPC-related projects; our research activities and topics of interest include: - multi-core CPUs and NUMA servers - many-core GPUs and GPGPU computing - emerging parallel architectures - distributed computing on tightly coupled clusters - parallel data processing and concurrency in database systems - programming languages and compilers for parallel data processing

People

Jakub Yaghob

Collaborator

David Bednárek

Lecturer

Filip Zavoral

Scientific secretary, Lecturer

Latest publications

• Tapestry: Revealing Wait-For Dependencies Between Application Threads (2025)
• Maboss for HPC environments: implementations of the continuous time Boolean model simulator for large CPU clusters and GPU accelerators (2024)
• Astute Approach to Handling Memory Layouts of Regular Data Structures (2023)
• Distributed Asynchronous Regular Path Queries (RPQs) on Graphs (2023)
• Better Distributed Graph Query Planning With Scouting Queries (2023)
• aDFS: An Almost Depth-First-Search Distributed Graph-Querying System (2021)
• GPU-Accelerated Mahalanobis-Average Hierarchical Clustering Analysis (2021)
• Letting future programmers experience performance-related tasks (2021)
• Detailed Analysis and Optimization of CUDA K-means Algorithm (2020)
• GigaSOM.jl: High-performance clustering and visualization of huge cytometry datasets (2020)
• Improving matrix-based dynamic programming on massively parallel accelerators (2017)

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