Aim & Scope
The 2026 Conference on Advanced Topics and Auto-Tuning in High-Performance Scientific Computing (ATAT 2026) continues the series’ mission to provide a focused forum for discussing recent progress and emerging challenges in high-performance scientific computing. The conference aims to bring together researchers and practitioners from academia, laboratories, and industry to share their latest achievements in algorithm design, performance modeling, system optimization, and auto-tuning techniques for complex computational systems. Building upon the themes of previous years, ATAT 2026 places particular emphasis on integrating artificial intelligence (AI), machine learning, and data-driven approaches into performance optimization and adaptive computation across heterogeneous architectures, including multi-core CPUs, GPUs, and domain-specific accelerators. A new and distinctive highlight of this year’s conference is the inclusion of a dedicated session on quantum computing, covering topics such as quantum algorithms, quantum–classical hybrid workflows, quantum circuit optimization, and performance characterization of quantum architectures. The conference welcomes contributions that explore algorithm–architecture co-design, performance portability, and energy efficiency, as well as innovative auto-tuning methods that enhance robustness, scalability, and reproducibility in next-generation scientific and engineering applications.

Conference Website:

https://sites.google.com/site/atathpsc/2026