Chairs

Introduction

The exponential growth of data in High-Performance Computing (HPC) simulations has exposed severe I/O bottlenecks in traditional offline post-processing. To address these challenges, this track, titled "Scalable Pre-processing and Visual Analytics for High-Performance Computing", focuses on optimizing the end-to-end computational pipeline. We seek cutting-edge algorithmic innovations for scalable data preparation, including parallel mesh generation and distributed discretization. Furthermore, to facilitate insights from massive datasets, we welcome breakthroughs in advanced visual computing paradigms, such as in-situ/in-transit visualization, remote data streaming, and high-performance rendering. Ultimately, this track aims to empower next-generation scientific discovery through novel distributed solutions.

Topics

• Parallel and distributed algorithms for data pre-processing and discretization
• Scalable and parallel mesh generation algorithms
• In-situ and in-transit visualization frameworks
• Data compression and streaming for remote visual computing
• High-performance rendering architectures and large-scale data exploration

Important Date

We are pleased to announce the important dates for PDCAT 2026. Please mark your calendars!
All deadlines are based on Anywhere on Earth (AoE), at midnight on the specified date.

• Paper Submission Deadline: 31 August, 2026 (AoE)
• Notification of Acceptance: 10 October, 2026
• Camera-Ready Submission Deadline: 31 October, 2026
• Conference Dates: 4-6 December, 2026