Refactoring TEZip: Integrating Python-Based Predictive Compression into an HPC C++/LibTorch Environment
TEZip is a framework for compressing time-evolving image data using predictive deep neural networks. Until now, TEZip primarily relied on Python libraries (TensorFlow or PyTorch). This work presents a new TEZip pipeline built with C++/LibTorch for improved speed and High preformance Computer(HPC) compatibility.
Authors
- Kento Sato (ORCID: https://orcid.org/0000-0001-7850-2121)
- Mina Yousef
- Amarjit Singh (ORCID: https://orcid.org/0000-0002-7081-7329)
Institutions
- RIKEN Center for Computational Science (JP)
- Nile University (EG)
Publication Details
- Published
- 2025-07-20
- DOI
- https://doi.org/10.1145/3731545.3735120
- Primary Topic
- Parallel Computing and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00