2/5/2025 | 11:00 AM - 12:20 PM | Regency A

High-performance Image Reconstruction using ABCI supercomputer

Author(s)

Peng Chen | National Institute of Advanced Industrial Science and Technology （AIST）
Wahib Mohamed | RIKEN-CCS
Xiao Wang | ORNL
Isaac Lyngaas | ORNL
Jun Igarashi | RIKEN-CCS

Abstract

In this work, we showcase our high-performance image reconstruction framework utilizing the ABCI supercomputer. Computed Tomography (CT) is a critical imaging technique, but its image reconstruction algorithms are computationally intensive. To address this challenge, we introduce a novel back-projection algorithm that reduces projection computation costs compared to traditional methods. Our solution efficiently takes advantage of GPU-accelerated systems by dividing the workload between CPUs and GPUs, overlapping the filtering stage on CPUs with the back-projection on GPUs to optimize performance. Additionally, we present a distributed framework designed for high-resolution image reconstruction on modern supercomputers. This framework optimizes communication by interleaving MPI collective operations, enabling scalable data transfer. By scaling across up to 2,048 V100 GPUs on the ABCI supercomputer, we demonstrate near-instantaneous CT image reconstruction, showcasing the scalability and real-time capability of our approach.