학술논문

Balancing Load of GPU Subsystems to Accelerate Image Reconstruction in Parallel Beam Tomography
Document Type
Conference
Source
2018 30th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD) Computer Architecture and High Performance Computing (SBAC-PAD), 2018 30th International Symposium on. :158-166 Sep, 2018
Subject
Computing and Processing
Graphics processing units
Image reconstruction
Engines
Computer architecture
Open area test sites
Tomography
Language
Abstract
Synchrotron X-ray imaging is a powerful method to investigate internal structures down to the micro and nanoscopic scale. Fast cameras recording thousands of frames per second allow time-resolved studies with a high temporal resolution. Fast image reconstruction is essential to provide the synchrotron instrumentation with the imaging information required to track and control the process under study. Traditionally Filtered Back Projection algorithm is used for tomographic reconstruction. In this article, we discuss how to implement the algorithm on nowadays GPGPU architectures efficiently. The key is to achieve balanced utilization of available GPU subsystems. We present two highly optimized algorithms to perform back projection on parallel hardware. One is relying on the texture engine to perform reconstruction, while another one utilizes the Core computational units of the GPU. Both methods outperform current state-of-the-art techniques found in the standard reconstructions codes significantly. Finally, we propose a hybrid approach combining both algorithms to better balance load between G PU subsystems. It further boosts the performance by about 30 % on NVIDIA Pascal micro-architecture.