Using a high-level parallel programming language for GPU-accelerated tomographic reconstruction

Mette Bjerg Lindhøj; Troels Henriksen; Lærke Pedersen; Jon Sporring

Using a high-level parallel programming language for GPU-accelerated tomographic reconstruction

Mette Bjerg Lindhøj, Troels Henriksen, Lærke Pedersen, Jon Sporring

Abstract

This paper aims to determine the usefulness of using a high-level parallel programming language for implementing parallel high-performance tomographic reconstruction algorithms. The purpose of this is to make it easier for researchers to implement advanced model-based iterative reconstruction algorithms for use at synchrotron facilities, while still taking advantage of hardware such as GPUs. To this end, we implement the forward- and back-projection in the programming language Futhark, and verify their applicability through an implementation of an algebraic reconstruction algorithm. We obtain promising performance results by use of algorithmic considerations instead of low-level optimizations. Finally, we demonstrate that the implementation makes it possible to prototype implementations of iterative reconstruction algorithms on a standard laptop while still obtaining good scaling towards highend GPUs.

Originalsprog	Engelsk
Titel	The 2019 International Conference on High Performance Computing & Simulation : HPCS 2019
Antal sider	6
Publikationsdato	15 jul. 2019
Sider	27-32
Artikelnummer	3
Kapitel	2
Status	Udgivet - 15 jul. 2019

Citationsformater

Using a high-level parallel programming language for GPU-accelerated tomographic reconstruction. / Lindhøj, Mette Bjerg; Henriksen, Troels; Pedersen, Lærke et al.

The 2019 International Conference on High Performance Computing & Simulation: HPCS 2019. 2019. s. 27-32 3.

Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › peer review

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AU - Henriksen, Troels

AU - Pedersen, Lærke

AU - Sporring, Jon

PY - 2019/7/15

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N2 - This paper aims to determine the usefulness of using a high-level parallel programming language for implementing parallel high-performance tomographic reconstruction algorithms. The purpose of this is to make it easier for researchers to implement advanced model-based iterative reconstruction algorithms for use at synchrotron facilities, while still taking advantage of hardware such as GPUs. To this end, we implement the forward- and back-projection in the programming language Futhark, and verify their applicability through an implementation of an algebraic reconstruction algorithm. We obtain promising performance results by use of algorithmic considerations instead of low-level optimizations. Finally, we demonstrate that the implementation makes it possible to prototype implementations of iterative reconstruction algorithms on a standard laptop while still obtaining good scaling towards highend GPUs.

AB - This paper aims to determine the usefulness of using a high-level parallel programming language for implementing parallel high-performance tomographic reconstruction algorithms. The purpose of this is to make it easier for researchers to implement advanced model-based iterative reconstruction algorithms for use at synchrotron facilities, while still taking advantage of hardware such as GPUs. To this end, we implement the forward- and back-projection in the programming language Futhark, and verify their applicability through an implementation of an algebraic reconstruction algorithm. We obtain promising performance results by use of algorithmic considerations instead of low-level optimizations. Finally, we demonstrate that the implementation makes it possible to prototype implementations of iterative reconstruction algorithms on a standard laptop while still obtaining good scaling towards highend GPUs.

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Using a high-level parallel programming language for GPU-accelerated tomographic reconstruction

Abstract

Fingeraftryk

Citationsformater