3D Model-Based Parameter Quantification on Resource Constrained Hardware using Double-Buffering

Publikation: Beitrag in Buch/Bericht/KonferenzbandBeitrag in einem KonferenzbandForschungBegutachtung

Abstract

Reconstructing 3D parameter maps of huge volumes entirely on the GPU is highly desirable due to the offeredcomputation speed-up. However, GPU memory restrictions limit the coverable volume. To overcome thislimitation, a double-buffering strategy in combination with model-based parameter quantification and 3D-TGVregularization is proposed. This combination warrants whole volume reconstruction while maintaining thespeed advantages of GPU-based computation. In contrast to sequential transfers, double-buffering splits thevolume into blocks and overlaps memory transfer and kernel execution concurrently, hiding memory latency.The proposed method is able to reconstruct arbitrary large volumes within 5.3 min/slice, even on a single GPU.
Originalspracheenglisch
TitelProceedings of the ISMRM 27TH Annual Meeting & Exhibition, 2019
PublikationsstatusVeröffentlicht - 2019
VeranstaltungISMRM 27th Annual Meeting & Exhibition - Palais des congrès de Montréal, Montréal, Kanada
Dauer: 11 Mai 201916 Mai 2019
https://www.ismrm.org/19m/

Konferenz

KonferenzISMRM 27th Annual Meeting & Exhibition
KurztitelISMRM 2019
LandKanada
OrtMontréal
Zeitraum11/05/1916/05/19
Internetadresse

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  • Dieses zitieren

    Maier, O., & Stollberger, R. (2019). 3D Model-Based Parameter Quantification on Resource Constrained Hardware using Double-Buffering. in Proceedings of the ISMRM 27TH Annual Meeting & Exhibition, 2019 [4839]