Out-of-core diffraction algorithm using multiple SSDs for ultra-high-resolution hologram generation

被引:0
|
作者
Lee, Jaehong [1 ]
Kim, Duksu [1 ]
机构
[1] Korea Univ Technol & Educ KOREATECH, Cheonan, South Korea
基金
新加坡国家研究基金会;
关键词
DECOMPOSITION;
D O I
10.1364/OE.493984
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The diffraction calculation is critical in computer-generated holography (CGH). However, it becomes a performance bottleneck when generating ultra-high-resolution holograms due to limited physical memory space. We propose a novel out-of-core (OOC) diffraction algorithm that utilizes multiple solid-state drives (SSDs) to address this issue. Our method employs the implicit diffraction approach and exploits its even-odd separation characteristic to utilize multiple SSDs optimally. We implement our algorithm on two machines, each with four SSDs, and compare it with prior OOC diffraction methods and a RAID-based solution. Our approach achieves up to 2.43 times higher performance than prior OOC methods for large-scale diffraction calculations, with continued performance improvement observed by adding more SSDs. Additionally, our method reduces the generation time for ultra-high-resolution holograms (200K x 200K) by 38% compared to the prior OOC method with multiple SSDs. These results demonstrate the effectiveness of our algorithm for extreme-scale CGH.
引用
收藏
页码:28683 / 28700
页数:18
相关论文
共 50 条
  • [31] Real-Time Object Detection using an Ultra-High-Resolution Camera on Embedded Systems
    Antonakakis, Marios
    Tzavaras, Aimilios
    Tsakos, Konstantinos
    Spanakis, Emmanouil G.
    Sakkalis, Vangelis
    Zervakis, Michalis
    Petrakis, Euripides G. M.
    2022 IEEE INTERNATIONAL CONFERENCE ON IMAGING SYSTEMS AND TECHNIQUES (IST 2022), 2022,
  • [32] Species-Level Classification of Peatland Vegetation Using Ultra-High-Resolution UAV Imagery
    Simpson, Gillian
    Nichol, Caroline J.
    Wade, Tom
    Helfter, Carole
    Hamilton, Alistair
    Gibson-Poole, Simon
    DRONES, 2024, 8 (03)
  • [33] Using deep learning to detect an indicator arid shrub in ultra-high-resolution UAV imagery
    Retallack, Angus
    Finlayson, Graeme
    Ostendorf, Bertram
    Lewis, Megan
    Ecological Indicators, 2022, 145
  • [34] Bone microarchitectural analysis using ultra-high-resolution CT in tiger vertebra and human tibia
    Inai, Ryota
    Nakahara, Ryuichi
    Morimitsu, Yusuke
    Akagi, Noriaki
    Marukawa, Youhei
    Matsushita, Toshi
    Tanaka, Takashi
    Tada, Akihiro
    Hiraki, Takao
    Nasu, Yoshihisa
    Nishida, Keiichiro
    Ozaki, Toshifumi
    Kanazawa, Susumu
    EUROPEAN RADIOLOGY EXPERIMENTAL, 2020, 4 (01)
  • [35] Contour-type cutter path computation using ultra-high-resolution dexel model
    Inui M.
    Umezu N.
    Computer-Aided Design and Applications, 2020, 17 (03): : 621 - 638
  • [36] Using deep learning to detect an indicator arid shrub in ultra-high-resolution UAV imagery
    Retallack, Angus
    Finlayson, Graeme
    Ostendorf, Bertram
    Lewis, Megan
    ECOLOGICAL INDICATORS, 2022, 145
  • [37] Pasture Biomass Estimation Using Ultra-High-Resolution RGB UAVs Images and Deep Learning
    Vahidi, Milad
    Shafian, Sanaz
    Thomas, Summer
    Maguire, Rory
    REMOTE SENSING, 2023, 15 (24)
  • [38] ULTRA-HIGH-RESOLUTION SPECT SYSTEM USING 4 PINHOLE COLLIMATORS FOR SMALL ANIMAL STUDIES
    ISHIZU, K
    MUKAI, T
    YONEKURA, Y
    PAGANI, M
    FUJITA, T
    MAGATA, Y
    NISHIZAWA, S
    TAMAKI, N
    SHIBASAKI, H
    KONISHI, J
    JOURNAL OF NUCLEAR MEDICINE, 1995, 36 (12) : 2282 - 2287
  • [39] Molecular Characterization of Organosulfates in Highly Polluted Atmosphere Using Ultra-High-Resolution Mass Spectrometry
    Cai, Dongmei
    Wang, Xinke
    Chen, Jianmin
    Li, Xiang
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2020, 125 (08)
  • [40] Metal artefact reduction in the oral cavity using deep learning reconstruction algorithm in ultra-high-resolution computed tomography: a phantom study
    Sakai, Yuki
    Kitamoto, Erina
    Okamura, Kazutoshi
    Tatsumi, Masato
    Shirasaka, Takashi
    Mikayama, Ryoji
    Kondo, Masatoshi
    Hamasaki, Hiroshi
    Kato, Toyoyuki
    Yoshiura, Kazunori
    DENTOMAXILLOFACIAL RADIOLOGY, 2021, 50 (07)