Towards a GPU accelerated spatial computing framework

Harshada Chavan, Rami Alghamdi, Mohamed Mokbel

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Ease of availability of spatial data has increased the interest in the domain of spatial computing. Various services such as Uber, Google maps, and Blue Brain Project have been developed that consume and process such spatial data. Spatial data processing is not only data intensive but also compute intensive. A lot of efforts have been made by the spatial computing community to tackle the problems due to huge volumes of data. However, unfortunately, not enough attention has been given to address the compute intensive nature of the problem. In parallel to the advancements in spatial domain, Graphics Processing Units (GPUs) have emerged as compelling computing units. A lot of work has been done in spatial domain to leverage the computing power of GPUs. However, to the best of our knowledge, none of the work present a holistic system. In this paper, we propose a vision for a GPU accelerated end-to-end system for performing spatial computations. Our envisioned system supports a plethora of spatial operations ranging from basic operations, computational geometry operations to Open Geospatial Consortium (OGC) compliant operations. Our system exploits the power of CPU-GPU co-processing by scheduling the execution of spatial operators either on CPU or GPU based on a cost model. Within the framework of our system we discuss the challenges and open research problems in building such a system. We also provide some preliminary results to show the computational gain achieved by performing spatial operations on GPUs.

Original languageEnglish
Title of host publication2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages135-142
Number of pages8
ISBN (Electronic)9781509021086
DOIs
Publication statusPublished - 20 Jun 2016
Externally publishedYes
Event32nd IEEE International Conference on Data Engineering Workshops, ICDEW 2016 - Helsinki, Finland
Duration: 16 May 201620 May 2016

Other

Other32nd IEEE International Conference on Data Engineering Workshops, ICDEW 2016
CountryFinland
CityHelsinki
Period16/5/1620/5/16

Fingerprint

Program processors
Computational geometry
Graphics processing unit
Brain
Scheduling
Availability
Processing
Costs

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Information Systems and Management
  • Computer Graphics and Computer-Aided Design

Cite this

Chavan, H., Alghamdi, R., & Mokbel, M. (2016). Towards a GPU accelerated spatial computing framework. In 2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016 (pp. 135-142). [7495634] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDEW.2016.7495634

Towards a GPU accelerated spatial computing framework. / Chavan, Harshada; Alghamdi, Rami; Mokbel, Mohamed.

2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 135-142 7495634.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chavan, H, Alghamdi, R & Mokbel, M 2016, Towards a GPU accelerated spatial computing framework. in 2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016., 7495634, Institute of Electrical and Electronics Engineers Inc., pp. 135-142, 32nd IEEE International Conference on Data Engineering Workshops, ICDEW 2016, Helsinki, Finland, 16/5/16. https://doi.org/10.1109/ICDEW.2016.7495634
Chavan H, Alghamdi R, Mokbel M. Towards a GPU accelerated spatial computing framework. In 2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 135-142. 7495634 https://doi.org/10.1109/ICDEW.2016.7495634
Chavan, Harshada ; Alghamdi, Rami ; Mokbel, Mohamed. / Towards a GPU accelerated spatial computing framework. 2016 IEEE 32nd International Conference on Data Engineering Workshops, ICDEW 2016. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 135-142
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