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Accelerating radio transient detection using the Bispectrum algorithm and GPGPU
Modern radio interferometers such as those in the Square Kilometre Array (SKA) project are powerful tools to discover completely new classes of astronomical phenomena. Amongst these phenomena are radio transients. Transients are bursts of electromagnetic radiation and is an exciting area of research...
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| Format: | Thesis |
| Language: | English |
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Department of Computer Science
2016
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| _version_ | 1867613190869745664 |
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| access_status_str | Open Access |
| author | Lin, Tsu-Shiuan |
| author2 | Gain, James |
| author_browse | Gain, James Lin, Tsu-Shiuan |
| author_facet | Gain, James Lin, Tsu-Shiuan |
| author_sort | Lin, Tsu-Shiuan |
| collection | Thesis |
| description | Modern radio interferometers such as those in the Square Kilometre Array (SKA) project are powerful tools to discover completely new classes of astronomical phenomena. Amongst these phenomena are radio transients. Transients are bursts of electromagnetic radiation and is an exciting area of research as localizing pulsars (transient emitters) allow physicists to test and formulate theories on strong gravitational forces. Current methods for detecting transients requires an image of the sky to be produced at every time step. Since interferometers have more information available to them, the computational demands for producing images becomes infeasible due to the larger data sets provided by larger interferometers. Law and Bower (2012) formulated a different approach by using a closure quantity known as the "bispectrum": the product of visibilities around a closed loop of antennae. The proposed algorithm has been shown to be easily parallelized and suitable for Graphics processing units (GPUs).Recent advancements in the field of many core technology such as GPUs has demonstrated significant performance enhancements to many scientific applications. A GPU implementation of the bispectrum algorithm has yet to be explored. In this thesis, we present a number of modified implementations of the bispectrum algorithm, allowing both instruction-level and data-level parallelism. Firstly, a multi-threaded CPU version is developed in C++ using OpenMP and then compared to a GPU version developed using Compute Unified Device Architecture (CUDA).In order to verify validity of the implementations presented, the implementations were firstly run on simulated data created from MeqTrees: a tool for simulating transients developed by the SKA. Thereafter, data from the Karl Jansky Very Large Array (JVLA) containing the B0355+54pulsar was used to test the implementation on real data. This research concludes that the bispectrum algorithm is well suited for both CPU and GPU implementations as we achieved a 3.2x speed up on a 4-core multi-threaded CPU implementation over a single thread implementation. The GPU implementation on a GTX670, achieved about a 20 times speed-up over the multi-threaded CPU implementation. These results show that the bispectrum algorithm will open doors to a series of efficient transient surveys suitable for modern data-intensive radio interferometers. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/21198 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:32:13.078Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Department of Computer Science |
| publisherStr | Department of Computer Science |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/21198 Accelerating radio transient detection using the Bispectrum algorithm and GPGPU Lin, Tsu-Shiuan Gain, James Armstrong, Richard Computer Science Modern radio interferometers such as those in the Square Kilometre Array (SKA) project are powerful tools to discover completely new classes of astronomical phenomena. Amongst these phenomena are radio transients. Transients are bursts of electromagnetic radiation and is an exciting area of research as localizing pulsars (transient emitters) allow physicists to test and formulate theories on strong gravitational forces. Current methods for detecting transients requires an image of the sky to be produced at every time step. Since interferometers have more information available to them, the computational demands for producing images becomes infeasible due to the larger data sets provided by larger interferometers. Law and Bower (2012) formulated a different approach by using a closure quantity known as the "bispectrum": the product of visibilities around a closed loop of antennae. The proposed algorithm has been shown to be easily parallelized and suitable for Graphics processing units (GPUs).Recent advancements in the field of many core technology such as GPUs has demonstrated significant performance enhancements to many scientific applications. A GPU implementation of the bispectrum algorithm has yet to be explored. In this thesis, we present a number of modified implementations of the bispectrum algorithm, allowing both instruction-level and data-level parallelism. Firstly, a multi-threaded CPU version is developed in C++ using OpenMP and then compared to a GPU version developed using Compute Unified Device Architecture (CUDA).In order to verify validity of the implementations presented, the implementations were firstly run on simulated data created from MeqTrees: a tool for simulating transients developed by the SKA. Thereafter, data from the Karl Jansky Very Large Array (JVLA) containing the B0355+54pulsar was used to test the implementation on real data. This research concludes that the bispectrum algorithm is well suited for both CPU and GPU implementations as we achieved a 3.2x speed up on a 4-core multi-threaded CPU implementation over a single thread implementation. The GPU implementation on a GTX670, achieved about a 20 times speed-up over the multi-threaded CPU implementation. These results show that the bispectrum algorithm will open doors to a series of efficient transient surveys suitable for modern data-intensive radio interferometers. 2016-08-11T10:22:46Z 2016-08-11T10:22:46Z 2015 Master Thesis Masters MSc http://hdl.handle.net/11427/21198 eng application/pdf Department of Computer Science Faculty of Science University of Cape Town |
| spellingShingle | Computer Science Lin, Tsu-Shiuan Accelerating radio transient detection using the Bispectrum algorithm and GPGPU |
| thesis_degree_str | Master's |
| title | Accelerating radio transient detection using the Bispectrum algorithm and GPGPU |
| title_full | Accelerating radio transient detection using the Bispectrum algorithm and GPGPU |
| title_fullStr | Accelerating radio transient detection using the Bispectrum algorithm and GPGPU |
| title_full_unstemmed | Accelerating radio transient detection using the Bispectrum algorithm and GPGPU |
| title_short | Accelerating radio transient detection using the Bispectrum algorithm and GPGPU |
| title_sort | accelerating radio transient detection using the bispectrum algorithm and gpgpu |
| topic | Computer Science |
| url | http://hdl.handle.net/11427/21198 |
| work_keys_str_mv | AT lintsushiuan acceleratingradiotransientdetectionusingthebispectrumalgorithmandgpgpu |