Exploring the design space of HEVC inverse transforms with dataflow programming
This paper presents the design space exploration of the hardware-based inverse fixed-point integer transform for High Efficiency Video Coding (HEVC). The designs are specified at high-level using CAL dataflow language and automatically synthesized to HDL for FPGA implementation. Several parallel des...
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my.utm.669902017-07-18T04:09:47Z http://eprints.utm.my/id/eprint/66990/ Exploring the design space of HEVC inverse transforms with dataflow programming Khoo, Zhi Yion Ab. Rahman, Ab. Al-Hadi TK Electrical engineering. Electronics Nuclear engineering This paper presents the design space exploration of the hardware-based inverse fixed-point integer transform for High Efficiency Video Coding (HEVC). The designs are specified at high-level using CAL dataflow language and automatically synthesized to HDL for FPGA implementation. Several parallel design alternatives are proposed with trade-off between performance and resource. The HEVC transform consists of several independent components from 4x4 to 32x32 discrete cosine transform and 4x4 discrete sine transform. This work explores the strategies to efficiently compute the transforms by applying data parallelism on the different components. Results show that an intermediate version of parallelism, whereby the 4x4 and 8x8 are merged together, and the 16x16 and 32x32 merged together gives the best trade-off between performance and resource. The results presented in this work also give an insight on how the HEVC transform can be designed efficiently in parallel for hardware implementation. FKE UTM 2016-01-12 Conference or Workshop Item PeerReviewed Khoo, Zhi Yion and Ab. Rahman, Ab. Al-Hadi (2016) Exploring the design space of HEVC inverse transforms with dataflow programming. In: 2016 International Conference on Electrical, Electronic, Communication and Control Engineering, 18-19 Dec, 2016, Johor Bahru, Malaysia. http://dx.doi.org/10.11591/ijeecs.v6.i1.pp104-109 |
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TK Electrical engineering. Electronics Nuclear engineering Khoo, Zhi Yion Ab. Rahman, Ab. Al-Hadi Exploring the design space of HEVC inverse transforms with dataflow programming |
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This paper presents the design space exploration of the hardware-based inverse fixed-point integer transform for High Efficiency Video Coding (HEVC). The designs are specified at high-level using CAL dataflow language and automatically synthesized to HDL for FPGA implementation. Several parallel design alternatives are proposed with trade-off between performance and resource. The HEVC transform consists of several independent components from 4x4 to 32x32 discrete cosine transform and 4x4 discrete sine transform. This work explores the strategies to efficiently compute the transforms by applying data parallelism on the different components. Results show that an intermediate version of parallelism, whereby the 4x4 and 8x8 are merged together, and the 16x16 and 32x32 merged together gives the best trade-off between performance and resource. The results presented in this work also give an insight on how the HEVC transform can be designed efficiently in parallel for hardware implementation. |
format |
Conference or Workshop Item |
author |
Khoo, Zhi Yion Ab. Rahman, Ab. Al-Hadi |
author_facet |
Khoo, Zhi Yion Ab. Rahman, Ab. Al-Hadi |
author_sort |
Khoo, Zhi Yion |
title |
Exploring the design space of HEVC inverse transforms with dataflow programming |
title_short |
Exploring the design space of HEVC inverse transforms with dataflow programming |
title_full |
Exploring the design space of HEVC inverse transforms with dataflow programming |
title_fullStr |
Exploring the design space of HEVC inverse transforms with dataflow programming |
title_full_unstemmed |
Exploring the design space of HEVC inverse transforms with dataflow programming |
title_sort |
exploring the design space of hevc inverse transforms with dataflow programming |
publisher |
FKE UTM |
publishDate |
2016 |
url |
http://eprints.utm.my/id/eprint/66990/ http://dx.doi.org/10.11591/ijeecs.v6.i1.pp104-109 |
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1643655875808722944 |
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13.160551 |