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Accelerating IDCT Algorithm on Xeon Phi Coprocessor

Inverse Discrete Cosine Transform (IDCT) is an important operation for image and videos decompression. How to accelerate the IDCT algorithm has been frequently studied. Recently Intel has proposed Xeon Phi coprocessors based on the many integrated core (MIC) architecture. Xeon Phi is integrated with... Full description

Journal Title: Advanced materials research 2013, Vol.756-759, p.3114-3120
Main Author: Qi, Jin
Other Authors: Yang, Can Qun , Chen, Cheng , Wu, Qiang , Tang, Tao
Format: Konferenzbeitrag Konferenzbeitrag
Language: English
ID: ISSN: 1662-8985
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recordid: cdi_crossref_primary_10_4028_www_scientific_net_AMR_756_759_3114
title: Accelerating IDCT Algorithm on Xeon Phi Coprocessor
format: Conference Proceeding
creator:
  • Qi, Jin
  • Yang, Can Qun
  • Chen, Cheng
  • Wu, Qiang
  • Tang, Tao
ispartof: Advanced materials research, 2013, Vol.756-759, p.3114-3120
description: Inverse Discrete Cosine Transform (IDCT) is an important operation for image and videos decompression. How to accelerate the IDCT algorithm has been frequently studied. Recently Intel has proposed Xeon Phi coprocessors based on the many integrated core (MIC) architecture. Xeon Phi is integrated with 61 cores and 512-bit SIMD extension within each core, thus providing very high performance. In this paper, we employ the Knights Corner (a beta version of Xeon Phi) to accelerate the IDCT algorithm. By employing the 512-bit SIMD instruction and data pre-fetching optimization, our implementation achieves (1) averagely 5.82 speedup over the none-SIMD version, (2) averagely 27.3% performance benefit with the data pre-fetching optimization, and (3) averagely 1.53 speedup on one Knights Corner coprocessor over the implementation on one octal-core Intel Xeon E5-2670 CPU.
language: eng
source:
identifier: ISSN: 1662-8985
fulltext: no_fulltext
issn:
  • 1662-8985
  • 1662-8985
url: Link


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descriptionInverse Discrete Cosine Transform (IDCT) is an important operation for image and videos decompression. How to accelerate the IDCT algorithm has been frequently studied. Recently Intel has proposed Xeon Phi coprocessors based on the many integrated core (MIC) architecture. Xeon Phi is integrated with 61 cores and 512-bit SIMD extension within each core, thus providing very high performance. In this paper, we employ the Knights Corner (a beta version of Xeon Phi) to accelerate the IDCT algorithm. By employing the 512-bit SIMD instruction and data pre-fetching optimization, our implementation achieves (1) averagely 5.82 speedup over the none-SIMD version, (2) averagely 27.3% performance benefit with the data pre-fetching optimization, and (3) averagely 1.53 speedup on one Knights Corner coprocessor over the implementation on one octal-core Intel Xeon E5-2670 CPU.
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descriptionInverse Discrete Cosine Transform (IDCT) is an important operation for image and videos decompression. How to accelerate the IDCT algorithm has been frequently studied. Recently Intel has proposed Xeon Phi coprocessors based on the many integrated core (MIC) architecture. Xeon Phi is integrated with 61 cores and 512-bit SIMD extension within each core, thus providing very high performance. In this paper, we employ the Knights Corner (a beta version of Xeon Phi) to accelerate the IDCT algorithm. By employing the 512-bit SIMD instruction and data pre-fetching optimization, our implementation achieves (1) averagely 5.82 speedup over the none-SIMD version, (2) averagely 27.3% performance benefit with the data pre-fetching optimization, and (3) averagely 1.53 speedup on one Knights Corner coprocessor over the implementation on one octal-core Intel Xeon E5-2670 CPU.
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abstractInverse Discrete Cosine Transform (IDCT) is an important operation for image and videos decompression. How to accelerate the IDCT algorithm has been frequently studied. Recently Intel has proposed Xeon Phi coprocessors based on the many integrated core (MIC) architecture. Xeon Phi is integrated with 61 cores and 512-bit SIMD extension within each core, thus providing very high performance. In this paper, we employ the Knights Corner (a beta version of Xeon Phi) to accelerate the IDCT algorithm. By employing the 512-bit SIMD instruction and data pre-fetching optimization, our implementation achieves (1) averagely 5.82 speedup over the none-SIMD version, (2) averagely 27.3% performance benefit with the data pre-fetching optimization, and (3) averagely 1.53 speedup on one Knights Corner coprocessor over the implementation on one octal-core Intel Xeon E5-2670 CPU.
doi10.4028/www.scientific.net/AMR.756-759.3114