KIPS Transactions on Computer and Communication Systems (정보처리학회논문지:컴퓨터 및 통신 시스템)

Korea Information Processing Society (한국정보처리학회)
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Efficient Workload Distribution of Photomosaic Using OpenCL into a Heterogeneous Computing Environment

이기종 컴퓨팅 환경에서 OpenCL을 사용한 포토모자이크 응용의 효율적인 작업부하 분배

  • 김희곤 (고려대학교 컴퓨터정보학과) ;
  • 사재원 (고려대학교 컴퓨터정보학과) ;
  • 최동휘 (고려대학교 컴퓨터정보학과) ;
  • 김혜련 (고려대학교 컴퓨터정보학과) ;
  • 이성주 (고려대학교 컴퓨터정보학과) ;
  • 정용화 (고려대학교 컴퓨터정보학과) ;
  • 박대희 (고려대학교 컴퓨터정보학과)
  • Received : 2015.04.28
  • Accepted : 2015.06.26
  • Published : 2015.08.31
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Abstract

Recently, parallel processing methods with accelerator have been introduced into a high performance computing and a mobile computing. The photomosaic application can be parallelized by using inherent data parallelism and accelerator. In this paper, we propose a way to distribute the workload of the photomosaic application into a CPU and GPU heterogeneous computing environment. That is, the photomosaic application is parallelized using both CPU and GPU resource with the asynchronous mode of OpenCL, and then the optimal workload distribution rate is estimated by measuring the execution time with CPU-only and GPU-only distribution rates. The proposed approach is simple but very effective, and can be applied to parallelize other applications on a CPU and GPU heterogeneous computing environment. Based on the experimental results, we confirm that the performance is improved by 141% into a heterogeneous computing environment with the optimal workload distribution compared with using GPU-only method.

최근 고성능 컴퓨팅과 모바일 컴퓨팅에서 성능가속기를 사용하는 병렬처리 방법들이 소개되어왔다. 포토모자이크 응용은 내재된 데이터 병렬성을 활용하고 성능가속기를 사용하여 병렬처리가 가능하다. 본 논문에서는 CPU와 GPU로 구성된 이기종 컴퓨팅 환경에서 포토모자이크 수행 시 작업부하 분배 방법을 제안한다. 즉, 포토모자이크 응용을 비동기 방식으로 병렬화하여 CPU와 GPU 자원을 동시에 활용하고, 각 처리기에 할당할 최적의 작업부하량을 예측하기 위해 CPU-only와 GPU-only 작업 분배 환경에서 수행시간을 측정한다. 제안 방법은 간단하지만 매우 효과적이고, CPU와 GPU로 구성된 이기종 컴퓨팅 환경에서 다른 응용을 병렬화하 데에도 적용될 수 있다. 실험 결과, 이기종 컴퓨팅 환경에서 최적의 작업 분배량으로 수행한 경우, GPU-only의 방법과 비교하여 141%의 성능이 개선되었음을 확인한다.

Keywords

References

  1. C. Chun, S. Hong, J. Bae, and M. Lee, "High Performance Computing Using GPU's: with Application to Financial Derivatives Modeling," The Journal of Korean Institute of Next Generation Computing, Vol.5, No.1, pp.30-40, 2009.
  2. J. Nickolls, I. Buck, M. Garland, and K. Skadron, "Scalable Parallel Programming with CUDA," ACM Queue, Vol.6, No.2, pp.40-53, 2008.
  3. I. Kim, K. Chang, C. Lee, D. Oh, and W. Ro, "An Efficient H.264 Encoding Process using Multiple GPUs," in Proceedings of the IEEK Summer Conference, Jeju, pp.739-740, 2012.
  4. J. Kang, D. Lee, I. Kang, and H. Yu, "A Study on a Declines in Performance by Memory Copy in CUDA," in Proceedings of the 40th conference of the KIPS, Jeju, pp.135-138, 2013.
  5. J. Kim, S. Ko, and N. Park, "Implementation of High-Throughput AES Algorithm using CUDA," in Proceedings of the 2014 Spring Conference of the KIPS, Suwon, pp.119-120, 2014.
  6. Y. Jeong, N. Tran, and M. Lee, "Parallelization and Optimization of Boyer-Moore Algorithm on GPU," in Proceedings of the KCC, Busan, pp.54-56, 2014.
  7. J. Stone, D Gohara, and G Shi, "OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems," Computing in Science and Engineering, Vol.12, No.3, pp.66-73, 2010.
  8. Y. Yuan, Z. He, Z. Gong, and W. Qiu, "Acceleration of AES Encryption with OpenCL," in Proceedings of The 9th Asia JCIS, Wuhan, pp.64-70, 2014.
  9. M. Bach, V. Lindenstruth, O. Philipsen, and C. Pinke, "Lattice QCD based on OpenCL," Computer Physics Communications, Vol.184, No.9, pp.2042-2052, 2013. https://doi.org/10.1016/j.cpc.2013.03.020
  10. V. Demchik and N. Kolomoyets, "QCDGPU: open-source package for Monte Carlo lattice simulations on OpenCLcompatible multi-GPU systems," in Proceedings of The 3rd HPC-UA, Kyiv, pp.92-99, 2013.
  11. R. Silvers and M. Hawley, "Photomosaics," New York: Holt Paperbacks, 1997.
  12. D. Kang and K. Yoon, "Photomosaic using a programmable GPU," Journal of the Korea Computer Graphics Society, Vol.15, No.1, pp.17-25, 2008.
  13. J. Yang, C. Joo, and K. Oh, "Photo Mosaics using Quad-tree structure on GPU," Journal of the Korea Computer Graphics Society, Vol.17, No.1, pp.25-31, 2011. https://doi.org/10.15701/kcgs.2011.17.1.25