• Title/Summary/Keyword: Dependence Set Partitioning

Search Result 5, Processing Time 0.018 seconds

Design and Evaluation of Flexible Thread Partitioning System (융통성 있는 스레드 분할 시스템 설계와 평가)

  • Jo, Sun-Moon
    • Journal of Internet Computing and Services
    • /
    • v.8 no.3
    • /
    • pp.75-83
    • /
    • 2007
  • Multithreaded model is an effective parallel system in that it can reduce the long memory reference latency time and solve the synchronization problems. When compiling the non-strict functional programs for the multithreaded parallel machine, the most important thing is to find an set of sequentially executable instructions and to partitions them into threads. The existing partitioning algorithm partitions the condition of conditional expression, true expression and false expression into the basic blocks and apply local partitioning to these basic blocks. We can do the better partitioning if we modify the definition of the thread and allow the branching within the thread. The branching within the thread do not reduce the parallelism, do not increase the number of synchronization and do not violate the basic rule of the thread partitioning. On the contrary, it can lengthen the thread and reduce the number of synchronization. In the paper, we enhance the method of the partition of threads by combining the three basic blocks into one of two blocks.

  • PDF

Extended Three Region Partitioning Method of Loops with Irregular Dependences (비규칙 종속성을 가진 루프의 확장된 세지역 분할 방법)

  • Jeong, Sam-Jin
    • Journal of the Korea Convergence Society
    • /
    • v.6 no.3
    • /
    • pp.51-57
    • /
    • 2015
  • This paper proposes an efficient method such as Extended Three Region Partitioning Method for nested loops with irregular dependences for maximizing parallelism. Our approach is based on the Convex Hull theory, and also based on minimum dependence distance tiling, the unique set oriented partitioning, and three region partitioning methods. In the proposed method, we eliminate anti dependences from the nested loop by variable renaming. After variable renaming, we present algorithm to select one or more appropriate lines among given four lines such as LMLH, RMLH, LMLT and RMLT. If only one line is selected, the method divides the iteration space into two parallel regions by the selected line. Otherwise, we present another algorithm to find a serial region. The selected lines divide the iteration space into two parallel regions as large as possible and one or less serial region as small as possible. Our proposed method gives much better speedup and extracts more parallelism than other existing three region partitioning methods.

3-D Lossy Volumetric Medical Image Compression with Overlapping method and SPIHT Algorithm and Lifting Steps (Overlapping method와 SPIHT Algorithm과 Lifting Steps을 이용한 3차원 손실 의료 영상 압축 방법)

  • 김영섭
    • Journal of the Korea Academia-Industrial cooperation Society
    • /
    • v.4 no.3
    • /
    • pp.263-269
    • /
    • 2003
  • This paper focuses on lossy medical image compression methods for medical images that operate on three-dimensional(3D) irreversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm〔l-3〕to medical images, using a 3-D wavelet decomposition and a 3-D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. As the compression rate increases, the boundaries between adjacent coding units become increasingly visible. Unlike video, the volume image is examined under static condition, and must not exhibit such boundary artifacts. In order to eliminate them, we utilize overlapping at axial boundaries between adjacent coding units. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well. The improvement is visibly manifested as fewer ringing artifacts and noticeably better reconstruction of low contrast.

  • PDF

Lossless Medical Image Compression with SPIHT and Lifting Steps (SPIHT알고리즘과 Lifting 스텝을 이용한 무손실 의료 영상 압축 방법)

  • 김영섭;정제창
    • Proceedings of the IEEK Conference
    • /
    • 2003.07e
    • /
    • pp.2395-2398
    • /
    • 2003
  • This paper focuses on lossless medical image compression methods for medical images that operate on two-dimensional(2D) reversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm [1][3][9] to medical images, using a 2D wavelet decomposition and a 2D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well and sometimes better in lossless coding than previous coding systems using 2D integer wavelet transforms on medical images.

  • PDF

2차원 손실 의료영상 압축

  • 김영섭
    • Proceedings of the Korean Society Of Semiconductor Equipment Technology
    • /
    • 2004.05a
    • /
    • pp.217-222
    • /
    • 2004
  • This paper focuses on lossy medical image compression methods for medical images that operate on two-dimensional(2D) integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm to medical images, using a 2D wavelet decomposition and a 2D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well and is sometimes better lossy coding using 2D integer wavelet transforms on medical images.

  • PDF