02661nas|a2200241 i 450000500170000000800410001703500150005810000290007324500710010226000520017330000100022549000260023550001420026150200580040352016160046165000470207770000260212470000480215070000430219871000550224181000580229685600650235420260818171218.0260799s1998    th  uzm rtt  00|  a1eng d  a.b117561231 aDavaasambuu, Davaajargal10aParallel image processing algorithm for convex exemplar SPP system  aBangkok :bAsian Institute of Technology,c1998  a50 p.1 aThesis ;vno. CS-98-9  aA thesis submitted in partial fulfillment of the requirements for the degree of Master of  Engineering, School of Advanced Technologies    aThesis (M.Eng.) - Asian Institute of Technology, 1998  aParallel Processing has an advantage over traditional supercomputers in price I performance I  speed and it comprises algorithms, computer architecture, programming tools, and  performance analysis. The objective of this study is to propose an efficient parallel algorithm  for image matching computation on the Convex Exemplar SPP System.  Three new parallel algorithms are proposed which are the improvement on each other and  implemented in Convex MPICH message-passing environment. The most efficient proposed  parallel algorithm is called the Parallel Help-Load Balancing Improved Algorithm and the  reasons for the efficiency are computational power of the system, reduced communication in  the parallel algorithm, the processors help each other, and proportional amount of data is  distributed during the load balancing process. To evaluate the performance of the new efficient  parallel algorithm, this study discusses the normalized performances of the proposed load  balancing strategies, how system workload affects the performance of parallel algorithm, and  compares the performances between the proposed efficient parallel algorithm and shared memory parallel algorithm. Results of study are categorized in the following order. First, this  study presents the efficient parallel algorithm for image matching computation on Convex  Exemplar in Convex MPICH. Second, results indicate that the Parallel Help-Load Balancing  Improved Algorithm is the most efficient when the program is computation intensive. Finally,  it is determined that the efficiency depends on system workload and its balancing. 0aParallel processing (Electronic computers)1 aYulu Qi,eChairperson1 aBatanov, Dentcho N.,eExamination Committee1 aZhang, Jianguo,eExamination committee2 aJapan - Asian Development Bank,eScholarship donor2 aAsian Institute of Technology.tThesis ;vno. CS-98-9  3Full-Textuhttp://203.159.5.9/ait-thesis/detail.php?q=B13251