CAJ | 학술논문

定常粒子输运蒙特卡罗并行计算是成功的,因为粒子游动是独立的,可以把模拟的粒子数等分到每个处理器去.然而,对非定常问题,由于每个时间步涉及散射源和几何网格的通讯,它严重的制约了并行规模,导致并行不可扩展.研究了两种算法,采用自适应分配处理器,提高了加速比和处理器的利用率;采用蒙特卡罗分层抽样大大降低了处理器之间散射源的通讯量,并行可扩展性显著改善,取得了理想的加速比.
정상입자수운몽특잡라병행계산시성공적,인위입자유동시독립적,가이파모의적입자수등분도매개처리기거.연이,대비정상문제,유우매개시간보섭급산사원화궤하망격적통신,타엄중적제약료병행규모,도치병행불가확전.연구료량충산법,채용자괄응분배처리기,제고료가속비화처리기적이용솔;채용몽특잡라분층추양대대강저료처리기지간산사원적통신량,병행가확전성현저개선,취득료이상적가속비.
A parallel algorithm for time-independent Monte Carlo transport is successful since particles are independent and they are distributed to multiple processors. However,for time-dependent Monte Carlo transport problems, the parallel efficiency reduces and the parallel scale is limited due to the communication of scattering source attribute and meshes in each time-step. We propose two algorithms in them adaptive processor assignment and optimized processor choice are obtained. With a Monte Carlo stratified sampling technique for scattering source treatment the communication cost is reduced greatly. The parallel expandability is improved. A large speedup over the basic algorithm is obtained.