CAJ | 학술논문

用传统的串行算法进行矩阵相乘运算会受到矩阵规模、单机的CPU主频、内存大小和存储器空间等方面的限制。而使用并行算法是解决上述限制的最有效途径。为此，在集群计算环境下，使用SPMD计算模型和基于MPI消息传递技术设计实现了矩阵相乘的并行算法。实验表明，此并行算法在一定矩阵规模下具有较好的加速比和并行效率。
용전통적천행산법진행구진상승운산회수도구진규모、단궤적CPU주빈、내존대소화존저기공간등방면적한제。이사용병행산법시해결상술한제적최유효도경。위차，재집군계산배경하，사용SPMD계산모형화기우MPI소식전체기술설계실현료구진상승적병행산법。실험표명，차병행산법재일정구진규모하구유교호적가속비화병행효솔。
With traditional serial algorithm for matrix multiplication , the result will be con-strained by matrix scale , CPU frequency , and memory size and storage space .The most ef-fective way to solve the limitation was parallel algorithm .Therefore, this paper completed the matrix multiplication with SPMD model and MPI in cluster computing environment .Experi-mental results showed that this algorithm under a certain size of the matrix has a good speed-up and efficiency .