| 引用本文: | 杨岳湘,李晓梅.巨型机求解大型稀疏问题的Krylov子空间法.[J].国防科技大学学报,1993,15(1):51-55.[点击复制] |
| Yang Yuexiang,Li Xiaomei.The Krylov Subspace Methods to Solve Large Sparse Problems on Supercomputers[J].Journal of National University of Defense Technology,1993,15(1):51-55[点击复制] |
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| 巨型机求解大型稀疏问题的Krylov子空间法 |
| 杨岳湘, 李晓梅 |
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(电子计算机系)
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| 摘要: |
| 求解大型稀疏问题最流行的方法是建立在子空间投影技术之上的。这类方法的主要吸引力是仅需要使用矩阵向量乘法。我们给出PCG、GMRES、Lanczos 和 Davidson 算法及在 YH-Ⅰ上的实现，然后比较每一方法的优缺点，并尽可能讨论其并行执行。 |
| 关键词: 矩阵，大型稀疏问题，Krylov子空间 |
| DOI： |
| 投稿日期：1991-10-25 |
| 基金项目:国家自然科学基金资助项目 |
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| The Krylov Subspace Methods to Solve Large Sparse Problems on Supercomputers |
| Yang Yuexiang, Li Xiaomei |
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(Department of Computer Science)
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| Abstract: |
| The most popular methods to solve large sparse problems are based on projection techniques on appropriate subspaces. The main attraction of these methods is that they only require using the matrix by vector multiplications. We give the implementations of PCG、GMRES、Lanczos's method and Davidson's method on YH-1.We then compare their advantages and disadvantages. Finally we discuss the parallel implementations as possible as we can. |
| Keywords: matrix,large sparse problems,Krylao subspace |
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