A novel parallel algorithm for large-scale Fock matrix construction with small locally distributed memory architectures: RT parallel algorithm
We developed a novel parallel algorithm for large‐scale Fock matrix calculation with small locally distributed memory architectures, and named it the “RT parallel algorithm.” The RT parallel algorithm actively involves the concept of integral screening, which is indispensable for reduction of comput...
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| Published in: | Journal of computational chemistry Vol. 23; no. 14; pp. 1337 - 1346 |
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| Main Authors: | , , , , , , , |
| Format: | Journal Article |
| Language: | English |
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15.11.2002
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| ISSN: | 0192-8651, 1096-987X |
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| Abstract | We developed a novel parallel algorithm for large‐scale Fock matrix calculation with small locally distributed memory architectures, and named it the “RT parallel algorithm.” The RT parallel algorithm actively involves the concept of integral screening, which is indispensable for reduction of computing times with large‐scale biological molecules. The primary characteristic of this algorithm is parallel efficiency, which is achieved by well‐balanced reduction of both communicating and computing volume. Only the density matrix data necessary for Fock matrix calculations are communicated, and the data once communicated are reutilized for calculations as many times as possible. The RT parallel algorithm is a scalable method because required memory volume does not depend on the number of basis functions. This algorithm automatically includes a partial summing technique that is indispensable for maintaining computing accuracy, and can also include some conventional methods to reduce calculation times. In our analysis, the RT parallel algorithm had better performance than other methods for massively parallel processors. The RT parallel algorithm is most suitable for massively parallel and distributed Fock matrix calculations for large‐scale biological molecules with more than thousands of basis functions. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 1337–1346, 2002 |
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| AbstractList | We developed a novel parallel algorithm for large-scale Fock matrix calculation with small locally distributed memory architectures, and named it the "RT parallel algorithm." The RT parallel algorithm actively involves the concept of integral screening, which is indispensable for reduction of computing times with large-scale biological molecules. The primary characteristic of this algorithm is parallel efficiency, which is achieved by well-balanced reduction of both communicating and computing volume. Only the density matrix data necessary for Fock matrix calculations are communicated, and the data once communicated are reutilized for calculations as many times as possible. The RT parallel algorithm is a scalable method because required memory volume does not depend on the number of basis functions. This algorithm automatically includes a partial summing technique that is indispensable for maintaining computing accuracy, and can also include some conventional methods to reduce calculation times. In our analysis, the RT parallel algorithm had better performance than other methods for massively parallel processors. The RT parallel algorithm is most suitable for massively parallel and distributed Fock matrix calculations for large-scale biological molecules with more than thousands of basis functions. We developed a novel parallel algorithm for large-scale Fock matrix calculation with small locally distributed memory architectures, and named it the "RT parallel algorithm." The RT parallel algorithm actively involves the concept of integral screening, which is indispensable for reduction of computing times with large-scale biological molecules. The primary characteristic of this algorithm is parallel efficiency, which is achieved by well-balanced reduction of both communicating and computing volume. Only the density matrix data necessary for Fock matrix calculations are communicated, and the data once communicated are reutilized for calculations as many times as possible. The RT parallel algorithm is a scalable method because required memory volume does not depend on the number of basis functions. This algorithm automatically includes a partial summing technique that is indispensable for maintaining computing accuracy, and can also include some conventional methods to reduce calculation times. In our analysis, the RT parallel algorithm had better performance than other methods for massively parallel processors. The RT parallel algorithm is most suitable for massively parallel and distributed Fock matrix calculations for large-scale biological molecules with more than thousands of basis functions.We developed a novel parallel algorithm for large-scale Fock matrix calculation with small locally distributed memory architectures, and named it the "RT parallel algorithm." The RT parallel algorithm actively involves the concept of integral screening, which is indispensable for reduction of computing times with large-scale biological molecules. The primary characteristic of this algorithm is parallel efficiency, which is achieved by well-balanced reduction of both communicating and computing volume. Only the density matrix data necessary for Fock matrix calculations are communicated, and the data once communicated are reutilized for calculations as many times as possible. The RT parallel algorithm is a scalable method because required memory volume does not depend on the number of basis functions. This algorithm automatically includes a partial summing technique that is indispensable for maintaining computing accuracy, and can also include some conventional methods to reduce calculation times. In our analysis, the RT parallel algorithm had better performance than other methods for massively parallel processors. The RT parallel algorithm is most suitable for massively parallel and distributed Fock matrix calculations for large-scale biological molecules with more than thousands of basis functions. We developed a novel parallel algorithm for large‐scale Fock matrix calculation with small locally distributed memory architectures, and named it the “RT parallel algorithm.” The RT parallel algorithm actively involves the concept of integral screening, which is indispensable for reduction of computing times with large‐scale biological molecules. The primary characteristic of this algorithm is parallel efficiency, which is achieved by well‐balanced reduction of both communicating and computing volume. Only the density matrix data necessary for Fock matrix calculations are communicated, and the data once communicated are reutilized for calculations as many times as possible. The RT parallel algorithm is a scalable method because required memory volume does not depend on the number of basis functions. This algorithm automatically includes a partial summing technique that is indispensable for maintaining computing accuracy, and can also include some conventional methods to reduce calculation times. In our analysis, the RT parallel algorithm had better performance than other methods for massively parallel processors. The RT parallel algorithm is most suitable for massively parallel and distributed Fock matrix calculations for large‐scale biological molecules with more than thousands of basis functions. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 1337–1346, 2002 We developed a novel parallel algorithm for large‐scale Fock matrix calculation with small locally distributed memory architectures, and named it the “ RT parallel algorithm.” The RT parallel algorithm actively involves the concept of integral screening, which is indispensable for reduction of computing times with large‐scale biological molecules. The primary characteristic of this algorithm is parallel efficiency, which is achieved by well‐balanced reduction of both communicating and computing volume. Only the density matrix data necessary for Fock matrix calculations are communicated, and the data once communicated are reutilized for calculations as many times as possible. The RT parallel algorithm is a scalable method because required memory volume does not depend on the number of basis functions. This algorithm automatically includes a partial summing technique that is indispensable for maintaining computing accuracy, and can also include some conventional methods to reduce calculation times. In our analysis, the RT parallel algorithm had better performance than other methods for massively parallel processors. The RT parallel algorithm is most suitable for massively parallel and distributed Fock matrix calculations for large‐scale biological molecules with more than thousands of basis functions. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 1337–1346, 2002 |
| Author | Takashima, Hajime Tanabe, Kazutoshi Nagashima, Umpei Inabata, Shinjiro Obara, Shigeru Miyakawa, Nobuaki Yamada, So Kitamura, Kunihiro |
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| Snippet | We developed a novel parallel algorithm for large‐scale Fock matrix calculation with small locally distributed memory architectures, and named it the “RT... We developed a novel parallel algorithm for large‐scale Fock matrix calculation with small locally distributed memory architectures, and named it the “ RT... We developed a novel parallel algorithm for large-scale Fock matrix calculation with small locally distributed memory architectures, and named it the "RT... |
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| SubjectTerms | Algorithms Biological materials Calculations Combinatorial Chemistry Techniques Computer Simulation Functions integral screening Large scale systems large-scale SCF massively parallel and distributed Fock matrix construction Matrix algebra Models, Theoretical Molecules parallel efficiency RT parallel algorithm Time Factors |
| Title | A novel parallel algorithm for large-scale Fock matrix construction with small locally distributed memory architectures: RT parallel algorithm |
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