Solving large-scale semidefinite programs in parallel |
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Authors: | Madhu V. Nayakkankuppam |
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Affiliation: | (1) Computational Finance Group, Bloomberg LP, 731 Lexington Avenue, New York, NY 10022, USA |
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Abstract: | We describe an approach to the parallel and distributed solution of large-scale, block structured semidefinite programs using the spectral bundle method. Various elements of this approach (such as data distribution, an implicitly restarted Lanczos method tailored to handle block diagonal structure, a mixed polyhedral-semidefinite subdifferential model, and other aspects related to parallelism) are combined in an implementation called LAMBDA, which delivers faster solution times than previously possible, and acceptable parallel scalability on sufficiently large problems. This work was supported in part by NSF grants DMS-0215373 and DMS-0238008. |
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Keywords: | Semidefinite programming Eigenvalue optimization Subgradient bundle methods Lanczos method Parallel computing |
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