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#define | id "%d" |
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#define | cgerr(x) printf(x); |
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#define | CG_OK (0) |
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#define | CG_ERR (1) |
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#define | CG_TRUE (1) |
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#define | CG_FALSE (0) |
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#define | CG_PRECOND_DIAG (10) |
| | Use diagonal as the pre-conditioner.
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#define | CG_PRECOND_CHOL (11) |
| | Use Cholesky factor as the pre-conditioner.
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#define | CG_NO_PRECOND (12) |
| | Use direct solver.
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#define | CG_STATUS_SOLVED (100) |
| | System is solved to desired accuracy within maximum iteration.
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#define | CG_STATUS_MAXITER (101) |
| | System reaches maximum iteration.
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#define | CG_STATUS_FAILED (102) |
| | CG fails to converge.
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#define | CG_STATUS_UNKNOWN (104) |
| | CG status is not known. Solution not yet started.
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#define | CG_STATUS_DIRECT (105) |
| | CG serves as a wrapper for direct solver.
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#define | MIN(a, b) (((a)<(b))?(a):(b)) |
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#define | MAX(a, b) (((a)>(b))?(a):(b)) |
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Header for basic types and routine list.
Given a set of positive definite linear systems
, adpcg solves them adaptively with pre-conditioning conjugate gradient method.
The routine is employed in HDSDP.
- Author
- Wenzhi Gao, Shanghai University of Finance and Economics
- Date
- Aug 29th, 2022