class |
EstimatorBasicAvg |
Basic average case estimator for matrix sparsity:
sp = 1 - Math.pow(1-sp1*sp2, k)
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class |
EstimatorBasicWorst |
Basic average case estimator for matrix sparsity:
sp = Math.min(1, sp1 * k) * Math.min(1, sp2 * k).
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class |
EstimatorBitsetMM |
This estimator implements a naive but rather common approach of boolean matrix
multiplies which allows to infer the exact non-zero structure and thus is
also useful for sparse result preallocation.
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class |
EstimatorDensityMap |
This estimator implements an approach called density maps, as introduced in
David Kernert, Frank Köhler, Wolfgang Lehner: SpMacho - Optimizing Sparse
Linear Algebra Expressions with Probabilistic Density Estimation.
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class |
EstimatorLayeredGraph |
This estimator implements an approach based on a so-called layered graph,
introduced in
Edith Cohen.
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class |
EstimatorMatrixHistogram |
This estimator implements a remarkably simple yet effective
approach for incorporating structural properties into sparsity
estimation.
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class |
EstimatorSample |
This estimator implements an approach based on row/column sampling
Yongyang Yu, MingJie Tang, Walid G.
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class |
EstimatorSampleRa |
This estimator implements an approach based on row/column sampling
Rasmus Resen Amossen, Andrea Campagna, Rasmus Pagh:
Better Size Estimation for Sparse Matrix Products.
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