| /external/eigen/unsupported/test/ |
| kronecker_product.cpp | 13 #include "sparse.h"
88 // DM = dense matrix; SM = sparse matrix
154 // test kroneckerProduct(SM,SM,SM) with sparse pattern
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| /external/llvm/include/llvm/Analysis/ |
| SparsePropagation.h | 1 //===- SparsePropagation.h - Sparse Conditional Property Propagation ------===//
10 // This file implements an abstract sparse conditional propagation algorithm,
109 /// SparseSolver - This class is a general purpose solver for Sparse Conditional
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| /external/smali/smali/src/test/resources/LexerTest/ |
| RealSmaliFileTest.smali | 119 sparse-switch p1, :sswitch_data_c
139 .sparse-switch
143 .end sparse-switch
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| /external/autotest/client/deps/iwcap/src/ |
| Makefile | 69 $(Q)$(MAKE) all CC="REAL_CC=$(CC) CHECK=\"sparse -Wall\" cgcc"
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| /external/bsdiff/ |
| bspatch.1 | 65 is a positive integer. An offset value of -1 denotes a sparse extent, namely a
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| /external/ceres-solver/internal/ceres/ |
| block_evaluate_preparer.cc | 49 // Point the jacobian blocks directly into the block sparse matrix.
|
| dynamic_compressed_row_jacobian_writer.h | 31 // A jacobian writer that directly writes to dynamic compressed row sparse
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| /external/chromium-trace/catapult/third_party/mapreduce/mapreduce/ |
| kv_pb.py | 168 def _BuildTagLookupTable(sparse, maxtag, default=None):
169 return tuple([sparse.get(i, default) for i in xrange(0, 1+maxtag)])
346 def _BuildTagLookupTable(sparse, maxtag, default=None):
347 return tuple([sparse.get(i, default) for i in xrange(0, 1+maxtag)])
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| /external/deqp/external/vulkancts/modules/vulkan/api/ |
| vktApiBufferTests.cpp | 229 return tcu::TestStatus::fail("Bind sparse buffer memory failed! (requested memory size: " + de::toString(size) + ")");
245 TCU_THROW(NotSupportedError, "Sparse bindings feature is not supported");
248 TCU_THROW(NotSupportedError, "Sparse buffer residency feature is not supported");
251 TCU_THROW(NotSupportedError, "Sparse aliased residency feature is not supported");
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| /external/eigen/Eigen/src/PaStiXSupport/ |
| PaStiXSupport.h | 413 * \brief Sparse direct LU solver based on PaStiX library
419 * The vectors or matrices X and B can be either dense or sparse.
421 * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
528 * \brief A sparse direct supernodal Cholesky (LLT) factorization and solver based on the PaStiX library
533 * The vectors or matrices X and B can be either dense or sparse
535 * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
609 * \brief A sparse direct supernodal Cholesky (LLT) factorization and solver based on the PaStiX library
614 * The vectors or matrices X and B can be either dense or sparse
616 * \tparam MatrixType the type of the sparse matrix A, it must be a SparseMatrix<>
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| /external/eigen/Eigen/src/SparseCore/ |
| SparseDenseProduct.h | 46 typedef Sparse StorageKind;
138 static Scalar get(const _RhsNested &rhs, Index outer, Sparse = Sparse())
277 // dense = dense * sparse
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| SparseView.h | 22 typedef Sparse StorageKind;
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| /external/eigen/bench/ |
| sparse_transpose.cpp | 61 // eigen sparse matrices
|
| /external/eigen/bench/spbench/ |
| test_sparseLU.cpp | 41 /* Fill the matrix with sparse matrix stored in Matrix-Market coordinate column-oriented format */
|
| /external/eigen/doc/ |
| B01_Experimental.dox | 26 \li Sparse
|
| SparseLinearSystems.dox | 2 /** \eigenManualPage TopicSparseSystems Solving Sparse Linear Systems
3 In Eigen, there are several methods available to solve linear systems when the coefficient matrix is sparse. Because of the special representation of this class of matrices, special care should be taken in order to get a good performance. See \ref TutorialSparse for a detailed introduction about sparse matrices in Eigen. This page lists the sparse solvers available in Eigen. The main steps that are common to all these linear solvers are introduced as well. Depending on the properties of the matrix, the desired accuracy, the end-user is able to tune those steps in order to improve the performance of its code. Note that it is not required to know deeply what's hiding behind these steps: the last section presents a benchmark routine that can be easily used to get an insight on the performance of all the available solvers.
7 \section TutorialSparseDirectSolvers Sparse solvers
20 <td>Recommended for very sparse and not too large problems (e.g., 2D Poisson eq.)</td></tr>
38 <td>Requires the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">SuiteSparse</a> package, \b GPL </td>
41 <td>Requires the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">SuiteSparse</a> package, \b GPL </td>
48 <td> requires the <a href="http://www.cise.ufl.edu/research/sparse/SuiteSparse/">SuiteSparse</a> package, \b GPL </td><td>recommended for linear least-squares problems, has a rank-revealing feature</tr>
|
| /external/eigen/test/eigen2/ |
| eigen2_sparse_vector.cpp | 10 #include "sparse.h"
|
| /external/opencv3/modules/core/include/opencv2/core/ |
| mat.hpp | [all...] |
| /external/opencv3/modules/cudaoptflow/include/opencv2/ |
| cudaoptflow.hpp | 83 /** @brief Base interface for sparse optical flow algorithms.
88 /** @brief Calculates a sparse optical flow.
149 /** @brief Class used for calculating a sparse optical flow.
151 The class can calculate an optical flow for a sparse feature set using the
|
| /external/webrtc/talk/app/webrtc/ |
| fakemetricsobserver.h | 61 // comes to sparse enum types, like the SSL ciphers in the IANA registry.
|
| /frameworks/data-binding/extensions/baseAdapters/src/main/java/android/databinding/adapters/ |
| TableLayoutBindingAdapter.java | 89 // putting true in this sparse array indicates that the
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| /frameworks/support/v7/recyclerview/src/android/support/v7/util/ |
| TileList.java | 24 * A sparse collection of tiles sorted for efficient access.
|
| /prebuilts/gcc/linux-x86/host/x86_64-w64-mingw32-4.8/lib/gcc/x86_64-w64-mingw32/4.8.3/plugin/include/ |
| bitmap.h | 23 /* Implementation of sparse integer sets as a linked list.
25 This sparse set representation is suitable for sparse sets with an
38 This representation is very space-efficient for large sparse sets, and
43 the set is very sparse.
74 Additionally, the linked-list sparse set representation supports
96 The storage requirements for linked-list sparse sets are O(E), with E->N
97 in the worst case (a sparse set with large distances between the values
101 sparse sets. The canonical example in GCC is, of course, the "set of
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| /prebuilts/go/darwin-x86/src/runtime/ |
| hash_test.go | 200 sparse(t, 32, 6)
201 sparse(t, 40, 6)
202 sparse(t, 48, 5)
203 sparse(t, 56, 5)
204 sparse(t, 64, 5)
205 sparse(t, 96, 4)
206 sparse(t, 256, 3)
207 sparse(t, 2048, 2)
209 func sparse(t *testing.T, n int, k int) { func
|
| /prebuilts/go/linux-x86/src/runtime/ |
| hash_test.go | 200 sparse(t, 32, 6)
201 sparse(t, 40, 6)
202 sparse(t, 48, 5)
203 sparse(t, 56, 5)
204 sparse(t, 64, 5)
205 sparse(t, 96, 4)
206 sparse(t, 256, 3)
207 sparse(t, 2048, 2)
209 func sparse(t *testing.T, n int, k int) { func
|
