| Commit message (Collapse) | Author | Age |
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(could come back to redux after it has been vectorized,
and could serve as a starting point for that)
also make the abs2 functor vectorizable (for real types).
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* make Matrix2f (and similar) vectorized using linear path
* fix a couple of warnings and compilation issues with ICC and gcc 3.3/3.4
(cannot get Transform compiles with gcc 3.3/3.4, see the FIXME)
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which is even better optimized by the compiler.
* Quaternion no longer inherits MatrixBase. Instead it stores the coefficients
using a Matrix<> and provides only relevant methods.
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* fix a couple of compilation issues when unrolling is disabled
* reduce default unrolling limit to a more reasonable value
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This include:
- cwise Pow,Sin,Cos,Exp...
- cwise Greater and other comparison operators
- .any(), .all() and partial reduction
- random
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Rename DefaultLostFlagMask --> HerediraryBits
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* Fix a mistake in CwiseNullary.
* Added a CoreDeclarions header that declares only the forward declarations
and related basic stuffs.
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-finline-limit=1000 to gcc to get good performance. By the way some cleanup.
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part of a matrix. Triangular also provide an optimised method for forward
and backward substitution. Further optimizations regarding assignments and
products might come later.
Updated determinant() to take into account triangular matrices.
Started the QR module with a QR decompostion algorithm.
Help needed to build a QR algorithm (eigen solver) based on it.
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- vector to vector assign
- PartialRedux
- Vectorization criteria of Product
- returned type of normalized
- SSE integer mul
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* rename OperatorEquals -> Assign
* move Util.h and FwDecl.h to a util/ subdir
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Currently only the following platform/operations are supported:
- SSE2 compatible architecture
- compiler compatible with intel's SSE2 intrinsics
- float, double and int data types
- fixed size matrices with a storage major dimension multiple of 4 (or 2 for double)
- scalar-matrix product, component wise: +,-,*,min,max
- matrix-matrix product only if the left matrix is vectorizable and column major
or the right matrix is vectorizable and row major, e.g.:
a.transpose() * b is not vectorized with the default column major storage.
To use it you must define EIGEN_VECTORIZE and EIGEN_INTEL_PLATFORM.
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seems appropriate to me.
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* added "all" and "any" special redux operators
* added support bool matrices
* added support for cost model of STL functors via ei_functor_traits
(By default ei_functor_traits query the functor member Cost)
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when to evaluate arguments and when to meta-unroll.
-use it in Product to determine when to eval args. not yet used
to determine when to unroll. for now, not used anywhere else but
that'll follow.
-fix badness of my last commit
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-- currently 3 flags: RowMajor, Lazy and Large
-- only RowMajor actually used for now
* many minor improvements
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as well as partial redux (vertical or horizontal redux).
Includes shortcuts for: sum, minCoeff and maxCoeff.
There is no shortcut for the partial redux.
* Added a generic *visitor* mini framework. A visitor is a custom object
sequentially applied on each coefficient with knowledge of its value and
coordinates.
It is currentlly used to implement minCoeff(int*,int*) and maxCoeff(int*,int*).
findBiggestCoeff is now a shortcut for "this->cwiseAbs().maxCoeff(i,j)"
* Added coeff-wise min and max.
* fixed an issue with ei_pow(int,int) and gcc < 4.3 or ICC
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Gael Guennebaud
Benoit Jacob