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update doc

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Gael Guennebaud 2009-07-28 17:11:15 +02:00
parent de8b795895
commit 508f06ac0f
1 changed files with 12 additions and 16 deletions
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doc/I02_HiPerformance.dox
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@ -63,6 +63,14 @@ handled by a single GEMM-like call are correctly detected.
Make sure the matrix product is the top most expression.</td> Make sure the matrix product is the top most expression.</td>
</tr> </tr>
<tr> <tr>
<td>\code m1 += s1 * (m2 * m3).lazy(); \endcode</td>
<td>\code m1 += s1 * m2 * m3; // using a naive product \endcode</td>
<td>\code m1 += (s1 * m2 * m3).lazy(); \endcode</td>
<td>Even though this expression is evaluated without temporary, it is actually even
worse than the previous case because here the .lazy() enforces Eigen to use a
naive (and slow) evaluation of the product.</td>
</tr>
<tr>
<td>\code m1 = m1 + m2 * m3; \endcode</td> <td>\code m1 = m1 + m2 * m3; \endcode</td>
<td>\code temp = (m2 * m3).lazy(); m1 = m1 + temp; \endcode</td> <td>\code temp = (m2 * m3).lazy(); m1 = m1 + temp; \endcode</td>
<td>\code m1 += (m2 * m3).lazy(); \endcode</td> <td>\code m1 += (m2 * m3).lazy(); \endcode</td>
@ -70,24 +78,12 @@ handled by a single GEMM-like call are correctly detected.
and so the matrix product will be immediately evaluated.</td> and so the matrix product will be immediately evaluated.</td>
</tr> </tr>
<tr> <tr>
<td>\code m1 += ((s1 * m2).transpose() * m3).lazy(); \endcode</td>
<td>\code temp = (s1*m2).transpose(); m1 = (temp * m3).lazy(); \endcode</td>
<td>\code m1 += (s1 * m2.transpose() * m3).lazy(); \endcode</td>
<td>This is because our expression analyzer stops at the first expression which cannot
be converted to a scalar multiple of a conjugate and therefore the nested scalar
multiple cannot be properly extracted.</td>
</tr>
<tr>
<td>\code m1 += (m2.conjugate().transpose() * m3).lazy(); \endcode</td>
<td>\code temp = m2.conjugate().transpose(); m1 += (temp * m3).lazy(); \endcode</td>
<td>\code m1 += (m2.adjoint() * m3).lazy(); \endcode</td>
<td>Same reason. Use .adjoint() or .transpose().conjugate()</td>
</tr>
<tr>
<td>\code m1 += ((s1*m2).block(....) * m3).lazy(); \endcode</td> <td>\code m1 += ((s1*m2).block(....) * m3).lazy(); \endcode</td>
<td>\code temp = (s1*m2).block(....); m1 += (temp * m3).lazy(); \endcode</td> <td>\code temp = (s1*m2).block(....); m1 += (temp * m3).lazy(); \endcode</td>
<td>\code m1 += (s1 * m2.block(....) * m3).lazy(); \endcode</td> <td>\code m1 += (s1 * m2.block(....) * m3).lazy(); \endcode</td>
<td>Same reason.</td> <td>This is because our expression analyzer is currently not able to extract trivial
expressions nested in a Block expression. Therefore the nested scalar
multiple cannot be properly extracted.</td>
</tr> </tr>
</table> </table>
@ -129,7 +125,7 @@ Of course all these remarks hold for all other kind of products that we will des
</tr> </tr>
<tr> <tr>
<td>SYR</td> <td>SYR</td>
<td>m.seductive<LowerTriangular>().rankUpdate(v,s)</td> <td>m.sefadjointView<LowerTriangular>().rankUpdate(v,s)</td>
<td></td> <td></td>
<td>Computes m += s * v * v.adjoint()</td> <td>Computes m += s * v * v.adjoint()</td>
</tr> </tr>