Klagarge/MSE-GPU-Cuda
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chore: delivery preparation

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This commit is contained in:
Rémi Heredero
2025-11-27 18:49:46 +01:00
parent 09ee32383f
commit bda49a20c9
24 changed files with 140 additions and 140 deletions
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6
Student_Cuda_Image/out/Rippling_performance.html
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@@ -87,7 +87,7 @@ Designed by <a href="https://github.com/cpptest/cpptest">CppTest</a>
<td style="width:30%" class="tablecell_success">1</td>
<td style="width:30%" class="tablecell_success">0</td>
<td style="width:30%" class="tablecell_success">100%</td>
<td style="width:10%" class="tablecell_success">8.000000</td>
<td style="width:10%" class="tablecell_success">16.000000</td>
</tr>
</table>
<hr />
@@ -106,7 +106,7 @@ Designed by <a href="https://github.com/cpptest/cpptest">CppTest</a>
<td style="width:10%" class="tablecell_success">1</td>
<td style="width:10%" class="tablecell_success">0</td>
<td style="width:10%" class="tablecell_success">100%</td>
<td style="width:10%" class="tablecell_success">8.000000</td>
<td style="width:10%" class="tablecell_success">16.000000</td>
</tr>
</table>
<hr />
@@ -123,7 +123,7 @@ Designed by <a href="https://github.com/cpptest/cpptest">CppTest</a>
<td class="tablecell_success">performanceOnly</td>
<td class="tablecell_success">0</td>
<td class="tablecell_success">true</td>
<td class="tablecell_success">8.000000</td>
<td class="tablecell_success">16.000000</td>
</tr>
</table>
<p class="spaced"><a href="#top">Back to top</a>

14
Student_Cuda_Image/src/core/01_student/01_Rippling/host/Rippling_BestGrid.h
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@@ -18,15 +18,15 @@ namespace rippling {
public:
static Grid get() {
const int MP = Hardware::getMPCount();
const int CORE_MP = Hardware::getCoreCountMP();
const int MP = Hardware::getMPCount();
const int CORE_MP = Hardware::getCoreCountMP();
// TODO Rippling
dim3 dg(MP, 1, 1);
dim3 db(CORE_MP, 4, 1);
Grid grid(dg, db);
// TODO Rippling
dim3 dg(MP, 1, 1);
dim3 db(CORE_MP, 4, 1);
Grid grid(dg, db);
return grid;
return grid;
}

4
Student_Cuda_Image/src/main/mainBenchmark.cpp
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@@ -34,8 +34,8 @@ static void raytracingCM2SM();
int mainBenchmark() {
// Please, un a la fois!
rippling();
// mandelbrot(); // Conseil : use nFixe (by example nMin=nMax=80)
// rippling();
mandelbrot(); // Conseil : use nFixe (by example nMin=nMax=80)
//
// raytracingGM();
// raytracingSM();

4
Student_Cuda_Image/src/main/mainBruteforce.cpp
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@@ -44,8 +44,8 @@ int mainBrutforce() {
Matlab matlab;
// Please, un a la fois!
rippling(&matlab);
// mandelbrot(&matlab); // Conseil : use nFixe (by example nMin=nMax=100)
// rippling(&matlab);
mandelbrot(&matlab); // Conseil : use nFixe (by example nMin=nMax=100)
// raytracingGM(&matlab);
// raytracingCM(&matlab);
// raytracingSM(&matlab);

4
Student_Cuda_Image/src/main/mainImage.cpp
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@@ -31,8 +31,8 @@ int mainImage(const Args& args) {
ImageOption zoomable(true, true, true, true);
ImageOption nozoomable(false, true, false, false);
Viewer<RipplingProvider> rippling(nozoomable, 0, 0); // imageOption px py
// Viewer<MandelbrotProvider> mandelbrot(zoomable, 0, 0);
// Viewer<RipplingProvider> rippling(nozoomable, 0, 0); // imageOption px py
Viewer<MandelbrotProvider> mandelbrot(zoomable, 0, 0);
// Viewer<RaytracingProviderGM> raytracingGM(nozoomable, 0, 0);
// Viewer<RaytracingProviderCM> raytracingCM(nozoomable, 0, 0);
// Viewer<RaytracingProviderSM> raytracingSM(nozoomable, 0, 0);

6
Student_Cuda_Image/src/main/mainTest.cpp
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@@ -34,9 +34,9 @@ static void raytracing();
int mainTest() {
// activer ci-dessous seulement le TP voulu (pas tous)
rippling();
//mandelbrot(); // fp16 only
//raytracing(); // voir code ci-dessous pour activer la version voulue
rippling();
mandelbrot(); // fp16 only
// raytracing(); // voir code ci-dessous pour activer la version voulue
return EXIT_SUCCESS;
}