OpenCV 3 SVM train with large Data - c++

Question

I recently switched from OpenCV 2.4.6 to 3.0.
My Code looks like this:
Ptr<ml::SVM> pSVM = ml::SVM::create();
pSVM->->setType(cv::ml::SVM::C_SVC);
pSVM->setKernel(cv::ml::SVM::LINEAR);
pSVM->->setC(1);
cv::Ptr<cv::ml::TrainData> TrainData = cv::ml::TrainData::create(TrainMatrix, cv::ml::ROW_SAMPLE, Labels);
//TrainMatrix is a cv::Mat with 35000 rows and 1900 cols and float values in it. One Feature per row.
//Labels is a std::vector<int> with 35000 Elements with 1 and -1 in it.
pSVM->trainAuto(TrainData, 10, cv::ml::SVM::getDefaultGrid(cv::ml::SVM::C), cv::ml::SVM::getDefaultGrid(cv::ml::SVM::GAMMA), cv::ml::SVM::getDefaultGrid(cv::ml::SVM::P),
cv::ml::SVM::getDefaultGrid(cv::ml::SVM::NU), cv::ml::SVM::getDefaultGrid(cv::ml::SVM::COEF), cv::ml::SVM::getDefaultGrid(cv::ml::SVM::DEGREE), false);
When my program reaches the trainAuto method is crashes and in the error message stands that it cannot allocate 524395968 bytes. This number seems a little bit high. Before the crash the program consumes about 400 MB in Debug Mode.
If I put a smaller matrix (about 500 rows) in the method everything runs normally.
Has anyone same problems and knows a solution to it?