RozDavid
commented
3 years ago Hey @ToniRV,
Thanks a lot for the feedback and also for the ideas. I think it would be really nice to have this runtime operation, but you are also perfectly right this can't couse perfromance loss.
I am sadly not a pro here, but did a short research on Eigen Dynamic memory allocation and found this. Source.
Here is this constructor:
inline DenseStorage(int size, int rows, int) : m_data(internal::aligned_new<T>(size)), m_rows(rows) {}Here, the m_data member is the actual array of coefficients of the matrix. As you see, it is dynamically allocated. Rather than calling new[] or malloc(), as you can see, we have our own internal::aligned_new defined in src/Core/util/Memory.h. What it does is that if vectorization is enabled, then it uses a platform-specific call to allocate a 128-bit-aligned array, as that is very useful for vectorization with both SSE2 and AltiVec. If vectorization is disabled, it amounts to the standard new[].
I believe if we don't change the directives EIGEN_DONT_ALIGN and EIGEN_MAX_ALIGN_BYTES (source) in the CMake build or with #defines, the memory allignment should be allright and the matrices will be automatically vectorized.
What do you think of this? Do you think if I replace the initialization with internal::aligned_new<T> that could bridge the performance gap?
ToniRV
Addressing my own issue #55, using dynamic sized semantic prior matrices and initialization in runtime. Reading number of labels from the launch file as a rosparam.
I believe the biggest concern could be the performance issue, for this here is a comparison of timings on the provided simulated semantic rosbag file.
With static labels
With dynamic labels