Fixed argument problem with omp

* fix/smooth-kernel: (25 commits)
  We now use the fmm operator to calculate the interaction lists
  Add a Gaussian kernel with the option of changing the kernel coefficients
  Add two defines   1) LOW_RANK_USE_SVD to enable truncated svd rather than partial aca   2) LOW_RANK_CHECK to check the reconstruction error
  problem with fft and settings is fixed
  Add a modified 'one_over_r' matrix kernel that adds a diagonal value.
  Add 'smooth_tag' for smooth kernels + trait to detect at compile-time if a kernel is smooth.
  Update smooth kernel implementation:
  Update smooth kernel implementation:
  matrix_kernel: complete gaussian matrix kernel to add an 'evaluate' member function
  Modification of the default coefficient of the Gaussian kernel. Test how to modify the coefficient in the main code.
  added comments
  Same as previous commit
  added functions to print the settings of the fmm operator (approximation, optimisation, kernel)
  Added Gaussian kernel
  We have a loss of precision with the low-rank approximation in uniform and Chebyshev compared to dense and fft
  add symmetric tag
  Correct format for doxygen documentation
  Code works if Gaussian coeff is 1.0 otherwise the results are wrong if we set
  The direct calculation is validated (verified from pyhton)
  delete dead code
  ...

  1) LOW_RANK_USE_SVD to enable truncated svd rather than partial aca
  2) LOW_RANK_CHECK to check the reconstruction error

benchs: change extension of out to log file to be able to display it in the web browser from gitlab's pipelines artifacts

benchs: the input-file is only compatible for dimension 2 and we want to consider dimensions (1 2 3)

  - ensure to reserve all the bora node with all the cores using --exclusive
  - ensure to not be binded to a single core using HFI_NO_CPUAFFINITY=1
  - update input parameters for the experiments

a kernel is smooth.

- remove the 'is_smooth' tag from smooth matrix kernels.
- implement "self evaluation" member method for smooth matrix kernels.
- add new trait that detects if a matrix kernel has a "self evaluation" member method.
- update p2p and full direct implementations to call "self evaluation" when dealing with smooth kernels.

- remove the 'is_smooth' tag from source kernel.
- implement "self evaluation" member method for smooth kernel.
- add new trait that detects if a matrix kernel has "self evaluation" member method.
- update p2p and full direct implementation to call "self evaluation"
- when dealing with smooth kernels.