Because of their simplicity, efficiency and ability for parallelism, FFT-based methods are very attractive in the context of numerical periodic homogenization, especially when compared to standard FE codes used in the same context. The AMITEX_FFTP code, developed at CEA for its applications, is available for the research and education community [5]. The code provides: - a simple user-interface, - versatility (various microstructures, behaviors or loading can be defined), - high-performance computing with an efficient distributed parallel implementation relying on the open source 2decomp library [1]. Some specificities of the code are reported below: - the possibility to choose between using the small strain assumption or the complete finite strain framework, - the compatibility with the umat interface that allows for users to implement their own non-linear behavior directly or through the MFRONT code generator [2], - the convergence acceleration technique that drastically accelerates the conventional fix-point algorithm, and do not require the evaluation of the tangent behavior (for non-linear simulations), - the implementation of the concept of composite voxels [4], to account for voxels crossed by an interface, reducing the level of spurious oscillations, - the efficient MPI implementation that allows to performs simulations of billions of voxels on thousands of cores [3]. AMITEX_FFTP allows pushing back (far away) the computation limits (time and memory) observed with standard FE codes used in this specific context (simulation on heterogeneous unit-cells). REFERENCES [1] https://github.com/2decomp-fft/2decomp-fft. [2] Mfront, tfel.sourceforge.net. [3] Y. Chen, L. Gélébart, C. Chateau, M. Bornert, C. Sauder, and A. King. Analysis of the damage initiation in a sic/sic composite tube from a direct comparison between large-scale numerical simulation and synchrotron x-ray micro-computed tomography. Int. J. Solids Struct., 161:111 – 126, 2019. [4] L Gélébart and F. Ouaki. Filtering material properties to improve fft-based methods for numerical homogenization. Journal of Computational Physics, 294(0):90 – 95, 2015. [5] Lionel Gélébart. https://amitexfftp.github.io/AMITEX/index.html. 2022.