sadatnfs

sadatnfs

sadatnfs

sadatnfs

echo "deb https://apt.repos.intel.com/mkl all main" > /etc/apt/sources.list.d/intel-mkl.list && \
echo "deb https://apt.repos.intel.com/tbb all main" > /etc/apt/sources.list.d/intel-tbb.list && \
echo "deb https://apt.repos.intel.com/daal all main" > /etc/apt/sources.list.d/intel-daal.list && \
echo "deb https://apt.repos.intel.com/mpi all main" > /etc/apt/sources.list.d/intel-mpi.list && \
apt-get update


## Set a bunch of envvars (perhaps throw these in your bashrc)
MKL_LIB_PATH="/opt/intel/compilers_and_libraries/linux/mkl/lib/intel64_lin"  \
MKL="-L/opt/intel/compilers_and_libraries/linux/mkl/lib/intel64_lin -Wl,--no-as-needed -lmkl_gf_lp64 -Wl,--start-group -lmkl_gnu_thread -lmkl_cdft_core -lmkl_core -Wl,--end-group -fopenmp -ldl -lpthread -lm"  \

sadatnfs

call plug#begin()

Plug 'brooth/far.vim'
Plug 'SirVer/ultisnips'
Plug 'honza/vim-snippets'

Plug 'scrooloose/nerdtree'  " file list
Plug 'majutsushi/tagbar'  " show tags in a bar (functions etc) for easy browsing
Plug 'vim-airline/vim-airline'  " make statusline awesome

sadatnfs

# Prepping your environment #
# 1. Set up WSL with ffmpeg: https://streaminglearningcenter.com/encoding/running-ffmpeg-on-windows-subsystem-for-linux.html
# 2. Install Miniconda in your WSL environment: https://dev.to/sfpear/miniconda-in-wsl-3642
# 3. Install Python packages: 
#     pip uninstall ffmpeg
#     pip uninstall ffmpeg-python
#     pip install ffmpeg-python git+https://github.com/SYSTRAN/faster-whisper
# 4. [IF YOU HAVE A COMPATIBLE NVIDIA GPU] Install all CUDA stuff, which can be painful
#    The instructions in this section should work clean: https://github.com/SYSTRAN/faster-whisper?tab=readme-ov-file#install-with-pip-linux-only
#    But it might be easiest to use the Docker image.