MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)

MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)

MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)

MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)

MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)

MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)

MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)

MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)

MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)

MPI.jl and Elemental.jl provide access to the existing MPI ecosystem of libraries. 4. GPU computing: The Julia GPU compiler provides the ability to run Julia code natively on GPUs. There is a rich ecosys- array operations distributed across workers, as outlined above. A mention must be made of Julia's GPU programming ecosystem, which includes: 1. CUDA.jl wraps the various CUDA libraries and supports compiling (GNU), others optionally permit placing hidden arguments directly after the character argument (Intel, PGI). For example, Fortran subroutines of the form subroutine test(str1, str2) character(len=*)