JULIANA (Julia Unification Layer for Intel, AMD, Nvidia and Apple)

Juliana is a syntax translation tool for CUDA.jl package to KernelAbstractions.jl. It will translate a big portion of CUDA.jl functions and macros to KernelAbstractions.jl equivalent constructs.

Installation and usage:

Installation

git clone https://github.com/101001000/Juliana.jl
julia -e 'using Pkg; Pkg.develop(path="./Juliana.jl")'

Usage

using Juliana

# Translate single file
Juliana.translate_file(
    "path/to/file.jl",
    "path/to/output"
)

# Translate multiple files
Juliana.translate_files(
    ["path/to/file1.jl", "path/to/file2.jl"],
    ["path/to/output1", "path/to/output2"]
)
# Note that for multiple files, the number of output paths must be equal to the number of input files

# Translate an entire package
Juliana.translate_pkg(
    "path/to/package",
    "path/to/output-package"
)

Additional arguments:

• extra_knames: Additional list of kernel names to be included.
• extra_kfuncs: Additional list of kernel functions to be included in the output.
• gpu_sim: GPU simulator to be used. Default: "NVIDIA_GeForce_GTX_950"

Use this arguments when Juliana is not able to find the proper definitions of the kernels or functions.

Extra considerations:

Juliana don't work well with GPU-CPU function overload (e.g writing a function with the same name which has different body depending if runs on the GPU or the CPU). It will attemp to fix some of this cases by itself, but it has some limitations. A clear separation of the GPU and CPU functions is recommended.

Juliana also has some issues when overriding existing CUDA functions (e.g. creating your own device function). Try to avoid clashing CUDA symbols with your own ones.

Feature support

Feature	Support Status
CUDA Kernels	Full support
Shared Memory	Full support (static only)
Device Functions	Full support
Synchronization	Full support
Thread Indexing	Full support
Memory Management	Full support
Stream Operations	Partial support
Dynamic Parallelism	Not supported
Texture Memory	Not supported
Warp Operations	Not supported

Warning list

Code	Type	Description	Impact
WN001	UntranslatedWarning	Untranslated CUDA symbol	Non-critical
WN002	SyncBlockingForzedWarning	CUDA @sync forced to be blocking	Performance impact
WN003	DynamicSMArrayWarning	Dynamic Shared Memory Arrays not allowed inside KernelAbstractions kernels	Breaking
WN004	DynamicSMArrayToStaticSMArrayWarning	Dynamic Shared Memory Array converted to Static Shared Memory Array	Requires const size
WN005	IncompatibleSymbolRemovedWarning	CUDA Symbol removed by incompatibility	Breaking
WN006	ThreadSizeNotChecked	Thread size not checked for max size	Performance risk
WN007	ThreadSizeTooLarge	Thread size shouldn't exceed max size for compatibility	Compatibility risk
WN008	DeviceAttributeWarning	Device attributes are loaded from a config file emulating Nvidia GPU	Simulation only
WN009	ImplicitCudaNamespace	Implicit namespace candidate symbol found	Code conflict risk
WN010	UnsupportedKWArg	Keyword argument in kernel call not supported	Breaking
WN011	AttributeSimulated	A hardcoded attribute has been used to replace a CUDA attribute	Simulation only
WN012	FreeMemorySimulated	Free memory simulated with 4GB default for some backends	Resource limitation
WN013	UnnecessaryCUDAPrefix	Code used wrongly a CUDA namespace prefix	Code style
WN014	UnprocessedKernels	Some kernels were not found	Breaking
WN015	TransitiveCUDAPrefix	Code used a CUDA namespace prefix for accessing other module	Code style
WN016	NoConstMemory	CUDA Const device array specifier removed	Performance impact
WN017	DeviceFunctionOverloaded	GPU function with context propagation used in CPU	Potential conflict

Translated projects

Julia Rodinia benchmarks. Full translation, no changes required.

Julia MiniBUDE. Full translation, minimal changes required (device function name clash).

Julia BabelStream. Full translation, minimal changes required (device function name clash).

Oceananigans.jl. Full translation, no changes required. Only AMD/NVIDIA (FFTW requires unified memory).

Citation

Proceeding of the congress where the project was presented are not released yet.