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Python Binding to NVRTC
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pynvrtc - Python Bindings to NVRTC


The pynvrtc package is a Python binding for NVRTC, the CUDA runtime compilation library from NVIDIA. This library takes CUDA source input and produces NVIDIA PTX output suitable for execution on NVIDIA GPUs on any platform. Please see the CUDA 9.2 documentation for a complete description of NVRTC.


The pynvrtc package does not have any external dependencies and can be installed with pip or easy_install.

$ pip install pynvrtc

Note, however, that the package does require the NVRTC library to be present at runtime. See below for instructions on how to set the search path.

Using pynvrtc

There are two primary interfaces with pynvrtc; a low-level interface which provides users with direct access to the NVRTC API, and a high-level interface which provides a Pythonic API for the compiler routines in NVRTC.

Low-Level Interface

The low-level interface can be found in the pynvrtc.interface module. An instance of the interface can be obtained by calling the NVRTCInterface constructor:

from pynvrtc.interface import NVRTCInterface

inter = NVRTCInterface()

By default, the NVRTCInterface object will attempt to load the NVRTC shared library from LD_LIBRARY_PATH on Linux, DYLD_LIBRARY_PATH on Mac, or PATH on Windows. An optional parameter to the NVRTCInterface constructor provides the absolute path to the NVRTC shared library and overwrites the system search path. For example, on Linux:

from pynvrtc.interface import NVRTCInterface

inter = NVRTCInterface('/usr/local/cuda-9.2/lib64/')

NOTE: It is important that the specified binary match the architecture of the Python interpreter under which your program is running.

Once an interface object is created, it provides access to all of the NVRTC API functions as regular Python functions. However, instead of returning a NVRTC status code, each function returns either a string (for output functions) or None. If an error occurs within NVRTC, an NVRTCException exception is raised with the corresponding status code.

Note that the nvrtcGetProgramLogSize and nvrtcGetPTXSize functions are not exposed. Instead, the nvrtcGetProgramLog and nvrtcGetPTX functions automatically determine the correct size and return a UTF-8 encoded Python string.

Full Example:

from pynvrtc.interface import NVRTCInterface, NVRTCException

src = ... ## Populate CUDA source code

inter = NVRTCInterface()

    prog = inter.nvrtcCreateProgram(src, '', [], []);
    inter.nvrtcCompileProgram(prog, ['-ftz=true'])
    ptx = inter.nvrtcGetPTX(prog)
except NVRTCException as e:
    print('Error: %s' % repr(e))

High-Level Interface

For clients wanting a higher-level interface to NVRTC, the Program class in pynvrtc.compiler provides such an interface. The usage is similar to that of the NVRTCInterface class, but the API is more Pythonic and you do not need to worry about maintaining NVRTC objects.

from pynvrtc.compiler import Program, ProgramException

src = ... ## Populate CUDA source code

    prog = Program(src, '')
    ptx = prog.compile(['-ftz=1'])
except ProgramException as e:
    print('Error: %s' % repr(e))

As with NVRTCInterface, the Program constructor accepts an optional path to the NVRTC library.

Please see samples/ for a complete example of a CUDA source to PTX compiler using the higher-level interface.

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