NVRTC

1. Introduction

NVRTC is a runtime compilation library for CUDA C++. It accepts CUDA C++ source code in character string form and creates handles that can be used to obtain the PTX. The PTX string generated by NVRTC can be loaded by cuModuleLoadData and cuModuleLoadDataEx, and linked with other modules by cuLinkAddData of the CUDA Driver API. This facility can often provide optimizations and performance not possible in a purely offline static compilation.

In the absence of NVRTC (or any runtime compilation support in CUDA), users needed to spawn a separate process to execute nvcc at runtime if they wished to implement runtime compilation in their applications or libraries, and, unfortunately, this approach has the following drawbacks:
  • The compilation overhead tends to be higher than necessary, and
  • End users are required to install nvcc and related tools which make it complicated to distribute applications that use runtime compilation.

NVRTC addresses these issues by providing a library interface that eliminates overhead associated with spawning separate processes, disk I/O, etc., while keeping application deployment simple.

NVRTC is a preview feature in the current release and any or all parts of this specification are subject to change in the next CUDA release.

2. Getting Started

2.1. System Requirements

NVRTC requires the following system configuration:
  • Operating System: Linux x86_64, Linux ppc64le, Linux aarch64, Windows x86_64, or Mac OS X.
  • GPU: Any GPU with CUDA Compute Capability 2.0 or higher.
  • CUDA Toolkit and Driver.

2.2. Installation

NVRTC is part of the CUDA Toolkit release and the components are organized as follows in the CUDA toolkit installation directory:
  • On Windows:
    • include\nvrtc.h
    • bin\nvrtc64_80.dll
    • bin\nvrtc-builtins64_80.dll
    • lib\x64\nvrtc.lib
    • doc\pdf\NVRTC_User_Guide.pdf
  • On Linux:
    • include/nvrtc.h
    • lib64/libnvrtc.so
    • lib64/libnvrtc.so.8.0
    • lib64/libnvrtc.so.8.0.<build version>
    • lib64/libnvrtc-builtins.so
    • lib64/libnvrtc-builtins.so.8.0
    • lib64/libnvrtc-builtins.so.8.0.<build version>
    • doc/pdf/NVRTC_User_Guide.pdf
  • On Mac OS X:
    • include/nvrtc.h
    • lib/libnvrtc.dylib
    • lib/libnvrtc.8.0.dylib
    • lib/libnvrtc-builtins.dylib
    • lib/libnvrtc-builtins.8.0.dylib
    • doc/pdf/NVRTC_User_Guide.pdf

3. User Interface

This chapter presents the API of NVRTC. Basic usage of the API is explained in Basic Usage. Note that the API may change in the production release based on user feedback.

3.1. Error Handling

NVRTC defines the following enumeration type and function for API call error handling.

Enumerations

enum nvrtcResult
The enumerated type nvrtcResult defines API call result codes. NVRTC API functions return nvrtcResult to indicate the call result.

Functions

const char* nvrtcGetErrorString ( nvrtcResult result )
nvrtcGetErrorString is a helper function that returns a string describing the given nvrtcResult code, e.g., NVRTC_SUCCESS to "NVRTC_SUCCESS". For unrecognized enumeration values, it returns "NVRTC_ERROR unknown".

Enumerations

enum nvrtcResult

Values
NVRTC_SUCCESS = 0
NVRTC_ERROR_OUT_OF_MEMORY = 1
NVRTC_ERROR_PROGRAM_CREATION_FAILURE = 2
NVRTC_ERROR_INVALID_INPUT = 3
NVRTC_ERROR_INVALID_PROGRAM = 4
NVRTC_ERROR_INVALID_OPTION = 5
NVRTC_ERROR_COMPILATION = 6
NVRTC_ERROR_BUILTIN_OPERATION_FAILURE = 7
NVRTC_ERROR_NO_NAME_EXPRESSIONS_AFTER_COMPILATION = 8
NVRTC_ERROR_NO_LOWERED_NAMES_BEFORE_COMPILATION = 9
NVRTC_ERROR_NAME_EXPRESSION_NOT_VALID = 10
NVRTC_ERROR_INTERNAL_ERROR = 11

Functions

const char* nvrtcGetErrorString ( nvrtcResult result )
nvrtcGetErrorString is a helper function that returns a string describing the given nvrtcResult code, e.g., NVRTC_SUCCESS to "NVRTC_SUCCESS". For unrecognized enumeration values, it returns "NVRTC_ERROR unknown".
Parameters
result
CUDA Runtime Compilation API result code.
Returns

Message string for the given nvrtcResult code.

Description

3.2. General Information Query

NVRTC defines the following function for general information query.

Functions

nvrtcResult nvrtcVersion ( int* major, int* minor )
nvrtcVersion sets the output parameters major and minor with the CUDA Runtime Compilation version number.

Functions

nvrtcResult nvrtcVersion ( int* major, int* minor )
nvrtcVersion sets the output parameters major and minor with the CUDA Runtime Compilation version number.
Parameters
major
CUDA Runtime Compilation major version number.
minor
CUDA Runtime Compilation minor version number.
Description

3.3. Compilation

NVRTC defines the following type and functions for actual compilation.

Typedefs

typedef _nvrtcProgram *  nvrtcProgram
nvrtcProgram is the unit of compilation, and an opaque handle for a program.

Functions

nvrtcResult nvrtcAddNameExpression ( nvrtcProgram prog, const char* name_expression )
nvrtcAddNameExpression notes the given name expression denoting a __global__ function or function template instantiation.
nvrtcResult nvrtcCompileProgram ( nvrtcProgram prog, int  numOptions, const char** options )
nvrtcCompileProgram compiles the given program.
nvrtcResult nvrtcCreateProgram ( nvrtcProgram* prog, const char* src, const char* name, int  numHeaders, const char** headers, const char** includeNames )
nvrtcCreateProgram creates an instance of nvrtcProgram with the given input parameters, and sets the output parameter prog with it.
nvrtcResult nvrtcDestroyProgram ( nvrtcProgram* prog )
nvrtcDestroyProgram destroys the given program.
nvrtcResult nvrtcGetLoweredName ( nvrtcProgram prog, const char* name_expression, const char** lowered_name )
nvrtcGetLoweredName extracts the lowered (mangled) name for a __global__ function or function template instantiation, and updates *lowered_name to point to it. The memory containing the name is released when the NVRTC program is destroyed by nvrtcDestroyProgram. The identical name expression must have been previously provided to nvrtcAddNameExpression.
nvrtcResult nvrtcGetPTX ( nvrtcProgram prog, char* ptx )
nvrtcGetPTX stores the PTX generated by the previous compilation of prog in the memory pointed by ptx.
nvrtcResult nvrtcGetPTXSize ( nvrtcProgram prog, size_t* ptxSizeRet )
nvrtcGetPTXSize sets ptxSizeRet with the size of the PTX generated by the previous compilation of prog (including the trailing NULL).
nvrtcResult nvrtcGetProgramLog ( nvrtcProgram prog, char* log )
nvrtcGetProgramLog stores the log generated by the previous compilation of prog in the memory pointed by log.
nvrtcResult nvrtcGetProgramLogSize ( nvrtcProgram prog, size_t* logSizeRet )
nvrtcGetProgramLogSize sets logSizeRet with the size of the log generated by the previous compilation of prog (including the trailing NULL).

Typedefs

typedef _nvrtcProgram * nvrtcProgram

nvrtcProgram is the unit of compilation, and an opaque handle for a program. To compile a CUDA program string, an instance of nvrtcProgram must be created first with nvrtcCreateProgram, then compiled with nvrtcCompileProgram.

Functions

nvrtcResult nvrtcAddNameExpression ( nvrtcProgram prog, const char* name_expression )
nvrtcAddNameExpression notes the given name expression denoting a __global__ function or function template instantiation.
Parameters
prog
CUDA Runtime Compilation program.
name_expression
constant expression denoting a __global__ function or function template instantiation.
Description

The identical name expression string must be provided on a subsequent call to nvrtcGetLoweredName to extract the lowered name.

See also:

nvrtcGetLoweredName

nvrtcResult nvrtcCompileProgram ( nvrtcProgram prog, int  numOptions, const char** options )
nvrtcCompileProgram compiles the given program.
Description

It supports compile options listed in Supported Compile Options.

nvrtcResult nvrtcCreateProgram ( nvrtcProgram* prog, const char* src, const char* name, int  numHeaders, const char** headers, const char** includeNames )
nvrtcCreateProgram creates an instance of nvrtcProgram with the given input parameters, and sets the output parameter prog with it.
Parameters
prog
CUDA Runtime Compilation program.
src
CUDA program source.
name
CUDA program name. name can be NULL; "default_program" is used when name is NULL.
numHeaders
Number of headers used. numHeaders must be greater than or equal to 0.
headers
Sources of the headers. headers can be NULL when numHeaders is 0.
includeNames
Name of each header by which they can be included in the CUDA program source. includeNames can be NULL when numHeaders is 0.
Description

See also:

nvrtcDestroyProgram

nvrtcResult nvrtcDestroyProgram ( nvrtcProgram* prog )
nvrtcDestroyProgram destroys the given program.
Parameters
prog
CUDA Runtime Compilation program.
Description

See also:

nvrtcCreateProgram

nvrtcResult nvrtcGetLoweredName ( nvrtcProgram prog, const char* name_expression, const char** lowered_name )
nvrtcGetLoweredName extracts the lowered (mangled) name for a __global__ function or function template instantiation, and updates *lowered_name to point to it. The memory containing the name is released when the NVRTC program is destroyed by nvrtcDestroyProgram. The identical name expression must have been previously provided to nvrtcAddNameExpression.
Parameters
prog
CUDA Runtime Compilation program.
name_expression
constant expression denoting a __global__ function or function template instantiation.
lowered_name
initialized by the function to point to a C string containing the lowered (mangled) name corresponding to the provided name expression.
Description

See also:

nvrtcAddNameExpression

nvrtcResult nvrtcGetPTX ( nvrtcProgram prog, char* ptx )
nvrtcGetPTX stores the PTX generated by the previous compilation of prog in the memory pointed by ptx.
Parameters
prog
CUDA Runtime Compilation program.
ptx
Compiled result.
Description

See also:

nvrtcGetPTXSize

nvrtcResult nvrtcGetPTXSize ( nvrtcProgram prog, size_t* ptxSizeRet )
nvrtcGetPTXSize sets ptxSizeRet with the size of the PTX generated by the previous compilation of prog (including the trailing NULL).
Parameters
prog
CUDA Runtime Compilation program.
ptxSizeRet
Size of the generated PTX (including the trailing NULL).
Description

See also:

nvrtcGetPTX

nvrtcResult nvrtcGetProgramLog ( nvrtcProgram prog, char* log )
nvrtcGetProgramLog stores the log generated by the previous compilation of prog in the memory pointed by log.
Parameters
prog
CUDA Runtime Compilation program.
log
Compilation log.
Description

See also:

nvrtcGetProgramLogSize

nvrtcResult nvrtcGetProgramLogSize ( nvrtcProgram prog, size_t* logSizeRet )
nvrtcGetProgramLogSize sets logSizeRet with the size of the log generated by the previous compilation of prog (including the trailing NULL).
Parameters
prog
CUDA Runtime Compilation program.
logSizeRet
Size of the compilation log (including the trailing NULL).
Description

Note that compilation log may be generated with warnings and informative messages, even when the compilation of prog succeeds.

See also:

nvrtcGetProgramLog

3.4. Supported Compile Options

NVRTC supports the compile options below. Option names with two preceding dashs (--) are long option names and option names with one preceding dash (-) are short option names. Short option names can be used instead of long option names. When a compile option takes an argument, an assignment operator (=) is used to separate the compile option argument from the compile option name, e.g., "--gpu-architecture=compute_20". Alternatively, the compile option name and the argument can be specified in separate strings without an assignment operator, .e.g, "--gpu-architecturend""compute_20". Single-character short option names, such as -D, -U, and -I, do not require an assignment operator, and the compile option name and the argument can be present in the same string with or without spaces between them. For instance, "-D=<def>", "-D<def>", and "-D <def>" are all supported.

The valid compiler options are:

  • Compilation targets
    • --gpu-architecture=<arch> (-arch)

      Specify the name of the class of GPU architectures for which the input must be compiled.

      • Valid <arch>s:
        • compute_20

        • compute_30

        • compute_35

        • compute_50

        • compute_52

        • compute_53

      • Default: compute_20

  • Separate compilation / whole-program compilation
    • --device-c (-dc)

      Generate relocatable code that can be linked with other relocatable device code. It is equivalent to --relocatable-device-code=true.

    • --device-w (-dw)

      Generate non-relocatable code. It is equivalent to --relocatable-device-code=false.

    • --relocatable-device-code={true|false} (-rdc)

      Enable (disable) the generation of relocatable device code.
      • Default: false

  • Debugging support
    • --device-debug (-G)

      Generate debug information.

    • --generate-line-info (-lineinfo)

      Generate line-number information.

  • Code generation
    • --maxrregcount=<N> (-maxrregcount)

      Specify the maximum amount of registers that GPU functions can use. Until a function-specific limit, a higher value will generally increase the performance of individual GPU threads that execute this function. However, because thread registers are allocated from a global register pool on each GPU, a higher value of this option will also reduce the maximum thread block size, thereby reducing the amount of thread parallelism. Hence, a good maxrregcount value is the result of a trade-off. If this option is not specified, then no maximum is assumed. Value less than the minimum registers required by ABI will be bumped up by the compiler to ABI minimum limit.

    • --ftz={true|false} (-ftz)

      When performing single-precision floating-point operations, flush denormal values to zero or preserve denormal values. --use_fast_math implies --ftz=true.
      • Default: false

    • --prec-sqrt={true|false} (-prec-sqrt)

      For single-precision floating-point square root, use IEEE round-to-nearest mode or use a faster approximation. --use_fast_math implies --prec-sqrt=false.
      • Default: true

    • --prec-div={true|false} (-prec-div)

      For single-precision floating-point division and reciprocals, use IEEE round-to-nearest mode or use a faster approximation. --use_fast_math implies --prec-div=false.
      • Default: true

    • --fmad={true|false} (-fmad)

      Enables (disables) the contraction of floating-point multiplies and adds/subtracts into floating-point multiply-add operations (FMAD, FFMA, or DFMA). --use_fast_math implies --fmad=true.
      • Default: true

    • --use_fast_math (-use_fast_math)

      Make use of fast math operations. --use_fast_math implies --ftz=true--prec-div=false--prec-sqrt=false--fmad=true.

  • Preprocessing
    • --define-macro=<def> (-D)

      <def> can be either <name> or <name=definitions>.
      • <name>

        Predefine <name> as a macro with definition 1.

      • <name>=<definition>

        The contents of <definition> are tokenized and preprocessed as if they appeared during translation phase three in a #define directive. In particular, the definition will be truncated by embedded new line characters.

    • --undefine-macro=<def> (-U)

      Cancel any previous definition of <def>.

    • --include-path=<dir> (-I)

      Add the directory <dir> to the list of directories to be searched for headers. These paths are searched after the list of headers given to nvrtcCreateProgram.

    • --pre-include=<header> (-include)

      Preinclude <header> during preprocessing.

  • Language Dialect
    • --std=c++11 (-std=c++11)

      Set language dialect to C++11.

    • --builtin-move-forward={true|false} (-builtin-move-forward)

      Provide builtin definitions of std::move and std::forward, when C++11 language dialect is selected.
      • Default: true

    • --builtin-initializer-list={true|false} (-builtin-initializer-list)

      Provide builtin definitions of std::initializer_list class and member functions when C++11 language dialect is selected.
      • Default: true

  • Misc.
    • --disable-warnings (-w)

      Inhibit all warning messages.

    • --restrict (-restrict)

      Programmer assertion that all kernel pointer parameters are restrict pointers.

    • --device-as-default-execution-space (-default-device)

      Treat entities with no execution space annotation as __device__ entities.

3.5. Host Helper

NVRTC defines the following functions for easier interaction with host code.

Functions

template < typename T >nvrtcResult nvrtcGetTypeName ( std::​string* result )
nvrtcGetTypeName stores the source level name of the template type argument T in the given std::string location.

Functions

template < typename T >

nvrtcResult nvrtcGetTypeName ( std::​string* result ) [inline]
nvrtcGetTypeName stores the source level name of the template type argument T in the given std::string location.
Parameters
result
pointer to std::string in which to store the type name.
Description

This function is only provided when the macro NVRTC_GET_TYPE_NAME is defined with a non-zero value. It uses abi::__cxa_demangle or UnDecorateSymbolName function calls to extract the type name, when using gcc/clang or cl.exe compilers, respectively. If the name extraction fails, it will return NVRTC_INTERNAL_ERROR, otherwise *result is initialized with the extracted name.

4. Language

Unlike the offline nvcc compiler, NVRTC is meant for compiling only device CUDA C++ code. It does not accept host code or host compiler extensions in the input code, unless otherwise noted.

4.1. Execution Space

NVRTC uses __host__ as the default execution space, and it generates an error if it encounters any host code in the input. That is, if the input contains entities with explicit __host__ annotations or no execution space annotation, NVRTC will emit an error. __host__ __device__ functions are treated as device functions.

NVRTC provides a compile option, --device-as-default-execution-space, that enables an alternative compilation mode, in which entities with no execution space annotations are treated as __device__ entities.

4.2. Separate Compilation

NVRTC itself does not provide any linker. Users can, however, use cuLinkAddData in the CUDA Driver API to link the generated relocatable PTX code with other relocatable code. To generate relocatable PTX code, the compile option --relocatable-device-code=true or --device-c is required.

4.3. Dynamic Parallelism

NVRTC supports dynamic parallelism under the following conditions:

Example: Dynamic Parallelism provides a simple example.

4.4. Integer Size

Different operating systems define integer type sizes differently. Linux x86_64 and Mac OS X implement LP64, and Windows x86_64 implements LLP64.

Table 1. Integer sizes in bits for LLP64 and LP64
  short int long longlong pointers and size_t
LLP64 16 32 32 64 64
LP64 16 32 64 64 64

NVRTC implements LP64 on Linux and Mac OS X, and LLP64 on Windows.

4.5. Predefined Macros

  • __CUDACC_RTC__: useful for distinguishing between runtime and offline nvcc compilation in user code.
  • __CUDACC__: defined with same semantics as with offline nvcc compilation.
  • __CUDACC_RDC__: defined with same semantics as with offline nvcc compilation.
  • __CUDA_ARCH__: defined with same semantics as with offline nvcc compilation.
  • __CUDACC_VER_MAJOR__: defined with the major version number as returned by nvrtcVersion.
  • __CUDACC_VER_MINOR__: defined with the minor version number as returned by nvrtcVersion.
  • __CUDACC_VER_BUILD__: defined with the build version number.
  • __CUDACC_VER__: Defined with the full version number of nvcc, represented as __CUDACC_VER_MAJOR__ * 10000 + __CUDACC_VER_MINOR__ * 100 + __CUDACC_VER_BUILD__ .
  • NULL: null pointer constant.
  • __cplusplus

4.6. Predefined Types

  • clock_t
  • size_t
  • ptrdiff_t
  • Predefined types such as dim3, char4, etc., that are available in the CUDA Runtime headers when compiling offline with nvcc are also available, unless otherwise noted.

4.7. Builtin Functions

Builtin functions provided by the CUDA Runtime headers when compiling offline with nvcc are available, unless otherwise noted.

5. Basic Usage

This section of the document uses a simple example, Single-Precision α⋅X Plus Y (SAXPY), shown in Figure 1 to explain what is involved in runtime compilation with NVRTC. For brevity and readability, error checks on the API return values are not shown. The complete code listing is available in Example: SAXPY.

Figure 1. CUDA source string for SAXPY
const char *saxpy = "                                           \n\
extern \"C\" __global__                                         \n\
void saxpy(float a, float *x, float *y, float *out, size_t n)   \n\
{                                                               \n\
  size_t tid = blockIdx.x * blockDim.x + threadIdx.x;           \n\
  if (tid < n) {                                                \n\
    out[tid] = a * x[tid] + y[tid];                             \n\
  }                                                             \n\
}                                                               \n";

First, an instance of nvrtcProgram needs to be created. Figure 2 shows creation of nvrtcProgram for SAXPY. As SAXPY does not require any header, 0 is passed as numHeaders, and NULL as headers and includeNames.

Figure 2. nvrtcProgram creation for SAXPY
nvrtcProgram prog;
nvrtcCreateProgram(&prog,         // prog
                   saxpy,         // buffer
                   "saxpy.cu",    // name
                   0,             // numHeaders
                   NULL,          // headers
                   NULL);         // includeNames

If SAXPY had any #include directives, the contents of the files that are #include'd can be passed as elements of headers, and their names as elements of includeNames. For example, #include <foo.h> and #include <bar.h> would require 2 as numHeaders, { "<contents of foo.h>", "<contents of bar.h>" } as headers, and { "foo.h", "bar.h" } as includeNames (<contents of foo.h> and <contents of bar.h> must be replaced by the actual contents of foo.h and bar.h). Alternatively, the compile option -I can be used if the header is guaranteed to exist in the file system at runtime.

Once the instance of nvrtcProgram for compilation is created, it can be compiled by nvrtcCompileProgram as shown in Figure 3. Two compile options are used in this example, --gpu-architecture=compute_20 and --fmad=false, to generate code for the compute_20 architecture and to disable the contraction of floating-point multiplies and adds/subtracts into floating-point multiply-add operations. Other combinations of compile options can be used as needed and Supported Compile Options lists valid compile options.

Figure 3. Compilation of SAXPY for compute_20 with FMAD enabled
const char *opts[] = {"--gpu-architecture=compute_20",
                      "--fmad=false"};
nvrtcCompileProgram(prog,     // prog
                    2,        // numOptions
                    opts);    // options

After the compilation completes, users can obtain the program compilation log and the generated PTX as Figure 4 shows. NVRTC does not generate valid PTX when the compilation fails, and it may generate program compilation log even when the compilation succeeds if needed.

A nvrtcProgram can be compiled by nvrtcCompileProgram multiple times with different compile options, and users can only retrieve the PTX and the log generated by the last compilation.

Figure 4. Obtaining generated PTX and program compilation log
// Obtain compilation log from the program.
size_t logSize;
nvrtcGetProgramLogSize(prog, &logSize);
char *log = new char[logSize];
nvrtcGetProgramLog(prog, log);
// Obtain PTX from the program.
size_t ptxSize;
nvrtcGetPTXSize(prog, &ptxSize);
char *ptx = new char[ptxSize];
nvrtcGetPTX(prog, ptx);

When the instance of nvrtcProgram is no longer needed, it can be destroyed by nvrtcDestroyProgram as shown in Figure 5.

Figure 5. Destruction of nvrtcProgram
nvrtcDestroyProgram(&prog);

The generated PTX can be further manipulated by the CUDA Driver API for execution or linking. Figure 6 shows an example code sequence for execution of the generated PTX.

Figure 6. Execution of SAXPY using the PTX generated by NVRTC
CUdevice cuDevice;
CUcontext context;
CUmodule module;
CUfunction kernel;
cuInit(0);
cuDeviceGet(&cuDevice, 0);
cuCtxCreate(&context, 0, cuDevice);
cuModuleLoadDataEx(&module, ptx, 0, 0, 0);
cuModuleGetFunction(&kernel, module, "saxpy");
size_t n = size_t n = NUM_THREADS * NUM_BLOCKS;
size_t bufferSize = n * sizeof(float);
float a = ...;
float *hX = ..., *hY = ..., *hOut = ...;
CUdeviceptr dX, dY, dOut;
cuMemAlloc(&dX, bufferSize);
cuMemAlloc(&dY, bufferSize);
cuMemAlloc(&dOut, bufferSize);
cuMemcpyHtoD(dX, hX, bufferSize);
cuMemcpyHtoD(dY, hY, bufferSize);
void *args[] = { &a, &dX, &dY, &dOut, &n };
cuLaunchKernel(kernel,
               NUM_THREADS, 1, 1,   // grid dim
               NUM_BLOCKS, 1, 1,    // block dim
               0, NULL,             // shared mem and stream
               args,                // arguments
               0);
cuCtxSynchronize();
cuMemcpyDtoH(hOut, dOut, bufferSize);

6. Accessing Lowered Names

6.1. Introduction

NVRTC will mangle __global__ function names as specified by the IA64 ABI. If the generated PTX is being loaded using the CUDA Driver API, the kernel function must be looked up by name, but this is hard to do when the name has been mangled. To address this problem, NVRTC provides API functions that map source level __global__ function/template instantiation names to the mangled names present in the generated PTX.

The two API functions nvrtcAddNameExpression and nvrtcGetLoweredName work together to provide this functionality. First, a string denoting the source level 'name expression' for the __global__ function/template instantiation is provided to nvrtcAddNameExpression. Then, the program is compiled with nvrtcCompileProgram. During compilation, NVRTC will parse the name expression string as a C++ constant expression at the end of the user program. The constant expression must provide the address of a __global__ function/template instantiation. Finally, the function nvrtcGetLoweredName is called with the original name expression and it returns a pointer to the lowered name. The lowered name can be used to refer to the kernel in the CUDA Driver API.

NVRTC guarantees that any __global__ function/template instantiation referenced in a call to nvrtcAddNameExpression will be present in the generated PTX (if the definition is available in the input source code).

6.2. Example

Example: Using Lowered Name lists a complete runnable example. Some relevant snippets:

  1. The GPU source code ('gpu_program') contains definitions of various __global__ functions and function templates:
    const char *gpu_program = " \n\
    static __global__ void f1(int *result) { *result = 10; } \n\
    namespace N1 { \n\
    namespace N2 { \n\
    __global__ void f2(int *result) { *result = 20; } \n\
    } \n\
    } \n\
    template<typename T> \n\
    __global__ void f3(int *result) { *result = sizeof(T); } \n\
    \n";
    
    
  2. The host source code invokes nvrtcAddNameExpression with various name expressions referring to __global__ functions and function template instantiations:
    name_vec.push_back("&f1");
    ..
    name_vec.push_back("N1::N2::f2");
    ..
    name_vec.push_back("f3<int>");
    ..
    name_vec.push_back("f3<double>");
    
    // add name expressions to NVRTC. Note this must be done before
    // the program is compiled.
    for (size_t i = 0; i < name_vec.size(); ++i)
    NVRTC_SAFE_CALL(nvrtcAddNameExpression(prog, name_vec[i].c_str()));
    
    
  3. The GPU program is then compiled with nvrtcCompileProgram. The generated PTX is loaded on the GPU. The mangled names of the __global__ function and template instantiations are looked up:
    // note: this call must be made after NVRTC program has been
    // compiled and before it has been destroyed.
    NVRTC_SAFE_CALL(nvrtcGetLoweredName(
    prog,
    name_vec[i].c_str(), // name expression
    &name // lowered name
    ));
    
    
  4. The mangled name is then used to launch the kernel using the CUDA Driver API:
    CUfunction kernel;
    CUDA_SAFE_CALL(cuModuleGetFunction(&kernel, module, name));
    ...
    CUDA_SAFE_CALL(
    cuLaunchKernel(kernel,
    1, 1, 1, // grid dim
    1, 1, 1, // block dim
    0, NULL, // shared mem and stream
    args, 0));    
      

6.3. Notes

  1. Sequence of calls: All name expressions must be added using nvrtcAddNameExpression before the NVRTC program is compiled with nvrtcCompileProgram. This is required because the name expressions are parsed at the end of the user program, and may trigger template instantiations. The lowered names must be looked up by calling nvrtcGetLoweredName only after the NVRTC program has been compiled, and before it has been destroyed. The pointer returned by nvrtcGetLoweredName points to memory owned by NVRTC, and this memory is freed when the NVRTC program has been destroyed (nvrtcDestroyProgram). Thus the correct sequence of calls is : nvrtcAddNameExpression, nvrtcCompileProgram, nvrtcGetLoweredName, nvrtcDestroyProgram.
  2. Identical Name Expressions: The name expression string passed to nvrtcAddNameExpression and nvrtcGetLoweredName must have identical characters. For example, "foo" and "foo " are not identical strings, even though semantically they refer to the same entity (foo), because the second string has a extra whitespace character.
  3. Constant Expressions: The characters in the name expression string are parsed as a C++ constant expression at the end of the user program. Any errors during parsing will cause compilation failure and compiler diagnostics will be generated in the compilation log. The constant expression must refer to the address of a __global__ function or function template instantiation.
  4. Address of overloaded function: If the NVRTC source code has multiple overloaded __global__ functions, then the name expression must use a cast operation to disambiguate. However, casts are not allowed in constant expression for C++ dialects before C++11. If using such name expressions, please compile the code in C++11 or later dialect using the '-std' command line flag. Example: Consider that the GPU code string contains:
    __global__ void foo(int) { }
    __global__ void foo(char) { }
    
    The name expression '(void(*)(int))foo' correctly disambiguates 'foo(int)', but the program must be compiled in C++11 or later dialect (e.g. '-std=c++11') because casts are not allowed in pre-C++11 constant expressions.

7. Interfacing With Template Host Code

7.1. Introduction

In some scenarios, it is useful to instantiate __global__ function templates in device code based on template arguments in host code. The NVRTC helper function nvrtcGetTypeName can be used to extract the source level name of a type in host code, and this string can be used to instantiate a __global__ function template and get the mangled name of the instantiation using the nvrtcAddNameExpression and nvrtcGetLoweredName functions.

nvrtcGetTypeName is defined inline in the NVRTC header file, and is available when the macro NVRTC_GET_TYPE_NAME is defined with a non-zero value. It uses the abi::__cxa_demangle and UnDecorateSymbolName host code functions when using gcc/clang and cl.exe compilers, respectively. Users may need to specify additional header paths and libraries to find the host functions used (abi::__cxa_demangle / UnDecorateSymbolName). See the build instructions for the example below for reference (Build Instruction).

7.2. Example

Example: Using nvrtcGetTypeName lists a complete runnable example. Some relevant snippets:

  1. The GPU source code ('gpu_program') contains definitions of a __global__ function template:
    const char *gpu_program = " \n\
    namespace N1 { struct S1_t { int i; double d; }; } \n\
    template<typename T> \n\
    __global__ void f3(int *result) { *result = sizeof(T); } \n\
    \n";
    
    
    
  2. The host code function getKernelNameForType creates the name expression for a __global__ function template instantiation based on the host template type T. The name of the type T is extracted using nvrtcGetTypeName:
    template <typename T>
    std::string getKernelNameForType(void)
    {
    // Look up the source level name string for the type "T" using
    // nvrtcGetTypeName() and use it to create the kernel name
    std::string type_name;
    NVRTC_SAFE_CALL(nvrtcGetTypeName<T>(&type_name));
    return std::string("f3<") + type_name + ">";
    }
    
    
    
  3. The name expressions are presented to NVRTC using the nvrtcAddNameExpression function:
    name_vec.push_back(getKernelNameForType<int>());
    ..
    name_vec.push_back(getKernelNameForType<double>());
    ..
    name_vec.push_back(getKernelNameForType<N1::S1_t>());
    ..
    for (size_t i = 0; i < name_vec.size(); ++i)
    NVRTC_SAFE_CALL(nvrtcAddNameExpression(prog, name_vec[i].c_str()));
    
    
    
  4. The GPU program is then compiled with nvrtcCompileProgram. The generated PTX is loaded on the GPU. The mangled names of the __global__ function template instantiations are looked up:
    // note: this call must be made after NVRTC program has been
    // compiled and before it has been destroyed.
    NVRTC_SAFE_CALL(nvrtcGetLoweredName(
    prog,
    name_vec[i].c_str(), // name expression
    &name // lowered name
    ));
    
    
  5. The mangled name is then used to launch the kernel using the CUDA Driver API:
    CUfunction kernel;
    CUDA_SAFE_CALL(cuModuleGetFunction(&kernel, module, name));
    ...
    CUDA_SAFE_CALL(
    cuLaunchKernel(kernel,
    1, 1, 1, // grid dim
    1, 1, 1, // block dim
    0, NULL, // shared mem and stream
    args, 0));    
      

A. Example: SAXPY

A.1. Code (saxpy.cpp)

#include <nvrtc.h>
#include <cuda.h>
#include <iostream>

#define NUM_THREADS 128
#define NUM_BLOCKS 32
#define NVRTC_SAFE_CALL(x)                                        \
  do {                                                            \
    nvrtcResult result = x;                                       \
    if (result != NVRTC_SUCCESS) {                                \
      std::cerr << "\nerror: " #x " failed with error "           \
                << nvrtcGetErrorString(result) << '\n';           \
      exit(1);                                                    \
    }                                                             \
  } while(0)
#define CUDA_SAFE_CALL(x)                                         \
  do {                                                            \
    CUresult result = x;                                          \
    if (result != CUDA_SUCCESS) {                                 \
      const char *msg;                                            \
      cuGetErrorName(result, &msg);                               \
      std::cerr << "\nerror: " #x " failed with error "           \
                << msg << '\n';                                   \
      exit(1);                                                    \
    }                                                             \
  } while(0)

const char *saxpy = "                                           \n\
extern \"C\" __global__                                         \n\
void saxpy(float a, float *x, float *y, float *out, size_t n)   \n\
{                                                               \n\
  size_t tid = blockIdx.x * blockDim.x + threadIdx.x;           \n\
  if (tid < n) {                                                \n\
    out[tid] = a * x[tid] + y[tid];                             \n\
  }                                                             \n\
}                                                               \n";

int main()
{
  // Create an instance of nvrtcProgram with the SAXPY code string.
  nvrtcProgram prog;

  NVRTC_SAFE_CALL(
    nvrtcCreateProgram(&prog,         // prog
                       saxpy,         // buffer
                       "saxpy.cu",    // name
                       0,             // numHeaders
                       NULL,          // headers
                       NULL));        // includeNames
  // Compile the program for compute_20 with fmad disabled.
  const char *opts[] = {"--gpu-architecture=compute_20",
                        "--fmad=false"};
  nvrtcResult compileResult = nvrtcCompileProgram(prog,  // prog
                                                  2,     // numOptions
                                                  opts); // options
  // Obtain compilation log from the program.
  size_t logSize;
  NVRTC_SAFE_CALL(nvrtcGetProgramLogSize(prog, &logSize));
  char *log = new char[logSize];
  NVRTC_SAFE_CALL(nvrtcGetProgramLog(prog, log));
  std::cout << log << '\n';
  delete[] log;
  if (compileResult != NVRTC_SUCCESS) {
    exit(1);
  }
  // Obtain PTX from the program.
  size_t ptxSize;
  NVRTC_SAFE_CALL(nvrtcGetPTXSize(prog, &ptxSize));
  char *ptx = new char[ptxSize];
  NVRTC_SAFE_CALL(nvrtcGetPTX(prog, ptx));
  // Destroy the program.
  NVRTC_SAFE_CALL(nvrtcDestroyProgram(&prog));
  // Load the generated PTX and get a handle to the SAXPY kernel.
  CUdevice cuDevice;
  CUcontext context;
  CUmodule module;
  CUfunction kernel;
  CUDA_SAFE_CALL(cuInit(0));
  CUDA_SAFE_CALL(cuDeviceGet(&cuDevice, 0));
  CUDA_SAFE_CALL(cuCtxCreate(&context, 0, cuDevice));
  CUDA_SAFE_CALL(cuModuleLoadDataEx(&module, ptx, 0, 0, 0));
  CUDA_SAFE_CALL(cuModuleGetFunction(&kernel, module, "saxpy"));
  // Generate input for execution, and create output buffers.
  size_t n = NUM_THREADS * NUM_BLOCKS;
  size_t bufferSize = n * sizeof(float);
  float a = 5.1f;
  float *hX = new float[n], *hY = new float[n], *hOut = new float[n];
  for (size_t i = 0; i < n; ++i) {
    hX[i] = static_cast<float>(i);
    hY[i] = static_cast<float>(i * 2);
  }
  CUdeviceptr dX, dY, dOut;
  CUDA_SAFE_CALL(cuMemAlloc(&dX, bufferSize));
  CUDA_SAFE_CALL(cuMemAlloc(&dY, bufferSize));
  CUDA_SAFE_CALL(cuMemAlloc(&dOut, bufferSize));
  CUDA_SAFE_CALL(cuMemcpyHtoD(dX, hX, bufferSize));
  CUDA_SAFE_CALL(cuMemcpyHtoD(dY, hY, bufferSize));
  // Execute SAXPY.
  void *args[] = { &a, &dX, &dY, &dOut, &n };
  CUDA_SAFE_CALL(
    cuLaunchKernel(kernel,
                   NUM_BLOCKS, 1, 1,    // grid dim
                   NUM_THREADS, 1, 1,   // block dim
                   0, NULL,             // shared mem and stream
                   args, 0));           // arguments
  CUDA_SAFE_CALL(cuCtxSynchronize());
  // Retrieve and print output.
  CUDA_SAFE_CALL(cuMemcpyDtoH(hOut, dOut, bufferSize));

  for (size_t i = 0; i < n; ++i) {
    std::cout << a << " * " << hX[i] << " + " << hY[i]
              << " = " << hOut[i] << '\n';
  }
  // Release resources.
  CUDA_SAFE_CALL(cuMemFree(dX));
  CUDA_SAFE_CALL(cuMemFree(dY));
  CUDA_SAFE_CALL(cuMemFree(dOut));
  CUDA_SAFE_CALL(cuModuleUnload(module));
  CUDA_SAFE_CALL(cuCtxDestroy(context));
  delete[] hX;
  delete[] hY;
  delete[] hOut;
  return 0;
}

A.2. Build Instruction

Assuming the environment variable CUDA_PATH points to CUDA Toolkit installation directory, build this example as:
  • Windows:
    cl.exe saxpy.cpp /Fesaxpy ^
      /I "%CUDA_PATH%"\include ^
      "%CUDA_PATH%"\lib\x64\nvrtc.lib "%CUDA_PATH%"\lib\x64\cuda.lib
  • Linux:
    g++ saxpy.cpp -o saxpy \
      -I $CUDA_PATH/include \
      -L $CUDA_PATH/lib64 \
      -lnvrtc -lcuda \
      -Wl,-rpath,$CUDA_PATH/lib64
  • Mac OS X:
    clang++ saxpy.cpp -o saxpy \
      -I $CUDA_PATH/include \
      -L $CUDA_PATH/lib \
      -lnvrtc -framework CUDA \
      -Wl,-rpath,$CUDA_PATH/lib

B. Example: Using Lowered Name

B.1. Code (lowered-name.cpp)

#include <nvrtc.h>
#include <cuda.h>
#include <iostream>
#include <vector>
#include <string>

#define NVRTC_SAFE_CALL(x)                                        \
  do {                                                            \
    nvrtcResult result = x;                                       \
    if (result != NVRTC_SUCCESS) {                                \
      std::cerr << "\nerror: " #x " failed with error "           \
                << nvrtcGetErrorString(result) << '\n';           \
      exit(1);                                                    \
    }                                                             \
  } while(0)
#define CUDA_SAFE_CALL(x)                                         \
  do {                                                            \
    CUresult result = x;                                          \
    if (result != CUDA_SUCCESS) {                                 \
      const char *msg;                                            \
      cuGetErrorName(result, &msg);                               \
      std::cerr << "\nerror: " #x " failed with error "           \
                << msg << '\n';                                   \
      exit(1);                                                    \
    }                                                             \
  } while(0)

const char *gpu_program = "                                     \n\
static __global__ void f1(int *result) { *result = 10; }        \n\
namespace N1 {                                                  \n\
  namespace N2 {                                                \n\
    __global__ void f2(int *result) { *result = 20; }           \n\
  }                                                             \n\
}                                                               \n\
template<typename T>                                            \n\
__global__ void f3(int *result) { *result = sizeof(T); }        \n\
                                                                \n";
int main()
{
  // Create an instance of nvrtcProgram
  nvrtcProgram prog;

  NVRTC_SAFE_CALL(nvrtcCreateProgram(&prog,         // prog
                                     gpu_program,   // buffer
                                     "prog.cu",     // name
                                     0,             // numHeaders
                                     NULL,          // headers
                                     NULL));        // includeNames

  // add all name expressions for kernels
  std::vector<std::string> name_vec;
  std::vector<int> expected_result;
  
  // note the name expressions are parsed as constant expressions
  name_vec.push_back("&f1");
  expected_result.push_back(10);
  
  name_vec.push_back("N1::N2::f2");
  expected_result.push_back(20);
    
  name_vec.push_back("f3<int>");
  expected_result.push_back(sizeof(int));
  
  name_vec.push_back("f3<double>");
  expected_result.push_back(sizeof(double));
  
  // add name expressions to NVRTC. Note this must be done before
  // the program is compiled.
  for (size_t i = 0; i < name_vec.size(); ++i)
    NVRTC_SAFE_CALL(nvrtcAddNameExpression(prog, name_vec[i].c_str()));
  
  nvrtcResult compileResult = nvrtcCompileProgram(prog,  // prog
                                                  0,     // numOptions
                                                  NULL); // options
  // Obtain compilation log from the program.
  size_t logSize;
  NVRTC_SAFE_CALL(nvrtcGetProgramLogSize(prog, &logSize));
  char *log = new char[logSize];
  NVRTC_SAFE_CALL(nvrtcGetProgramLog(prog, log));
  std::cout << log << '\n';
  delete[] log;
  if (compileResult != NVRTC_SUCCESS) {
    exit(1);
  }
  // Obtain PTX from the program.
  size_t ptxSize;
  NVRTC_SAFE_CALL(nvrtcGetPTXSize(prog, &ptxSize));
  char *ptx = new char[ptxSize];
  NVRTC_SAFE_CALL(nvrtcGetPTX(prog, ptx));

  // Load the generated PTX
  CUdevice cuDevice;
  CUcontext context;
  CUmodule module;
  
  CUDA_SAFE_CALL(cuInit(0));
  CUDA_SAFE_CALL(cuDeviceGet(&cuDevice, 0));
  CUDA_SAFE_CALL(cuCtxCreate(&context, 0, cuDevice));
  CUDA_SAFE_CALL(cuModuleLoadDataEx(&module, ptx, 0, 0, 0));
  
  CUdeviceptr dResult;
  int hResult = 0;
  CUDA_SAFE_CALL(cuMemAlloc(&dResult, sizeof(hResult)));
  CUDA_SAFE_CALL(cuMemcpyHtoD(dResult, &hResult, sizeof(hResult)));
  

  // for each of the name expressions previously provided to NVRTC,
  // extract the lowered name for corresponding __global__ function,
  // and launch it.
  
  for (size_t i = 0; i < name_vec.size(); ++i) {
    const char *name;
    
    // note: this call must be made after NVRTC program has been 
    // compiled and before it has been destroyed.
    NVRTC_SAFE_CALL(nvrtcGetLoweredName(
                          prog, 
			  name_vec[i].c_str(), // name expression
			  &name                // lowered name
                                        ));
    
    // get pointer to kernel from loaded PTX
    CUfunction kernel;
    CUDA_SAFE_CALL(cuModuleGetFunction(&kernel, module, name));
    
    // launch the kernel
    std::cout << "\nlaunching " << name << " ("
	      << name_vec[i] << ")" << std::endl;
    
    void *args[] = { &dResult };
    CUDA_SAFE_CALL(
      cuLaunchKernel(kernel,
		     1, 1, 1,             // grid dim
		     1, 1, 1,             // block dim
		     0, NULL,             // shared mem and stream
		     args, 0));           // arguments
    CUDA_SAFE_CALL(cuCtxSynchronize());
    
    // Retrieve the result
    CUDA_SAFE_CALL(cuMemcpyDtoH(&hResult, dResult, sizeof(hResult)));
    
    // check against expected value
    if (expected_result[i] != hResult) {
      std::cout << "\n Error: expected result = " << expected_result[i]
		<< " , actual result = " << hResult << std::endl;
      exit(1);
    }
  }  // for
    
  // Release resources.
  CUDA_SAFE_CALL(cuMemFree(dResult));
  CUDA_SAFE_CALL(cuModuleUnload(module));
  CUDA_SAFE_CALL(cuCtxDestroy(context));
  
  // Destroy the program. 
  NVRTC_SAFE_CALL(nvrtcDestroyProgram(&prog));

  return 0;
}

B.2. Build Instruction

Assuming the environment variable CUDA_PATH points to CUDA Toolkit installation directory, build this example as:
  • Windows:
    cl.exe lowered-name.cpp /Felowered-name ^
      /I "%CUDA_PATH%"\include ^
      "%CUDA_PATH%"\lib\x64\nvrtc.lib "%CUDA_PATH%"\lib\x64\cuda.lib
  • Linux:
    g++ lowered-name.cpp -o lowered-name \
      -I $CUDA_PATH/include \
      -L $CUDA_PATH/lib64 \
      -lnvrtc -lcuda \
      -Wl,-rpath,$CUDA_PATH/lib64
  • Mac OS X:
    clang++ lowered-name.cpp -o lowered-name \
      -I $CUDA_PATH/include \
      -L $CUDA_PATH/lib \
      -lnvrtc -framework CUDA \
      -Wl,-rpath,$CUDA_PATH/lib

C. Example: Using nvrtcGetTypeName

C.1. Code (host-type-name.cpp)

#include <nvrtc.h>
#include <cuda.h>
#include <iostream>
#include <vector>
#include <string>

#define NVRTC_SAFE_CALL(x)                                        \
  do {                                                            \
    nvrtcResult result = x;                                       \
    if (result != NVRTC_SUCCESS) {                                \
      std::cerr << "\nerror: " #x " failed with error "           \
                << nvrtcGetErrorString(result) << '\n';           \
      exit(1);                                                    \
    }                                                             \
  } while(0)
#define CUDA_SAFE_CALL(x)                                         \
  do {                                                            \
    CUresult result = x;                                          \
    if (result != CUDA_SUCCESS) {                                 \
      const char *msg;                                            \
      cuGetErrorName(result, &msg);                               \
      std::cerr << "\nerror: " #x " failed with error "           \
                << msg << '\n';                                   \
      exit(1);                                                    \
    }                                                             \
  } while(0)

const char *gpu_program = "                                     \n\
namespace N1 { struct S1_t { int i; double d; }; }              \n\
template<typename T>                                            \n\
__global__ void f3(int *result) { *result = sizeof(T); }        \n\
                                                                \n";


// note: this structure is also defined in GPU code string. Should ideally
// be in a header file included by both GPU code string and by CPU code.
namespace N1 { struct S1_t { int i; double d; }; };

template <typename T>
std::string getKernelNameForType(void)
{
   // Look up the source level name string for the type "T" using
   // nvrtcGetTypeName() and use it to create the kernel name 
   std::string type_name;
   NVRTC_SAFE_CALL(nvrtcGetTypeName<T>(&type_name));
   return std::string("f3<") + type_name + ">";
}

int main()
{
  // Create an instance of nvrtcProgram
  nvrtcProgram prog;
  NVRTC_SAFE_CALL(
    nvrtcCreateProgram(&prog,         // prog
                       gpu_program,   // buffer
                       "gpu_program.cu",    // name
                       0,             // numHeaders
                       NULL,          // headers
                       NULL));        // includeNames

  // add all name expressions for kernels
  std::vector<std::string> name_vec;
  std::vector<int> expected_result;
  
  // note the name expressions are parsed as constant expressions
  name_vec.push_back(getKernelNameForType<int>());
  expected_result.push_back(sizeof(int));
    
  name_vec.push_back(getKernelNameForType<double>());
  expected_result.push_back(sizeof(double));
  
  name_vec.push_back(getKernelNameForType<N1::S1_t>());
  expected_result.push_back(sizeof(N1::S1_t));
  
  
  // add name expressions to NVRTC. Note this must be done before
  // the program is compiled.
  for (size_t i = 0; i < name_vec.size(); ++i)
    NVRTC_SAFE_CALL(nvrtcAddNameExpression(prog, name_vec[i].c_str()));
  
  nvrtcResult compileResult = nvrtcCompileProgram(prog,  // prog
                                                  0,     // numOptions
                                                  NULL); // options
  // Obtain compilation log from the program.
  size_t logSize;
  NVRTC_SAFE_CALL(nvrtcGetProgramLogSize(prog, &logSize));
  char *log = new char[logSize];
  NVRTC_SAFE_CALL(nvrtcGetProgramLog(prog, log));
  std::cout << log << '\n';
  delete[] log;
  if (compileResult != NVRTC_SUCCESS) {
    exit(1);
  }
  // Obtain PTX from the program.
  size_t ptxSize;
  NVRTC_SAFE_CALL(nvrtcGetPTXSize(prog, &ptxSize));
  char *ptx = new char[ptxSize];
  NVRTC_SAFE_CALL(nvrtcGetPTX(prog, ptx));
  


  // Load the generated PTX
  CUdevice cuDevice;
  CUcontext context;
  CUmodule module;
  
  CUDA_SAFE_CALL(cuInit(0));
  CUDA_SAFE_CALL(cuDeviceGet(&cuDevice, 0));
  CUDA_SAFE_CALL(cuCtxCreate(&context, 0, cuDevice));
  CUDA_SAFE_CALL(cuModuleLoadDataEx(&module, ptx, 0, 0, 0));
  
  CUdeviceptr dResult;
  int hResult = 0;
  CUDA_SAFE_CALL(cuMemAlloc(&dResult, sizeof(hResult)));
  CUDA_SAFE_CALL(cuMemcpyHtoD(dResult, &hResult, sizeof(hResult)));
  
  // for each of the name expressions previously provided to NVRTC,
  // extract the lowered name for corresponding __global__ function,
  // and launch it.
  
  for (size_t i = 0; i < name_vec.size(); ++i) {
    const char *name;
    
    // note: this call must be made after NVRTC program has been 
    // compiled and before it has been destroyed.
    NVRTC_SAFE_CALL(nvrtcGetLoweredName(
                          prog, 
			  name_vec[i].c_str(), // name expression
			  &name                // lowered name
                                        ));
    
    // get pointer to kernel from loaded PTX
    CUfunction kernel;
    CUDA_SAFE_CALL(cuModuleGetFunction(&kernel, module, name));
    
    // launch the kernel
    std::cout << "\nlaunching " << name << " ("
	      << name_vec[i] << ")" << std::endl;
    
    void *args[] = { &dResult };
    CUDA_SAFE_CALL(
      cuLaunchKernel(kernel,
		     1, 1, 1,             // grid dim
		     1, 1, 1,             // block dim
		     0, NULL,             // shared mem and stream
		     args, 0));           // arguments
    CUDA_SAFE_CALL(cuCtxSynchronize());
    
    // Retrieve the result
    CUDA_SAFE_CALL(cuMemcpyDtoH(&hResult, dResult, sizeof(hResult)));
    
    // check against expected value
    if (expected_result[i] != hResult) {
      std::cout << "\n Error: expected result = " << expected_result[i]
		<< " , actual result = " << hResult << std::endl;
      exit(1);
    }
  }  // for
    
  // Release resources.
  CUDA_SAFE_CALL(cuMemFree(dResult));
  CUDA_SAFE_CALL(cuModuleUnload(module));
  CUDA_SAFE_CALL(cuCtxDestroy(context));
  
  // Destroy the program. 
  NVRTC_SAFE_CALL(nvrtcDestroyProgram(&prog));

  return 0;
}

C.2. Build Instruction

Assuming the environment variable CUDA_PATH points to CUDA Toolkit installation directory, build this example as:
  • Windows:
    cl.exe -DNVRTC_GET_TYPE_NAME=1 host-type-name.cpp /Fehost-type-name ^
      /I "%CUDA_PATH%"\include ^
      "%CUDA_PATH%"\lib\x64\nvrtc.lib "%CUDA_PATH%"\lib\x64\cuda.lib DbgHelp.lib
  • Linux:
    g++ -DNVRTC_GET_TYPE_NAME=1 host-type-name.cpp -o host-type-name \
      -I $CUDA_PATH/include \
      -L $CUDA_PATH/lib64 \
      -lnvrtc -lcuda \
      -Wl,-rpath,$CUDA_PATH/lib64
  • Mac OS X:
    clang++ -DNVRTC_GET_TYPE_NAME=1 host-type-name.cpp -o host-type-name \
      -I $CUDA_PATH/include \
      -L $CUDA_PATH/lib \
      -lnvrtc -framework CUDA \
      -Wl,-rpath,$CUDA_PATH/lib

D. Example: Dynamic Parallelism

D.1. Code (dynamic-parallelism.cpp)

#include <nvrtc.h>
#include <cuda.h>
#include <iostream>

#define NVRTC_SAFE_CALL(x)                                        \
  do {                                                            \
    nvrtcResult result = x;                                       \
    if (result != NVRTC_SUCCESS) {                                \
      std::cerr << "\nerror: " #x " failed with error "           \
                << nvrtcGetErrorString(result) << '\n';           \
      exit(1);                                                    \
    }                                                             \
  } while(0)
#define CUDA_SAFE_CALL(x)                                         \
  do {                                                            \
    CUresult result = x;                                          \
    if (result != CUDA_SUCCESS) {                                 \
      const char *msg;                                            \
      cuGetErrorName(result, &msg);                               \
      std::cerr << "\nerror: " #x " failed with error "           \
                << msg << '\n';                                   \
      exit(1);                                                    \
    }                                                             \
  } while(0)

const char *dynamic_parallelism = "                             \n\
extern \"C\" __global__                                         \n\
void child(float *out, size_t n)                                \n\
{                                                               \n\
  size_t tid = blockIdx.x * blockDim.x + threadIdx.x;           \n\
  if (tid < n) {                                                \n\
    out[tid] = tid;                                             \n\
  }                                                             \n\
}                                                               \n\
                                                                \n\
extern \"C\" __global__                                         \n\
void parent(float *out, size_t n,                               \n\
              size_t numBlocks, size_t numThreads)              \n\
{                                                               \n\
  child<<<numBlocks, numThreads>>>(out, n);                     \n\
  cudaDeviceSynchronize();                                      \n\
}                                                               \n";

int main(int argc, char *argv[])
{
  if (argc < 2) {
    std::cout << "Usage: dynamic-parallelism <path to cudadevrt library>\n\n"
              << "<path to cudadevrt library> must include the cudadevrt\n"
              << "library name itself, e.g., Z:\\path\\to\\cudadevrt.lib on \n"
              << "Windows and /path/to/libcudadevrt.a on Linux and Mac OS X.\n";
    exit(1);
  }
  size_t numBlocks = 32;
  size_t numThreads = 128;
  // Create an instance of nvrtcProgram with the code string.
  nvrtcProgram prog;
  NVRTC_SAFE_CALL(
    nvrtcCreateProgram(&prog,                       // prog
                       dynamic_parallelism,         // buffer
                       "dynamic_parallelism.cu",    // name
                       0,                           // numHeaders
                       NULL,                        // headers
                       NULL));                      // includeNames
  // Compile the program for compute_35 with rdc enabled.
  const char *opts[] = {"--gpu-architecture=compute_35",
                        "--relocatable-device-code=true"};
  nvrtcResult compileResult = nvrtcCompileProgram(prog,  // prog
                                                  2,     // numOptions
                                                  opts); // options
  // Obtain compilation log from the program.
  size_t logSize;
  NVRTC_SAFE_CALL(nvrtcGetProgramLogSize(prog, &logSize));
  char *log = new char[logSize];
  NVRTC_SAFE_CALL(nvrtcGetProgramLog(prog, log));
  std::cout << log << '\n';
  delete[] log;
  if (compileResult != NVRTC_SUCCESS) {
    exit(1);
  }
  // Obtain PTX from the program.
  size_t ptxSize;
  NVRTC_SAFE_CALL(nvrtcGetPTXSize(prog, &ptxSize));
  char *ptx = new char[ptxSize];
  NVRTC_SAFE_CALL(nvrtcGetPTX(prog, ptx));
  // Destroy the program.
  NVRTC_SAFE_CALL(nvrtcDestroyProgram(&prog));
  // Load the generated PTX and get a handle to the parent kernel.
  CUdevice cuDevice;
  CUcontext context;
  CUlinkState linkState;
  CUmodule module;
  CUfunction kernel;
  CUDA_SAFE_CALL(cuInit(0));
  CUDA_SAFE_CALL(cuDeviceGet(&cuDevice, 0));
  CUDA_SAFE_CALL(cuCtxCreate(&context, 0, cuDevice));
  CUDA_SAFE_CALL(cuLinkCreate(0, 0, 0, &linkState));
  CUDA_SAFE_CALL(cuLinkAddFile(linkState, CU_JIT_INPUT_LIBRARY, argv[1],
                               0, 0, 0));
  CUDA_SAFE_CALL(cuLinkAddData(linkState, CU_JIT_INPUT_PTX,
                               (void *)ptx, ptxSize, "dynamic_parallelism.ptx",
                               0, 0, 0));
  size_t cubinSize;
  void *cubin;
  CUDA_SAFE_CALL(cuLinkComplete(linkState, &cubin, &cubinSize));
  CUDA_SAFE_CALL(cuModuleLoadData(&module, cubin));
  CUDA_SAFE_CALL(cuModuleGetFunction(&kernel, module, "parent"));

  // Generate input for execution, and create output buffers.
  size_t n = numBlocks * numThreads;
  size_t bufferSize = n * sizeof(float);
  float *hOut = new float[n];
  CUdeviceptr dX, dY, dOut;
  CUDA_SAFE_CALL(cuMemAlloc(&dOut, bufferSize));
  // Execute parent kernel.
  void *args[] = { &dOut, &n, &numBlocks, &numThreads };
  CUDA_SAFE_CALL(
    cuLaunchKernel(kernel,
                   1, 1, 1,    // grid dim
                   1, 1, 1,    // block dim
                   0, NULL,    // shared mem and stream
                   args, 0));  // arguments
  CUDA_SAFE_CALL(cuCtxSynchronize());
  // Retrieve and print output.
  CUDA_SAFE_CALL(cuMemcpyDtoH(hOut, dOut, bufferSize));

  for (size_t i = 0; i < n; ++i) {
    std::cout << hOut[i] << '\n';
  }
  // Release resources.
  CUDA_SAFE_CALL(cuMemFree(dOut));
  CUDA_SAFE_CALL(cuModuleUnload(module));
  CUDA_SAFE_CALL(cuLinkDestroy(linkState));
  CUDA_SAFE_CALL(cuCtxDestroy(context));
  delete[] hOut;
  return 0;
}

D.2. Build Instruction

Assuming the environment variable CUDA_PATH points to CUDA Toolkit installation directory, build this example as:
  • Windows:
    cl.exe dynamic-parallelism.cpp /Fedynamic-parallelism ^
      /I "%CUDA_PATH%\include" ^
      "%CUDA_PATH%"\lib\x64\nvrtc.lib "%CUDA_PATH%"\lib\x64\cuda.lib
  • Linux:
    g++ dynamic-parallelism.cpp -o dynamic-parallelism \
      -I $CUDA_PATH/include \
      -L $CUDA_PATH/lib64 \
      -lnvrtc -lcuda \
      -Wl,-rpath,$CUDA_PATH/lib64
  • Mac OS X:
    clang++ dynamic-parallelism.cpp -o dynamic-parallelism \
      -I $CUDA_PATH/include \
      -L $CUDA_PATH/lib \
      -lnvrtc -framework CUDA \
      -Wl,-rpath,$CUDA_PATH/lib

Notices

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