NVRTC CUDA Runtime Compilation User Guide

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NVRTC - CUDA RUNTIME
COMPILATION
DU-07529-001 _v8.0 | February 2016
User Guide
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TABLE OF CONTENTS
Chapter 1. Introduction......................................................................................... 1
Chapter2.Getting Started.....................................................................................2
2.1.System Requirements.................................................................................... 2
2.2. Installation................................................................................................. 2
Chapter3.User Interface...................................................................................... 4
3.1. Error Handling.............................................................................................4
nvrtcResult.................................................................................................... 4
nvrtcGetErrorString.......................................................................................... 5
3.2.General Information Query..............................................................................5
nvrtcVersion...................................................................................................5
3.3. Compilation................................................................................................ 5
nvrtcProgram................................................................................................. 6
nvrtcAddNameExpression................................................................................... 6
nvrtcCompileProgram........................................................................................6
nvrtcCreateProgram......................................................................................... 7
nvrtcDestroyProgram........................................................................................ 8
nvrtcGetLoweredName......................................................................................8
nvrtcGetProgramLog......................................................................................... 9
nvrtcGetProgramLogSize.................................................................................... 9
nvrtcGetPTX................................................................................................. 10
nvrtcGetPTXSize............................................................................................ 11
3.4.Supported Compile Options............................................................................11
3.5. Host Helper...............................................................................................14
nvrtcGetTypeName......................................................................................... 15
Chapter 4. Language........................................................................................... 16
4.1.Execution Space......................................................................................... 16
4.2.Separate Compilation...................................................................................16
4.3.Dynamic Parallelism.....................................................................................16
4.4. Integer Size...............................................................................................17
4.5.Predefined Macros.......................................................................................17
4.6.Predefined Types........................................................................................ 17
4.7.Builtin Functions.........................................................................................18
Chapter5. Basic Usage........................................................................................ 19
Chapter6.Accessing Lowered Names..................................................................... 22
6.1. Introduction.............................................................................................. 22
6.2. Example................................................................................................... 22
6.3. Notes...................................................................................................... 23
Chapter7.Interfacing With Template Host Code........................................................25
7.1. Introduction.............................................................................................. 25
7.2. Example................................................................................................... 25
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AppendixA. Example: SAXPY................................................................................ 27
A.1.Code (saxpy.cpp)........................................................................................ 27
A.2.Build Instruction.........................................................................................29
AppendixB.Example: Using Lowered Name............................................................. 30
B.1.Code (lowered-name.cpp)............................................................................. 30
B.2.Build Instruction......................................................................................... 32
AppendixC.Example: Using nvrtcGetTypeName........................................................ 34
C.1.Code (host-type-name.cpp)........................................................................... 34
C.2.Build Instruction.........................................................................................37
AppendixD.Example: Dynamic Parallelism...............................................................38
D.1.Code (dynamic-parallelism.cpp)...................................................................... 38
D.2.Build Instruction.........................................................................................40
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LIST OF FIGURES
Figure1 CUDA source string for SAXPY ..................................................................... 19
Figure2 nvrtcProgram creation for SAXPY ................................................................. 19
Figure3 Compilation of SAXPY for compute_20 with FMAD enabled .................................. 20
Figure4 Obtaining generated PTX and program compilation log .......................................20
Figure5 Destruction of nvrtcProgram .......................................................................20
Figure6 Execution of SAXPY using the PTX generated by NVRTC ...................................... 21
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LIST OF TABLES
Table1 Integer sizes in bits for LLP64 and LP64 ..........................................................17
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Chapter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.
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Chapter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
Getting Started
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‣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
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Chapter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.
‣Error Handling
‣General Information Query
‣Compilation
‣Supported Compile Options
‣Host Helper
3.1.Error Handling
NVRTC defines the following enumeration type and function for API call error
handling.
enum nvrtcResult
The enumerated type nvrtcResult defines API call result codes. NVRTC API functions
return nvrtcResult to indicate the call result.
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
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NVRTC_ERROR_NAME_EXPRESSION_NOT_VALID = 10
NVRTC_ERROR_INTERNAL_ERROR = 11
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.
3.2.General Information Query
NVRTC defines the following function for general information query.
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.
Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_INVALID_INPUT
3.3.Compilation
NVRTC defines the following type and functions for actual compilation.
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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.
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.
Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_NO_NAME_EXPRESSIONS_AFTER_COMPILATION
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.
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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.
Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_OUT_OF_MEMORY
‣NVRTC_ERROR_PROGRAM_CREATION_FAILURE
‣NVRTC_ERROR_INVALID_INPUT
‣NVRTC_ERROR_INVALID_PROGRAM
Description
See also:
nvrtcDestroyProgram
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nvrtcResult nvrtcDestroyProgram (nvrtcProgram *prog)
nvrtcDestroyProgram destroys the given program.
Parameters
prog
CUDA Runtime Compilation program.
Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_INVALID_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.
Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_NO_LOWERED_NAMES_BEFORE_COMPILATION
‣NVRTC_ERROR_NAME_EXPRESSION_NOT_VALID
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Description
See also:
nvrtcAddNameExpression
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.
Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_INVALID_INPUT
‣NVRTC_ERROR_INVALID_PROGRAM
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).
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Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_INVALID_INPUT
‣NVRTC_ERROR_INVALID_PROGRAM
Description
Note that compilation log may be generated with warnings and informative messages,
even when the compilation of prog succeeds.
See also:
nvrtcGetProgramLog
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.
Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_INVALID_INPUT
‣NVRTC_ERROR_INVALID_PROGRAM
Description
See also:
nvrtcGetPTXSize
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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).
Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_INVALID_INPUT
‣NVRTC_ERROR_INVALID_PROGRAM
Description
See also:
nvrtcGetPTX
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)
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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.
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‣--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)
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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.
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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.
Parameters
result
pointer to std::string in which to store the type name.
Returns
‣NVRTC_SUCCESS
‣NVRTC_ERROR_INTERNAL_ERROR
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.
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Chapter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:
‣Compilation target must be compute 35 or higher.
‣Separate compilation must be enabled with the --relocatable-device-
code=true or --device-c compile option.
‣Generated PTX must be linked against the CUDA device runtime (cudadevrt)
library (see Separate Compilation).
Language
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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 long long 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.
Language
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4.7.Builtin Functions
Builtin functions provided by the CUDA Runtime headers when compiling offline with
nvcc are available, unless otherwise noted.
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Chapter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.
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";
Figure1 CUDA source string for SAXPY
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.
nvrtcProgram prog;
nvrtcCreateProgram(&prog, // prog
saxpy, // buffer
"saxpy.cu", // name
0, // numHeaders
NULL, // headers
NULL); // includeNames
Figure2 nvrtcProgram creation for SAXPY
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
Basic Usage
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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.
const char *opts[] = {"--gpu-architecture=compute_20",
"--fmad=false"};
nvrtcCompileProgram(prog, // prog
2, // numOptions
opts); // options
Figure3 Compilation of SAXPY for compute_20 with FMAD enabled
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.
// 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);
Figure4 Obtaining generated PTX and program compilation log
When the instance of nvrtcProgram is no longer needed, it can be destroyed by
nvrtcDestroyProgram as shown in Figure 5.
nvrtcDestroyProgram(&prog);
Figure5 Destruction of nvrtcProgram
Basic Usage
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|21
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.
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);
Figure6 Execution of SAXPY using the PTX generated by NVRTC
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|22
Chapter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:
Accessing Lowered Names
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|23
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
Accessing Lowered Names
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|24
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.
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|25
Chapter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";
Interfacing With Template Host Code
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|26
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));
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|27
Appendix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;
Example: SAXPY
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|28
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));
Example: SAXPY
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|29
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
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|30
Appendix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;
Example: Using Lowered Name
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|31
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)));
Example: Using Lowered Name
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|32
// 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:
Example: Using Lowered Name
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|33
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
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|34
Appendix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; }; };
Example: Using nvrtcGetTypeName
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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));
Example: Using nvrtcGetTypeName
www.nvidia.com
NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|36
// 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;
}
Example: Using nvrtcGetTypeName
www.nvidia.com
NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|37
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
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NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|38
Appendix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";
Example: Dynamic Parallelism
www.nvidia.com
NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|39
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"));
Example: Dynamic Parallelism
www.nvidia.com
NVRTC - CUDA Runtime Compilation DU-07529-001 _v8.0|40
// 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
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