Updating graphConditionalNodes orphan directory

This commit is contained in:
Rob Nertney 2024-04-10 19:44:42 +00:00
parent 3559ca4d08
commit 5f97d7d0df
14 changed files with 1300 additions and 0 deletions

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{
"configurations": [
{
"name": "Linux",
"includePath": [
"${workspaceFolder}/**",
"${workspaceFolder}/../../../Common"
],
"defines": [],
"compilerPath": "/usr/local/cuda/bin/nvcc",
"cStandard": "gnu17",
"cppStandard": "gnu++14",
"intelliSenseMode": "linux-gcc-x64",
"configurationProvider": "ms-vscode.makefile-tools"
}
],
"version": 4
}

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{
"recommendations": [
"nvidia.nsight-vscode-edition",
"ms-vscode.cpptools",
"ms-vscode.makefile-tools"
]
}

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{
"configurations": [
{
"name": "CUDA C++: Launch",
"type": "cuda-gdb",
"request": "launch",
"program": "${workspaceFolder}/graphConditionalNodes"
}
]
}

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{
"version": "2.0.0",
"tasks": [
{
"label": "sample",
"type": "shell",
"command": "make dbg=1",
"problemMatcher": ["$nvcc"],
"group": {
"kind": "build",
"isDefault": true
}
}
]
}

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################################################################################
# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
################################################################################
#
# Makefile project only supported on Mac OS X and Linux Platforms)
#
################################################################################
# Location of the CUDA Toolkit
CUDA_PATH ?= /usr/local/cuda
##############################
# start deprecated interface #
##############################
ifeq ($(x86_64),1)
$(info WARNING - x86_64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=x86_64 instead)
TARGET_ARCH ?= x86_64
endif
ifeq ($(ARMv7),1)
$(info WARNING - ARMv7 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=armv7l instead)
TARGET_ARCH ?= armv7l
endif
ifeq ($(aarch64),1)
$(info WARNING - aarch64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=aarch64 instead)
TARGET_ARCH ?= aarch64
endif
ifeq ($(ppc64le),1)
$(info WARNING - ppc64le variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=ppc64le instead)
TARGET_ARCH ?= ppc64le
endif
ifneq ($(GCC),)
$(info WARNING - GCC variable has been deprecated)
$(info WARNING - please use HOST_COMPILER=$(GCC) instead)
HOST_COMPILER ?= $(GCC)
endif
ifneq ($(abi),)
$(error ERROR - abi variable has been removed)
endif
############################
# end deprecated interface #
############################
# architecture
HOST_ARCH := $(shell uname -m)
TARGET_ARCH ?= $(HOST_ARCH)
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
# sbsa and aarch64 systems look similar. Need to differentiate them at host level for now.
ifeq ($(HOST_ARCH),aarch64)
ifeq ($(CUDA_PATH)/targets/sbsa-linux,$(shell ls -1d $(CUDA_PATH)/targets/sbsa-linux 2>/dev/null))
HOST_ARCH := sbsa
TARGET_ARCH := sbsa
endif
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-sbsa x86_64-ppc64le))
$(error ERROR - cross compiling from $(HOST_ARCH) to $(TARGET_ARCH) is not supported!)
endif
endif
# When on native aarch64 system with userspace of 32-bit, change TARGET_ARCH to armv7l
ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_SIZE),aarch64-aarch64-32)
TARGET_ARCH = armv7l
endif
# operating system
HOST_OS := $(shell uname -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
TARGET_OS ?= $(HOST_OS)
ifeq (,$(filter $(TARGET_OS),linux darwin qnx android))
$(error ERROR - unsupported value $(TARGET_OS) for TARGET_OS!)
endif
# host compiler
ifdef HOST_COMPILER
CUSTOM_HOST_COMPILER = 1
endif
ifeq ($(TARGET_OS),darwin)
ifeq ($(shell expr `xcodebuild -version | grep -i xcode | awk '{print $$2}' | cut -d'.' -f1` \>= 5),1)
HOST_COMPILER ?= clang++
endif
else ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
ifeq ($(TARGET_OS),linux)
HOST_COMPILER ?= arm-linux-gnueabihf-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/arm-unknown-nto-qnx6.6.0eabi-g++
else ifeq ($(TARGET_OS),android)
HOST_COMPILER ?= arm-linux-androideabi-g++
endif
else ifeq ($(TARGET_ARCH),aarch64)
ifeq ($(TARGET_OS), linux)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/q++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
else ifeq ($(TARGET_ARCH),sbsa)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_ARCH),ppc64le)
HOST_COMPILER ?= powerpc64le-linux-gnu-g++
endif
endif
HOST_COMPILER ?= g++
NVCC := $(CUDA_PATH)/bin/nvcc -ccbin $(HOST_COMPILER)
# internal flags
NVCCFLAGS := -m${TARGET_SIZE}
CCFLAGS :=
LDFLAGS :=
# build flags
ifeq ($(TARGET_OS),darwin)
LDFLAGS += -rpath $(CUDA_PATH)/lib
CCFLAGS += -arch $(HOST_ARCH)
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
LDFLAGS += --dynamic-linker=/lib/ld-linux-armhf.so.3
CCFLAGS += -mfloat-abi=hard
else ifeq ($(TARGET_OS),android)
LDFLAGS += -pie
CCFLAGS += -fpie -fpic -fexceptions
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib -L$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/lib/aarch64-linux-gnu -L$(TARGET_FS)/lib/aarch64-linux-gnu
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib -L$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/aarch64-linux-gnu -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
LDFLAGS += --unresolved-symbols=ignore-in-shared-libs
CCFLAGS += -isystem=$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include/libdrm
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu -I$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
NVCCFLAGS += -D_QNX_SOURCE
NVCCFLAGS += --qpp-config 8.3.0,gcc_ntoaarch64le
CCFLAGS += -DWIN_INTERFACE_CUSTOM -I/usr/include/aarch64-qnx-gnu
LDFLAGS += -lsocket
LDFLAGS += -L/usr/lib/aarch64-qnx-gnu
CCFLAGS += "-Wl\,-rpath-link\,/usr/lib/aarch64-qnx-gnu"
ifdef TARGET_OVERRIDE
LDFLAGS += -lslog2
endif
ifneq ($(TARGET_FS),)
LDFLAGS += -L$(TARGET_FS)/usr/lib
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/lib"
LDFLAGS += -L$(TARGET_FS)/usr/libnvidia
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/libnvidia"
CCFLAGS += -I$(TARGET_FS)/../include
endif
endif
endif
ifdef TARGET_OVERRIDE # cuda toolkit targets override
NVCCFLAGS += -target-dir $(TARGET_OVERRIDE)
endif
# Install directory of different arch
CUDA_INSTALL_TARGET_DIR :=
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-gnueabihf/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),sbsa-linux)
CUDA_INSTALL_TARGET_DIR = targets/sbsa-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-android)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-android)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-qnx)
CUDA_INSTALL_TARGET_DIR = targets/ARMv7-linux-QNX/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-qnx/
else ifeq ($(TARGET_ARCH),ppc64le)
CUDA_INSTALL_TARGET_DIR = targets/ppc64le-linux/
endif
# Debug build flags
ifeq ($(dbg),1)
NVCCFLAGS += -g -G
BUILD_TYPE := debug
else
BUILD_TYPE := release
endif
ALL_CCFLAGS :=
ALL_CCFLAGS += $(NVCCFLAGS)
ALL_CCFLAGS += $(EXTRA_NVCCFLAGS)
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(CCFLAGS))
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
SAMPLE_ENABLED := 1
# This sample is not supported on Mac OSX
ifeq ($(TARGET_OS),darwin)
$(info >>> WARNING - graphConditionalNodes is not supported on Mac OSX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
# Common includes and paths for CUDA
INCLUDES := -I../../../Common
LIBRARIES :=
################################################################################
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64 sbsa))
SMS ?= 53 61 70 72 75 80 86 87 90
else
SMS ?= 50 52 60 61 70 75 80 86 89 90
endif
ifeq ($(SMS),)
$(info >>> WARNING - no SM architectures have been specified - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ifeq ($(GENCODE_FLAGS),)
# Generate SASS code for each SM architecture listed in $(SMS)
$(foreach sm,$(SMS),$(eval GENCODE_FLAGS += -gencode arch=compute_$(sm),code=sm_$(sm)))
# Generate PTX code from the highest SM architecture in $(SMS) to guarantee forward-compatibility
HIGHEST_SM := $(lastword $(sort $(SMS)))
ifneq ($(HIGHEST_SM),)
GENCODE_FLAGS += -gencode arch=compute_$(HIGHEST_SM),code=compute_$(HIGHEST_SM)
endif
endif
ALL_CCFLAGS += --threads 0 --std=c++11
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: graphConditionalNodes
check.deps:
ifeq ($(SAMPLE_ENABLED),0)
@echo "Sample will be waived due to the above missing dependencies"
else
@echo "Sample is ready - all dependencies have been met"
endif
graphConditionalNodes.o:graphConditionalNodes.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
graphConditionalNodes: graphConditionalNodes.o
$(EXEC) $(NVCC) $(ALL_LDFLAGS) $(GENCODE_FLAGS) -o $@ $+ $(LIBRARIES)
$(EXEC) mkdir -p ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
$(EXEC) cp $@ ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)
run: build
$(EXEC) ./graphConditionalNodes
testrun: build
clean:
rm -f graphConditionalNodes graphConditionalNodes.o
rm -rf ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/graphConditionalNodes
clobber: clean

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>graphConditionalNodes</name>
<cuda_api_list>
<toolkit>cudaDeviceSynchronize</toolkit>
<toolkit>cudaDriverGetVersion</toolkit>
<toolkit>cudaFree</toolkit>
<toolkit>cudaGraphAddNode</toolkit>
<toolkit>cudaGraphConditionalHandleCreate</toolkit>
<toolkit>cudaGraphCreate</toolkit>
<toolkit>cudaGraphDestroy</toolkit>
<toolkit>cudaGraphExecDestroy</toolkit>
<toolkit>cudaGraphInstantiate</toolkit>
<toolkit>cudaGraphLaunch</toolkit>
<toolkit>cudaGraphSetConditional</toolkit>
<toolkit>cudaMalloc</toolkit>
<toolkit>cudaMemset</toolkit>
<toolkit>cudaStreamBeginCapture</toolkit>
<toolkit>cudaStreamBeginCaptureToGraph</toolkit>
<toolkit>cudaStreamCreate</toolkit>
<toolkit>cudaStreamDestroy</toolkit>
<toolkit>cudaStreamEndCapture</toolkit>
<toolkit>cudaStreamGetCaptureInfo</toolkit>
</cuda_api_list>
<description><![CDATA[A demonstration of CUDA graphs conditional nodes.]]></description>
<devicecompilation>whole</devicecompilation>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../../Common</path>
</includepaths>
<keyconcepts>
<concept level="basic">CUDA Graphs</concept>
</keyconcepts>
<keywords>
<keyword>CUDA</keyword>
<keyword>CUDA Graphs</keyword>
<keyword>Streams</keyword>
<keyword>GPGPU</keyword>
<keyword>Graph Conditional Nodes</keyword>
</keywords>
<libraries>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>graphConditionalNodes.cu</primary_file>
<scopes>
<scope>1:CUDA Basic Topics</scope>
</scopes>
<sm-arch>sm60</sm-arch>
<sm-arch>sm61</sm-arch>
<sm-arch>sm70</sm-arch>
<sm-arch>sm72</sm-arch>
<sm-arch>sm75</sm-arch>
<sm-arch>sm80</sm-arch>
<sm-arch>sm86</sm-arch>
<sm-arch>sm87</sm-arch>
<sm-arch>sm89</sm-arch>
<sm-arch>sm90</sm-arch>
<supported_envs>
<env>
<arch>x86_64</arch>
<platform>linux</platform>
</env>
<env>
<platform>windows7</platform>
</env>
<env>
<arch>arm</arch>
</env>
<env>
<arch>sbsa</arch>
</env>
<env>
<arch>ppc64le</arch>
<platform>linux</platform>
</env>
</supported_envs>
<supported_sm_architectures>
<from>6.0</from>
</supported_sm_architectures>
<title>Graph Conditional Nodes</title>
<type>exe</type>
</entry>

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# graphConditionalNodes - Graph Conditional Nodes
## Description
A demonstration of CUDA graphs conditional nodes.
## Key Concepts
CUDA Graphs
## Supported SM Architectures
[SM 6.0 ](https://developer.nvidia.com/cuda-gpus) [SM 6.1 ](https://developer.nvidia.com/cuda-gpus) [SM 7.0 ](https://developer.nvidia.com/cuda-gpus) [SM 7.2 ](https://developer.nvidia.com/cuda-gpus) [SM 7.5 ](https://developer.nvidia.com/cuda-gpus) [SM 8.0 ](https://developer.nvidia.com/cuda-gpus) [SM 8.6 ](https://developer.nvidia.com/cuda-gpus) [SM 8.7 ](https://developer.nvidia.com/cuda-gpus) [SM 8.9 ](https://developer.nvidia.com/cuda-gpus) [SM 9.0 ](https://developer.nvidia.com/cuda-gpus)
## Supported OSes
Linux, Windows
## Supported CPU Architecture
x86_64, ppc64le, armv7l
## CUDA APIs involved
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaDeviceSynchronize, cudaDriverGetVersion, cudaFree, cudaGraphAddNode, cudaGraphConditionalHandleCreate, cudaGraphCreate, cudaGraphDestroy, cudaGraphExecDestroy, cudaGraphInstantiate, cudaGraphLaunch, cudaGraphSetConditional, cudaMalloc, cudaMemset, cudaStreamBeginCapture, cudaStreamBeginCaptureToGraph, cudaStreamCreate, cudaStreamDestroy, cudaStreamEndCapture, cudaStreamGetCaptureInfo
## Prerequisites
Download and install the [CUDA Toolkit 12.4](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
## Build and Run
### Windows
The Windows samples are built using the Visual Studio IDE. Solution files (.sln) are provided for each supported version of Visual Studio, using the format:
```
*_vs<version>.sln - for Visual Studio <version>
```
Each individual sample has its own set of solution files in its directory:
To build/examine all the samples at once, the complete solution files should be used. To build/examine a single sample, the individual sample solution files should be used.
> **Note:** Some samples require that the Microsoft DirectX SDK (June 2010 or newer) be installed and that the VC++ directory paths are properly set up (**Tools > Options...**). Check DirectX Dependencies section for details."
### Linux
The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
```
$ cd <sample_dir>
$ make
```
The samples makefiles can take advantage of certain options:
* **TARGET_ARCH=<arch>** - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, armv7l.
By default, TARGET_ARCH is set to HOST_ARCH. On a x86_64 machine, not setting TARGET_ARCH is the equivalent of setting TARGET_ARCH=x86_64.<br/>
`$ make TARGET_ARCH=x86_64` <br/> `$ make TARGET_ARCH=ppc64le` <br/> `$ make TARGET_ARCH=armv7l` <br/>
See [here](http://docs.nvidia.com/cuda/cuda-samples/index.html#cross-samples) for more details.
* **dbg=1** - build with debug symbols
```
$ make dbg=1
```
* **SMS="A B ..."** - override the SM architectures for which the sample will be built, where `"A B ..."` is a space-delimited list of SM architectures. For example, to generate SASS for SM 50 and SM 60, use `SMS="50 60"`.
```
$ make SMS="50 60"
```
* **HOST_COMPILER=<host_compiler>** - override the default g++ host compiler. See the [Linux Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html#system-requirements) for a list of supported host compilers.
```
$ make HOST_COMPILER=g++
```
## References (for more details)

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/* Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above copyright
* notice, this list of conditions and the following disclaimer in the
* documentation and/or other materials provided with the distribution.
* * Neither the name of NVIDIA CORPORATION nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
/*
* This file demonstrates the usage of conditional graph nodes with
* a series of *simple* example graphs.
*
* For more information on conditional nodes, see the programming guide:
*
* https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#conditional-graph-nodes
*
*/
// System includes
#include <cassert>
#include <cstdio>
// CUDA runtime
#include <cuda_runtime.h>
// helper functions and utilities to work with CUDA
#include <helper_cuda.h>
#include <helper_functions.h>
/*
* Create a graph containing two nodes.
* The first node, A, is a kernel and the second node, B, is a conditional IF node.
* The kernel sets the condition variable to true if a device memory location
* contains an odd number. Otherwise the condition variable is set to false.
* There is a single kernel, C, within the conditional body which prints a message.
*
* A -> B [ C ]
*
*/
__global__ void ifGraphKernelA(char *dPtr, cudaGraphConditionalHandle handle)
{
// In this example, condition is set if *dPtr is odd
unsigned int value = *dPtr & 0x01;
cudaGraphSetConditional(handle, value);
printf("GPU: Handle set to %d\n", value);
}
// This kernel will only be executed if the condition is true
__global__ void ifGraphKernelC(void)
{
printf("GPU: Hello from the GPU!\n");
}
// Setup and launch the graph
void simpleIfGraph(void)
{
cudaGraph_t graph;
cudaGraphExec_t graphExec;
cudaGraphNode_t node;
void *kernelArgs[2];
// Allocate a byte of device memory to use as input
char *dPtr;
checkCudaErrors(cudaMalloc((void**)&dPtr, 1));
printf("simpleIfGraph: Building graph...\n");
cudaGraphCreate(&graph, 0);
// Create conditional handle.
cudaGraphConditionalHandle handle;
cudaGraphConditionalHandleCreate(&handle, graph);
// Use a kernel upstream of the conditional to set the handle value
cudaGraphNodeParams params = { cudaGraphNodeTypeKernel };
params.kernel.func = (void *)ifGraphKernelA;
params.kernel.gridDim.x = params.kernel.gridDim.y = params.kernel.gridDim.z = 1;
params.kernel.blockDim.x = params.kernel.blockDim.y = params.kernel.blockDim.z = 1;
params.kernel.kernelParams = kernelArgs;
kernelArgs[0] = &dPtr;
kernelArgs[1] = &handle;
checkCudaErrors(cudaGraphAddNode(&node, graph, NULL, 0, &params));
cudaGraphNodeParams cParams = { cudaGraphNodeTypeConditional };
cParams.conditional.handle = handle;
cParams.conditional.type = cudaGraphCondTypeIf;
cParams.conditional.size = 1;
checkCudaErrors(cudaGraphAddNode(&node, graph, &node, 1, &cParams));
cudaGraph_t bodyGraph = cParams.conditional.phGraph_out[0];
// Populate the body of the conditional node
cudaGraphNode_t bodyNode;
params.kernel.func = (void *)ifGraphKernelC;
params.kernel.kernelParams = nullptr;
checkCudaErrors(cudaGraphAddNode(&bodyNode, bodyGraph, NULL, 0, &params));
checkCudaErrors(cudaGraphInstantiate(&graphExec, graph, NULL, NULL, 0));
// Initialize device memory and launch the graph
checkCudaErrors(cudaMemset(dPtr, 0, 1)); // Set dPtr to 0
printf("Host: Launching graph with conditional value set to false\n");
checkCudaErrors(cudaGraphLaunch(graphExec, 0));
checkCudaErrors(cudaDeviceSynchronize());
// Initialize device memory and launch the graph
checkCudaErrors(cudaMemset(dPtr, 1, 1)); // Set dPtr to 1
printf("Host: Launching graph with conditional value set to true\n");
checkCudaErrors(cudaGraphLaunch(graphExec, 0));
checkCudaErrors(cudaDeviceSynchronize());
// Cleanup
checkCudaErrors(cudaGraphExecDestroy(graphExec));
checkCudaErrors(cudaGraphDestroy(graph));
checkCudaErrors(cudaFree(dPtr));
printf("simpleIfGraph: Complete\n\n");
}
/*
* Create a graph containing a single conditional while node.
* The default value of the conditional variable is set to true, so this
* effectively becomes a do-while loop as the conditional body will always
* execute at least once. The body of the conditional contains 3 kernel nodes:
* A [ B -> C -> D ]
* Nodes B and C are just dummy nodes for demonstrative purposes. Node D
* will decrement a device memory location and set the condition value to false
* when the value reaches zero, terminating the loop.
* In this example, stream capture is used to populate the conditional body.
*/
// This kernel will only be executed if the condition is true
__global__ void doWhileEmptyKernel(void)
{
printf("GPU: doWhileEmptyKernel()\n");
return;
}
__global__ void doWhileLoopKernel(char *dPtr, cudaGraphConditionalHandle handle)
{
if (--(*dPtr) == 0) {
cudaGraphSetConditional(handle, 0);
}
printf("GPU: counter = %d\n", *dPtr);
}
void simpleDoWhileGraph(void)
{
cudaGraph_t graph;
cudaGraphExec_t graphExec;
cudaGraphNode_t node;
// Allocate a byte of device memory to use as input
char *dPtr;
checkCudaErrors(cudaMalloc((void**)&dPtr, 1));
printf("simpleDoWhileGraph: Building graph...\n");
checkCudaErrors(cudaGraphCreate(&graph, 0));
cudaGraphConditionalHandle handle;
checkCudaErrors(cudaGraphConditionalHandleCreate(&handle, graph, 1, cudaGraphCondAssignDefault));
cudaGraphNodeParams cParams = { cudaGraphNodeTypeConditional };
cParams.conditional.handle = handle;
cParams.conditional.type = cudaGraphCondTypeWhile;
cParams.conditional.size = 1;
checkCudaErrors(cudaGraphAddNode(&node, graph, NULL, 0, &cParams));
cudaGraph_t bodyGraph = cParams.conditional.phGraph_out[0];
cudaStream_t captureStream;
checkCudaErrors(cudaStreamCreate(&captureStream));
checkCudaErrors(cudaStreamBeginCaptureToGraph(captureStream, bodyGraph, nullptr, nullptr, 0, cudaStreamCaptureModeRelaxed));
doWhileEmptyKernel<<<1, 1, 0, captureStream>>>();
doWhileEmptyKernel<<<1, 1, 0, captureStream>>>();
doWhileLoopKernel<<<1, 1, 0, captureStream>>>(dPtr, handle);
checkCudaErrors(cudaStreamEndCapture(captureStream, nullptr));
checkCudaErrors(cudaStreamDestroy(captureStream));
checkCudaErrors(cudaGraphInstantiate(&graphExec, graph, NULL, NULL, 0));
// Initialize device memory and launch the graph
checkCudaErrors(cudaMemset(dPtr, 10, 1)); // Set dPtr to 10
printf("Host: Launching graph with loop counter set to 10\n");
checkCudaErrors(cudaGraphLaunch(graphExec, 0));
checkCudaErrors(cudaDeviceSynchronize());
// Cleanup
checkCudaErrors(cudaGraphExecDestroy(graphExec));
checkCudaErrors(cudaGraphDestroy(graph));
checkCudaErrors(cudaFree(dPtr));
printf("simpleDoWhileGraph: Complete\n\n");
}
/*
* Create a graph containing a conditional while loop using stream capture.
* This demonstrates how to insert a conditional node into a stream which is
* being captured. The graph consists of a kernel node followed by a conditional
* while node which contains a single kernel node:
*
* A -> B [ C ]
*
* The same kernel will be used for both nodes A and C. This kernel will test
* a device memory location and set the condition when the location is non-zero.
* We must run the kernel before the loop as well as inside the loop in order
* to behave like a while loop. We need to evaluate the device memory location
* before the conditional node is evaluated in order to set the condition variable
* properly. Because we're using a kernel upstream of the conditional node,
* there is no need to use the handle default value to initialize the conditional
* value.
*/
__global__ void capturedWhileKernel(char *dPtr, cudaGraphConditionalHandle handle)
{
printf("GPU: counter = %d\n", *dPtr);
if (*dPtr) {
(*dPtr)--;
}
cudaGraphSetConditional(handle, *dPtr);
}
__global__ void capturedWhileEmptyKernel(void)
{
printf("GPU: capturedWhileEmptyKernel()\n");
return;
}
void capturedWhileGraph(void)
{
cudaGraph_t graph;
cudaGraphExec_t graphExec;
cudaStreamCaptureStatus status;
const cudaGraphNode_t *dependencies;
size_t numDependencies;
// Allocate a byte of device memory to use as input
char *dPtr;
checkCudaErrors(cudaMalloc((void**)&dPtr, 1));
printf("capturedWhileGraph: Building graph...\n");
cudaStream_t captureStream;
checkCudaErrors(cudaStreamCreate(&captureStream));
checkCudaErrors(cudaStreamBeginCapture(captureStream, cudaStreamCaptureModeRelaxed));
// Obtain the handle of the graph
checkCudaErrors(cudaStreamGetCaptureInfo(captureStream, &status, NULL, &graph, &dependencies, &numDependencies));
// Create the conditional handle
cudaGraphConditionalHandle handle;
checkCudaErrors(cudaGraphConditionalHandleCreate(&handle, graph));
// Insert kernel node A
capturedWhileKernel<<<1, 1, 0, captureStream>>>(dPtr, handle);
// Obtain the handle for node A
checkCudaErrors(cudaStreamGetCaptureInfo(captureStream, &status, NULL, &graph, &dependencies, &numDependencies));
// Insert conditional node B
cudaGraphNode_t node;
cudaGraphNodeParams cParams = { cudaGraphNodeTypeConditional };
cParams.conditional.handle = handle;
cParams.conditional.type = cudaGraphCondTypeWhile;
cParams.conditional.size = 1;
checkCudaErrors(cudaGraphAddNode(&node, graph, dependencies, numDependencies, &cParams));
cudaGraph_t bodyGraph = cParams.conditional.phGraph_out[0];
// Update stream capture dependencies to account for the node we manually added
checkCudaErrors(cudaStreamUpdateCaptureDependencies(captureStream, &node, 1, cudaStreamSetCaptureDependencies));
// Insert kernel node D
capturedWhileEmptyKernel<<<1, 1, 0, captureStream>>>();
checkCudaErrors(cudaStreamEndCapture(captureStream, &graph));
checkCudaErrors(cudaStreamDestroy(captureStream));
// Populate conditional body graph using stream capture
cudaStream_t bodyStream;
checkCudaErrors(cudaStreamCreate(&bodyStream));
checkCudaErrors(cudaStreamBeginCaptureToGraph(bodyStream, bodyGraph, nullptr, nullptr, 0, cudaStreamCaptureModeRelaxed));
// Insert kernel node C
capturedWhileKernel<<<1, 1, 0, bodyStream>>>(dPtr, handle);
checkCudaErrors(cudaStreamEndCapture(bodyStream, nullptr));
checkCudaErrors(cudaStreamDestroy(bodyStream));
checkCudaErrors(cudaGraphInstantiate(&graphExec, graph, NULL, NULL, 0));
// Initialize device memory and launch the graph
// Device memory is zero, so the conditional node will not execute
checkCudaErrors(cudaMemset(dPtr, 0, 1)); // Set dPtr to 0
printf("Host: Launching graph with loop counter set to 0\n");
checkCudaErrors(cudaGraphLaunch(graphExec, 0));
checkCudaErrors(cudaDeviceSynchronize());
// Initialize device memory and launch the graph
checkCudaErrors(cudaMemset(dPtr, 10, 1)); // Set dPtr to 10
printf("Host: Launching graph with loop counter set to 10\n");
checkCudaErrors(cudaGraphLaunch(graphExec, 0));
checkCudaErrors(cudaDeviceSynchronize());
// Cleanup
checkCudaErrors(cudaGraphExecDestroy(graphExec));
checkCudaErrors(cudaGraphDestroy(graph));
checkCudaErrors(cudaFree(dPtr));
printf("capturedWhileGraph: Complete\n\n");
}
int main(int argc, char **argv) {
int device = findCudaDevice(argc, (const char **)argv);
int driverVersion = 0;
cudaDriverGetVersion(&driverVersion);
printf("Driver version is: %d.%d\n", driverVersion / 1000,
(driverVersion % 100) / 10);
if (driverVersion < 12030) {
printf("Waiving execution as driver does not support Graph Conditional Nodes\n");
exit(EXIT_WAIVED);
}
simpleIfGraph();
simpleDoWhileGraph();
capturedWhileGraph();
return 0;
}

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2017
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "graphConditionalNodes", "graphConditionalNodes_vs2017.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
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Debug|x64 = Debug|x64
Release|x64 = Release|x64
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{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
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<CudaCompile>
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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2019
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "graphConditionalNodes", "graphConditionalNodes_vs2019.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
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GlobalSection(ProjectConfigurationPlatforms) = postSolution
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{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
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</Project>

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2022
Project("{8BC9CEB8-8B4A-11D0-8D11-00A0C91BC942}") = "graphConditionalNodes", "graphConditionalNodes_vs2022.vcxproj", "{997E0757-EA74-4A4E-A0FC-47D8C8831A15}"
EndProject
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
Debug|x64 = Debug|x64
Release|x64 = Release|x64
EndGlobalSection
GlobalSection(ProjectConfigurationPlatforms) = postSolution
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.ActiveCfg = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Debug|x64.Build.0 = Debug|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.ActiveCfg = Release|x64
{997E0757-EA74-4A4E-A0FC-47D8C8831A15}.Release|x64.Build.0 = Release|x64
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HideSolutionNode = FALSE
EndGlobalSection
EndGlobal

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<LinkTimeCodeGeneration>Default</LinkTimeCodeGeneration>
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<CudaCompile>
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</CudaCompile>
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