add and update samples for CUDA 11.5

This commit is contained in:
Rutwik Choughule
2021-10-21 16:34:49 +05:30
parent 3342d604fe
commit 1f76a2d110
2796 changed files with 1511725 additions and 827 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}/recursiveGaussian"
}
]
}

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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) 2019, 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 $(TARGET_OS) for TARGET_OS!)
endif
# host compiler
ifeq ($(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 += --qpp-config 5.4.0,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 QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - recursiveGaussian is not supported on QNX - 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 :=
################################################################################
# Makefile include to help find GL Libraries
include ./findgllib.mk
# OpenGL specific libraries
ifeq ($(TARGET_OS),darwin)
# Mac OSX specific libraries and paths to include
LIBRARIES += -L/System/Library/Frameworks/OpenGL.framework/Libraries
LIBRARIES += -lGL -lGLU
ALL_LDFLAGS += -Xlinker -framework -Xlinker GLUT
else
LIBRARIES += $(GLLINK)
LIBRARIES += -lGL -lGLU -lglut
endif
#Detect if installed version of GCC supports required C++11
ifeq ($(TARGET_OS),linux)
empty :=
space := $(empty) $(empty)
GCCVERSIONSTRING := $(shell expr `$(HOST_COMPILER) -dumpversion`)
#Create version number without "."
GCCVERSION := $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f1 -d.)
GCCVERSION += $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f2 -d.)
GCCVERSION += $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f3 -d.)
# Make sure the version number has at least 3 decimals
GCCVERSION += 00
# Remove spaces from the version number
GCCVERSION := $(subst $(space),$(empty),$(GCCVERSION))
#$(warning $(GCCVERSION))
IS_MIN_VERSION := $(shell expr `echo $(GCCVERSION)` \>= 51000)
ifeq ($(IS_MIN_VERSION), 1)
$(info >>> GCC Version is greater or equal to 5.1.0 <<<)
else
$(info >>> Waiving build. Minimum GCC version required is 5.1.0<<<)
SAMPLE_ENABLED := 0
endif
endif
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64))
SMS ?= 35 37 50 52 60 61 70 72 75 80 86
else
SMS ?= 35 37 50 52 60 61 70 75 80 86
endif
ifeq ($(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 ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: recursiveGaussian
check.deps:
ifeq ($(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
recursiveGaussian.o:recursiveGaussian.cpp
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
recursiveGaussian_cuda.o:recursiveGaussian_cuda.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
recursiveGaussian: recursiveGaussian.o recursiveGaussian_cuda.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
$(EXEC) ./recursiveGaussian
clean:
rm -f recursiveGaussian recursiveGaussian.o recursiveGaussian_cuda.o
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/recursiveGaussian
clobber: clean

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>recursiveGaussian</name>
<cuda_api_list>
<toolkit>cudaGraphicsMapResources</toolkit>
<toolkit>cudaGraphicsUnmapResources</toolkit>
<toolkit>cudaGraphicsResourceGetMappedPointer</toolkit>
<toolkit>cudaGraphicsRegisterResource</toolkit>
<toolkit>cudaGraphicsGLRegisterBuffer</toolkit>
<toolkit>cudaGraphicsUnregisterResource</toolkit>
</cuda_api_list>
<description><![CDATA[This sample implements a Gaussian blur using Deriche's recursive method. The advantage of this method is that the execution time is independent of the filter width.]]></description>
<devicecompilation>whole</devicecompilation>
<files>
<file>data\lena.ppm</file>
<file>data\ref_10.ppm</file>
<file>data\ref_14.ppm</file>
<file>data\ref_18.ppm</file>
<file>data\ref_22.ppm</file>
</files>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../Common</path>
</includepaths>
<keyconcepts>
<concept level="advanced">Graphics Interop</concept>
<concept level="advanced">Image Processing</concept>
</keyconcepts>
<keywords>
<keyword>GPGPU</keyword>
<keyword>CUDA</keyword>
<keyword>Image Processing</keyword>
<keyword>box filter</keyword>
<keyword>opengl</keyword>
<keyword>openGL</keyword>
</keywords>
<libraries>
<library>GLU</library>
<library>GL</library>
<library framework="true" os="macosx">GLUT</library>
<library os="linux">GLEW</library>
<library os="linux">glut</library>
<library os="linux">X11</library>
</libraries>
<librarypaths>
<path arch="x86_64" os="linux">../../common/lib/linux/x86_64</path>
<path arch="armv7l" os="linux">../../common/lib/linux/armv7l</path>
<path os="macosx">../../common/lib/darwin</path>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>recursiveGaussian.cpp</primary_file>
<qatests>
<qatest>-sigma=10 -file=ref_10.ppm</qatest>
<qatest>-sigma=14 -file=ref_14.ppm</qatest>
<qatest>-sigma=18 -file=ref_18.ppm</qatest>
<qatest>-sigma=22 -file=ref_22.ppm</qatest>
</qatests>
<required_dependencies>
<dependency>X11</dependency>
<dependency>GL</dependency>
</required_dependencies>
<scopes>
<scope>2:Graphics Interop</scope>
<scope>2:Image Processing</scope>
<scope>2:Computer Vision</scope>
</scopes>
<sm-arch>sm35</sm-arch>
<sm-arch>sm37</sm-arch>
<sm-arch>sm50</sm-arch>
<sm-arch>sm52</sm-arch>
<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>
<supported_envs>
<env>
<arch>x86_64</arch>
<platform>linux</platform>
</env>
<env>
<platform>windows7</platform>
</env>
<env>
<arch>x86_64</arch>
<platform>macosx</platform>
</env>
<env>
<arch>arm</arch>
</env>
</supported_envs>
<supported_sm_architectures>
<include>all</include>
</supported_sm_architectures>
<title>Recursive Gaussian Filter</title>
<type>exe</type>
</entry>

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# recursiveGaussian - Recursive Gaussian Filter
## Description
This sample implements a Gaussian blur using Deriche's recursive method. The advantage of this method is that the execution time is independent of the filter width.
## Key Concepts
Graphics Interop, Image Processing
## Supported SM Architectures
[SM 3.5 ](https://developer.nvidia.com/cuda-gpus) [SM 3.7 ](https://developer.nvidia.com/cuda-gpus) [SM 5.0 ](https://developer.nvidia.com/cuda-gpus) [SM 5.2 ](https://developer.nvidia.com/cuda-gpus) [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)
## Supported OSes
Linux, Windows
## Supported CPU Architecture
x86_64, armv7l
## CUDA APIs involved
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
cudaGraphicsMapResources, cudaGraphicsUnmapResources, cudaGraphicsResourceGetMappedPointer, cudaGraphicsRegisterResource, cudaGraphicsGLRegisterBuffer, cudaGraphicsUnregisterResource
## Dependencies needed to build/run
[X11](../../README.md#x11), [GL](../../README.md#gl)
## Prerequisites
Download and install the [CUDA Toolkit 11.5](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## 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, 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=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) 2020, 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.
#
################################################################################
#
# findgllib.mk is used to find the necessary GL Libraries for specific distributions
# this is supported on Mac OSX and Linux Platforms
#
################################################################################
# Determine OS platform and unix distribution
ifeq ("$(TARGET_OS)","linux")
# first search lsb_release
DISTRO := $(shell lsb_release -i -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
ifeq ("$(DISTRO)","")
# second search and parse /etc/issue
DISTRO := $(shell awk '{print $$1}' /etc/issue | tr -d "[:space:]" | sed -e "/^$$/d" | tr "[:upper:]" "[:lower:]")
# ensure data from /etc/issue is valid
ifeq (,$(filter $(DISTRO),ubuntu fedora red rhel centos suse))
DISTRO :=
endif
ifeq ("$(DISTRO)","")
# third, we can search in /etc/os-release or /etc/{distro}-release
DISTRO := $(shell awk '/ID/' /etc/*-release | sed 's/ID=//' | grep -v "VERSION" | grep -v "ID" | grep -v "DISTRIB")
endif
endif
endif
ifeq ("$(TARGET_OS)","linux")
# $(info) >> findgllib.mk -> LINUX path <<<)
# Each set of Linux Distros have different paths for where to find their OpenGL libraries reside
UBUNTU = $(shell echo $(DISTRO) | grep -i ubuntu >/dev/null 2>&1; echo $$?)
FEDORA = $(shell echo $(DISTRO) | grep -i fedora >/dev/null 2>&1; echo $$?)
RHEL = $(shell echo $(DISTRO) | grep -i 'red\|rhel' >/dev/null 2>&1; echo $$?)
CENTOS = $(shell echo $(DISTRO) | grep -i centos >/dev/null 2>&1; echo $$?)
SUSE = $(shell echo $(DISTRO) | grep -i 'suse\|sles' >/dev/null 2>&1; echo $$?)
ifeq ("$(UBUNTU)","0")
ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
GLPATH := /usr/arm-linux-gnueabihf/lib
GLLINK := -L/usr/arm-linux-gnueabihf/lib
ifneq ($(TARGET_FS),)
GLPATH += $(TARGET_FS)/usr/lib/arm-linux-gnueabihf
GLLINK += -L$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
endif
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-aarch64)
GLPATH := /usr/aarch64-linux-gnu/lib
GLLINK := -L/usr/aarch64-linux-gnu/lib
ifneq ($(TARGET_FS),)
GLPATH += $(TARGET_FS)/usr/lib
GLPATH += $(TARGET_FS)/usr/lib/aarch64-linux-gnu
GLLINK += -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
endif
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-ppc64le)
GLPATH := /usr/powerpc64le-linux-gnu/lib
GLLINK := -L/usr/powerpc64le-linux-gnu/lib
else
UBUNTU_PKG_NAME = $(shell which dpkg >/dev/null 2>&1 && dpkg -l 'nvidia-*' | grep '^ii' | awk '{print $$2}' | head -1)
ifneq ("$(UBUNTU_PKG_NAME)","")
GLPATH ?= /usr/lib/$(UBUNTU_PKG_NAME)
GLLINK ?= -L/usr/lib/$(UBUNTU_PKG_NAME)
endif
DFLT_PATH ?= /usr/lib
endif
endif
ifeq ("$(SUSE)","0")
GLPATH ?= /usr/X11R6/lib64
GLLINK ?= -L/usr/X11R6/lib64
DFLT_PATH ?= /usr/lib64
endif
ifeq ("$(FEDORA)","0")
GLPATH ?= /usr/lib64/nvidia
GLLINK ?= -L/usr/lib64/nvidia
DFLT_PATH ?= /usr/lib64
endif
ifeq ("$(RHEL)","0")
GLPATH ?= /usr/lib64/nvidia
GLLINK ?= -L/usr/lib64/nvidia
DFLT_PATH ?= /usr/lib64
endif
ifeq ("$(CENTOS)","0")
GLPATH ?= /usr/lib64/nvidia
GLLINK ?= -L/usr/lib64/nvidia
DFLT_PATH ?= /usr/lib64
endif
# find libGL, libGLU
GLLIB := $(shell find -L $(GLPATH) $(DFLT_PATH) -name libGL.so -print 2>/dev/null)
GLULIB := $(shell find -L $(GLPATH) $(DFLT_PATH) -name libGLU.so -print 2>/dev/null)
ifeq ("$(GLLIB)","")
$(info >>> WARNING - libGL.so not found, refer to CUDA Getting Started Guide for how to find and install them. <<<)
SAMPLE_ENABLED := 0
endif
ifeq ("$(GLULIB)","")
$(info >>> WARNING - libGLU.so not found, refer to CUDA Getting Started Guide for how to find and install them. <<<)
SAMPLE_ENABLED := 0
endif
HEADER_SEARCH_PATH ?= $(TARGET_FS)/usr/include
ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
HEADER_SEARCH_PATH += /usr/arm-linux-gnueabihf/include
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-aarch64-linux)
HEADER_SEARCH_PATH += /usr/aarch64-linux-gnu/include
endif
GLHEADER := $(shell find -L $(HEADER_SEARCH_PATH) -name gl.h -print 2>/dev/null)
GLUHEADER := $(shell find -L $(HEADER_SEARCH_PATH) -name glu.h -print 2>/dev/null)
ifeq ("$(GLHEADER)","")
$(info >>> WARNING - gl.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<)
SAMPLE_ENABLED := 0
endif
ifeq ("$(GLUHEADER)","")
$(info >>> WARNING - glu.h not found, refer to CUDA Getting Started Guide for how to find and install them. <<<)
SAMPLE_ENABLED := 0
endif
else
# This would be the Mac OS X path if we had to do anything special
endif

View File

@@ -0,0 +1,535 @@
/* Copyright (c) 2021, 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.
*/
/*
Recursive Gaussian filter
sgreen 8/1/08
This code sample implements a Gaussian blur using Deriche's recursive method:
http://citeseer.ist.psu.edu/deriche93recursively.html
This is similar to the box filter sample in the SDK, but it uses the previous
outputs of the filter as well as the previous inputs. This is also known as an
IIR (infinite impulse response) filter, since its response to an input impulse
can last forever.
The main advantage of this method is that the execution time is independent of
the filter width.
The GPU processes columns of the image in parallel. To avoid uncoalesced reads
for the row pass we transpose the image and then transpose it back again
afterwards.
The implementation is based on code from the CImg library:
http://cimg.sourceforge.net/
Thanks to David Tschumperl<72> and all the CImg contributors!
*/
#pragma warning(disable : 4819)
// OpenGL Graphics includes
#include <helper_gl.h>
#if defined(__APPLE__) || defined(MACOSX)
#pragma clang diagnostic ignored "-Wdeprecated-declarations"
#include <GLUT/glut.h>
#ifndef glutCloseFunc
#define glutCloseFunc glutWMCloseFunc
#endif
#else
#include <GL/freeglut.h>
#endif
// CUDA includes and interop headers
#include <cuda_runtime.h>
#include <cuda_gl_interop.h>
// CUDA utilities and system includes
#include <helper_functions.h>
#include <helper_cuda.h> // includes cuda.h and cuda_runtime_api.h
// Includes
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#define MAX(a, b) ((a > b) ? a : b)
#define USE_SIMPLE_FILTER 0
#define MAX_EPSILON_ERROR 5.0f
#define THRESHOLD 0.15f
// Define the files that are to be save and the reference images for validation
const char *sOriginal[] = {"lena_10.ppm", "lena_14.ppm", "lena_18.ppm",
"lena_22.ppm", NULL};
const char *sReference[] = {"ref_10.ppm", "ref_14.ppm", "ref_18.ppm",
"ref_22.ppm", NULL};
const char *image_filename = "lena.ppm";
float sigma = 10.0f;
int order = 0;
int nthreads = 64; // number of threads per block
unsigned int width, height;
unsigned int *h_img = NULL;
unsigned int *d_img = NULL;
unsigned int *d_temp = NULL;
GLuint pbo = 0; // OpenGL pixel buffer object
GLuint texid = 0; // texture
cudaGraphicsResource_t cuda_vbo_resource;
StopWatchInterface *timer = 0;
// Auto-Verification Code
const int frameCheckNumber = 4;
int fpsCount = 0; // FPS count for averaging
int fpsLimit = 1; // FPS limit for sampling
unsigned int frameCount = 0;
int *pArgc = NULL;
char **pArgv = NULL;
bool runBenchmark = false;
const char *sSDKsample = "CUDA Recursive Gaussian";
extern "C" void transpose(unsigned int *d_src, unsigned int *d_dest,
unsigned int width, int height);
extern "C" void gaussianFilterRGBA(unsigned int *d_src, unsigned int *d_dest,
unsigned int *d_temp, int width, int height,
float sigma, int order, int nthreads);
void cleanup();
void computeFPS() {
frameCount++;
fpsCount++;
if (fpsCount == fpsLimit) {
char fps[256];
float ifps = 1.f / (sdkGetAverageTimerValue(&timer) / 1000.f);
sprintf(fps, "%s (sigma=%4.2f): %3.1f fps", sSDKsample, sigma, ifps);
glutSetWindowTitle(fps);
fpsCount = 0;
fpsLimit = ftoi(MAX(ifps, 1.f));
sdkResetTimer(&timer);
}
}
// display results using OpenGL
void display() {
sdkStartTimer(&timer);
// execute filter, writing results to pbo
unsigned int *d_result;
checkCudaErrors(cudaGraphicsMapResources(1, &cuda_vbo_resource, 0));
size_t num_bytes;
checkCudaErrors(cudaGraphicsResourceGetMappedPointer(
(void **)&d_result, &num_bytes, cuda_vbo_resource));
gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
nthreads);
// unmap buffer object
checkCudaErrors(cudaGraphicsUnmapResources(1, &cuda_vbo_resource, 0));
// load texture from pbo
glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, pbo);
glBindTexture(GL_TEXTURE_2D, texid);
glPixelStorei(GL_UNPACK_ALIGNMENT, 1);
glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, width, height, GL_RGBA,
GL_UNSIGNED_BYTE, 0);
glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, 0);
// display results
glClear(GL_COLOR_BUFFER_BIT);
glEnable(GL_TEXTURE_2D);
glDisable(GL_DEPTH_TEST);
glBegin(GL_QUADS);
glTexCoord2f(0, 1);
glVertex2f(0, 0);
glTexCoord2f(1, 1);
glVertex2f(1, 0);
glTexCoord2f(1, 0);
glVertex2f(1, 1);
glTexCoord2f(0, 0);
glVertex2f(0, 1);
glEnd();
glDisable(GL_TEXTURE_2D);
glutSwapBuffers();
sdkStopTimer(&timer);
computeFPS();
}
void idle() { glutPostRedisplay(); }
void cleanup() {
sdkDeleteTimer(&timer);
checkCudaErrors(cudaFree(d_img));
checkCudaErrors(cudaFree(d_temp));
if (!runBenchmark) {
if (pbo) {
// unregister this buffer object with CUDA
checkCudaErrors(cudaGraphicsUnregisterResource(cuda_vbo_resource));
glDeleteBuffers(1, &pbo);
}
if (texid) {
glDeleteTextures(1, &texid);
}
}
}
void keyboard(unsigned char key, int x, int y) {
switch (key) {
case 27:
#if defined(__APPLE__) || defined(MACOSX)
exit(EXIT_SUCCESS);
#else
glutDestroyWindow(glutGetWindow());
return;
#endif
break;
case '=':
sigma += 0.1f;
break;
case '-':
sigma -= 0.1f;
if (sigma < 0.0) {
sigma = 0.0f;
}
break;
case '+':
sigma += 1.0f;
break;
case '_':
sigma -= 1.0f;
if (sigma < 0.0) {
sigma = 0.0f;
}
break;
case '0':
order = 0;
break;
case '1':
order = 1;
sigma = 0.5f;
break;
case '2':
order = 2;
sigma = 0.5f;
break;
default:
break;
}
printf("sigma = %f\n", sigma);
glutPostRedisplay();
}
void reshape(int x, int y) {
glViewport(0, 0, x, y);
glMatrixMode(GL_MODELVIEW);
glLoadIdentity();
glMatrixMode(GL_PROJECTION);
glLoadIdentity();
glOrtho(0.0, 1.0, 0.0, 1.0, 0.0, 1.0);
}
void initCudaBuffers() {
unsigned int size = width * height * sizeof(unsigned int);
// allocate device memory
checkCudaErrors(cudaMalloc((void **)&d_img, size));
checkCudaErrors(cudaMalloc((void **)&d_temp, size));
checkCudaErrors(cudaMemcpy(d_img, h_img, size, cudaMemcpyHostToDevice));
sdkCreateTimer(&timer);
}
void initGLBuffers() {
// create pixel buffer object to store final image
glGenBuffers(1, &pbo);
glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, pbo);
glBufferData(GL_PIXEL_UNPACK_BUFFER_ARB, width * height * sizeof(GLubyte) * 4,
h_img, GL_STREAM_DRAW_ARB);
glBindBuffer(GL_PIXEL_UNPACK_BUFFER_ARB, 0);
checkCudaErrors(cudaGraphicsGLRegisterBuffer(
&cuda_vbo_resource, pbo, cudaGraphicsRegisterFlagsWriteDiscard));
// create texture for display
glGenTextures(1, &texid);
glBindTexture(GL_TEXTURE_2D, texid);
glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA8, width, height, 0, GL_RGBA,
GL_UNSIGNED_BYTE, NULL);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MIN_FILTER, GL_NEAREST);
glTexParameteri(GL_TEXTURE_2D, GL_TEXTURE_MAG_FILTER, GL_NEAREST);
glBindTexture(GL_TEXTURE_2D, 0);
}
void initGL(int *argc, char **argv) {
glutInit(argc, argv);
glutInitDisplayMode(GLUT_RGB | GLUT_DOUBLE);
glutInitWindowSize(width, height);
glutCreateWindow(sSDKsample);
glutDisplayFunc(display);
glutKeyboardFunc(keyboard);
glutReshapeFunc(reshape);
glutIdleFunc(idle);
#if defined(__APPLE__) || defined(MACOSX)
atexit(cleanup);
#else
glutCloseFunc(cleanup);
#endif
printf("Press '+' and '-' to change filter width\n");
printf("0, 1, 2 - change filter order\n");
if (!isGLVersionSupported(2, 0) ||
!areGLExtensionsSupported(
"GL_ARB_vertex_buffer_object GL_ARB_pixel_buffer_object")) {
fprintf(stderr, "Required OpenGL extensions missing.");
exit(EXIT_FAILURE);
}
}
void benchmark(int iterations) {
// allocate memory for result
unsigned int *d_result;
unsigned int size = width * height * sizeof(unsigned int);
checkCudaErrors(cudaMalloc((void **)&d_result, size));
// warm-up
gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
nthreads);
checkCudaErrors(cudaDeviceSynchronize());
sdkStartTimer(&timer);
// execute the kernel
for (int i = 0; i < iterations; i++) {
gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
nthreads);
}
checkCudaErrors(cudaDeviceSynchronize());
sdkStopTimer(&timer);
// check if kernel execution generated an error
getLastCudaError("Kernel execution failed");
printf("Processing time: %f (ms)\n", sdkGetTimerValue(&timer));
printf("%.2f Mpixels/sec\n",
(width * height * iterations / (sdkGetTimerValue(&timer) / 1000.0f)) /
1e6);
checkCudaErrors(cudaFree(d_result));
}
bool runSingleTest(const char *ref_file, const char *exec_path) {
// allocate memory for result
int nTotalErrors = 0;
unsigned int *d_result;
unsigned int size = width * height * sizeof(unsigned int);
checkCudaErrors(cudaMalloc((void **)&d_result, size));
// warm-up
gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
nthreads);
checkCudaErrors(cudaDeviceSynchronize());
sdkStartTimer(&timer);
gaussianFilterRGBA(d_img, d_result, d_temp, width, height, sigma, order,
nthreads);
checkCudaErrors(cudaDeviceSynchronize());
getLastCudaError("Kernel execution failed");
sdkStopTimer(&timer);
unsigned char *h_result = (unsigned char *)malloc(width * height * 4);
checkCudaErrors(cudaMemcpy(h_result, d_result, width * height * 4,
cudaMemcpyDeviceToHost));
char dump_file[1024];
sprintf(dump_file, "lena_%02d.ppm", (int)sigma);
sdkSavePPM4ub(dump_file, h_result, width, height);
if (!sdkComparePPM(dump_file, sdkFindFilePath(ref_file, exec_path),
MAX_EPSILON_ERROR, THRESHOLD, false)) {
nTotalErrors++;
}
printf("Processing time: %f (ms)\n", sdkGetTimerValue(&timer));
printf("%.2f Mpixels/sec\n",
(width * height / (sdkGetTimerValue(&timer) / 1000.0f)) / 1e6);
checkCudaErrors(cudaFree(d_result));
free(h_result);
printf("Summary: %d errors!\n", nTotalErrors);
printf(nTotalErrors == 0 ? "Test passed\n" : "Test failed!\n");
return (nTotalErrors == 0);
}
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv) {
pArgc = &argc;
pArgv = argv;
char *ref_file = NULL;
#if defined(__linux__)
setenv("DISPLAY", ":0", 0);
#endif
printf("%s Starting...\n\n", sSDKsample);
printf(
"NOTE: The CUDA Samples are not meant for performance measurements. "
"Results may vary when GPU Boost is enabled.\n\n");
// use command-line specified CUDA device, otherwise use device with highest
// Gflops/s
if (argc > 1) {
if (checkCmdLineFlag(argc, (const char **)argv, "file")) {
getCmdLineArgumentString(argc, (const char **)argv, "file", &ref_file);
fpsLimit = frameCheckNumber;
}
}
// Get the path of the filename
char *filename;
if (getCmdLineArgumentString(argc, (const char **)argv, "image", &filename)) {
image_filename = filename;
}
// load image
char *image_path = sdkFindFilePath(image_filename, argv[0]);
if (image_path == NULL) {
fprintf(stderr, "Error unable to find and load image file: '%s'\n",
image_filename);
exit(EXIT_FAILURE);
}
sdkLoadPPM4ub(image_path, (unsigned char **)&h_img, &width, &height);
if (!h_img) {
printf("Error unable to load PPM file: '%s'\n", image_path);
exit(EXIT_FAILURE);
}
printf("Loaded '%s', %d x %d pixels\n", image_path, width, height);
if (checkCmdLineFlag(argc, (const char **)argv, "threads")) {
nthreads = getCmdLineArgumentInt(argc, (const char **)argv, "threads");
}
if (checkCmdLineFlag(argc, (const char **)argv, "sigma")) {
sigma = getCmdLineArgumentFloat(argc, (const char **)argv, "sigma");
}
runBenchmark = checkCmdLineFlag(argc, (const char **)argv, "benchmark");
int device;
struct cudaDeviceProp prop;
cudaGetDevice(&device);
cudaGetDeviceProperties(&prop, device);
if (!strncmp("Tesla", prop.name, 5)) {
printf(
"Tesla card detected, running the test in benchmark mode (no OpenGL "
"display)\n");
// runBenchmark = true;
runBenchmark = true;
}
// Benchmark or AutoTest mode detected, no OpenGL
if (runBenchmark == true || ref_file != NULL) {
findCudaDevice(argc, (const char **)argv);
} else {
// First initialize OpenGL context, and then select CUDA device.
initGL(&argc, argv);
findCudaDevice(argc, (const char **)argv);
}
initCudaBuffers();
if (ref_file) {
printf("(Automated Testing)\n");
bool testPassed = runSingleTest(ref_file, argv[0]);
cleanup();
exit(testPassed ? EXIT_SUCCESS : EXIT_FAILURE);
}
if (runBenchmark) {
printf("(Run Benchmark)\n");
benchmark(100);
cleanup();
exit(EXIT_SUCCESS);
}
initGLBuffers();
glutMainLoop();
exit(EXIT_SUCCESS);
}

View File

@@ -0,0 +1,160 @@
/* Copyright (c) 2021, 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.
*/
/*
Recursive Gaussian filter
sgreen 8/1/08
This code sample implements a Gaussian blur using Deriche's recursive method:
http://citeseer.ist.psu.edu/deriche93recursively.html
This is similar to the box filter sample in the SDK, but it uses the previous
outputs of the filter as well as the previous inputs. This is also known as an
IIR (infinite impulse response) filter, since its response to an input impulse
can last forever.
The main advantage of this method is that the execution time is independent of
the filter width.
The GPU processes columns of the image in parallel. To avoid uncoalesced reads
for the row pass we transpose the image and then transpose it back again
afterwards.
The implementation is based on code from the CImg library:
http://cimg.sourceforge.net/
Thanks to David Tschumperl<72> and all the CImg contributors!
*/
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <cuda_runtime.h>
#include <helper_cuda.h>
#include <helper_math.h>
#include "recursiveGaussian_kernel.cuh"
#define USE_SIMPLE_FILTER 0
// Round a / b to nearest higher integer value
int iDivUp(int a, int b) { return (a % b != 0) ? (a / b + 1) : (a / b); }
/*
Transpose a 2D array (see SDK transpose example)
*/
extern "C" void transpose(uint *d_src, uint *d_dest, uint width, int height) {
dim3 grid(iDivUp(width, BLOCK_DIM), iDivUp(height, BLOCK_DIM), 1);
dim3 threads(BLOCK_DIM, BLOCK_DIM, 1);
d_transpose<<<grid, threads>>>(d_dest, d_src, width, height);
getLastCudaError("Kernel execution failed");
}
/*
Perform Gaussian filter on a 2D image using CUDA
Parameters:
d_src - pointer to input image in device memory
d_dest - pointer to destination image in device memory
d_temp - pointer to temporary storage in device memory
width - image width
height - image height
sigma - sigma of Gaussian
order - filter order (0, 1 or 2)
*/
// 8-bit RGBA version
extern "C" void gaussianFilterRGBA(uint *d_src, uint *d_dest, uint *d_temp,
int width, int height, float sigma,
int order, int nthreads) {
// compute filter coefficients
const float nsigma = sigma < 0.1f ? 0.1f : sigma, alpha = 1.695f / nsigma,
ema = (float)std::exp(-alpha), ema2 = (float)std::exp(-2 * alpha),
b1 = -2 * ema, b2 = ema2;
float a0 = 0, a1 = 0, a2 = 0, a3 = 0, coefp = 0, coefn = 0;
switch (order) {
case 0: {
const float k = (1 - ema) * (1 - ema) / (1 + 2 * alpha * ema - ema2);
a0 = k;
a1 = k * (alpha - 1) * ema;
a2 = k * (alpha + 1) * ema;
a3 = -k * ema2;
} break;
case 1: {
const float k = (1 - ema) * (1 - ema) / ema;
a0 = k * ema;
a1 = a3 = 0;
a2 = -a0;
} break;
case 2: {
const float ea = (float)std::exp(-alpha),
k = -(ema2 - 1) / (2 * alpha * ema),
kn = (-2 * (-1 + 3 * ea - 3 * ea * ea + ea * ea * ea) /
(3 * ea + 1 + 3 * ea * ea + ea * ea * ea));
a0 = kn;
a1 = -kn * (1 + k * alpha) * ema;
a2 = kn * (1 - k * alpha) * ema;
a3 = -kn * ema2;
} break;
default:
fprintf(stderr, "gaussianFilter: invalid order parameter!\n");
return;
}
coefp = (a0 + a1) / (1 + b1 + b2);
coefn = (a2 + a3) / (1 + b1 + b2);
// process columns
#if USE_SIMPLE_FILTER
d_simpleRecursive_rgba<<<iDivUp(width, nthreads), nthreads>>>(
d_src, d_temp, width, height, ema);
#else
d_recursiveGaussian_rgba<<<iDivUp(width, nthreads), nthreads>>>(
d_src, d_temp, width, height, a0, a1, a2, a3, b1, b2, coefp, coefn);
#endif
getLastCudaError("Kernel execution failed");
transpose(d_temp, d_dest, width, height);
getLastCudaError("transpose: Kernel execution failed");
// process rows
#if USE_SIMPLE_FILTER
d_simpleRecursive_rgba<<<iDivUp(height, nthreads), nthreads>>>(
d_dest, d_temp, height, width, ema);
#else
d_recursiveGaussian_rgba<<<iDivUp(height, nthreads), nthreads>>>(
d_dest, d_temp, height, width, a0, a1, a2, a3, b1, b2, coefp, coefn);
#endif
getLastCudaError("Kernel execution failed");
transpose(d_temp, d_dest, height, width);
}

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/* Copyright (c) 2021, 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.
*/
/*
Recursive Gaussian filter
*/
#ifndef _RECURSIVEGAUSSIAN_KERNEL_CU_
#define _RECURSIVEGAUSSIAN_KERNEL_CU_
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <cooperative_groups.h>
namespace cg = cooperative_groups;
#include <helper_cuda.h>
#include <helper_math.h>
#define BLOCK_DIM 16
#define CLAMP_TO_EDGE 1
// Transpose kernel (see transpose CUDA Sample for details)
__global__ void d_transpose(uint *odata, uint *idata, int width, int height) {
// Handle to thread block group
cg::thread_block cta = cg::this_thread_block();
__shared__ uint block[BLOCK_DIM][BLOCK_DIM + 1];
// read the matrix tile into shared memory
unsigned int xIndex = blockIdx.x * BLOCK_DIM + threadIdx.x;
unsigned int yIndex = blockIdx.y * BLOCK_DIM + threadIdx.y;
if ((xIndex < width) && (yIndex < height)) {
unsigned int index_in = yIndex * width + xIndex;
block[threadIdx.y][threadIdx.x] = idata[index_in];
}
cg::sync(cta);
// write the transposed matrix tile to global memory
xIndex = blockIdx.y * BLOCK_DIM + threadIdx.x;
yIndex = blockIdx.x * BLOCK_DIM + threadIdx.y;
if ((xIndex < height) && (yIndex < width)) {
unsigned int index_out = yIndex * height + xIndex;
odata[index_out] = block[threadIdx.x][threadIdx.y];
}
}
// RGBA version
// reads from 32-bit uint array holding 8-bit RGBA
// convert floating point rgba color to 32-bit integer
__device__ uint rgbaFloatToInt(float4 rgba) {
rgba.x = __saturatef(rgba.x); // clamp to [0.0, 1.0]
rgba.y = __saturatef(rgba.y);
rgba.z = __saturatef(rgba.z);
rgba.w = __saturatef(rgba.w);
return (uint(rgba.w * 255) << 24) | (uint(rgba.z * 255) << 16) |
(uint(rgba.y * 255) << 8) | uint(rgba.x * 255);
}
// convert from 32-bit int to float4
__device__ float4 rgbaIntToFloat(uint c) {
float4 rgba;
rgba.x = (c & 0xff) / 255.0f;
rgba.y = ((c >> 8) & 0xff) / 255.0f;
rgba.z = ((c >> 16) & 0xff) / 255.0f;
rgba.w = ((c >> 24) & 0xff) / 255.0f;
return rgba;
}
/*
simple 1st order recursive filter
- processes one image column per thread
parameters:
id - pointer to input data (RGBA image packed into 32-bit integers)
od - pointer to output data
w - image width
h - image height
a - blur parameter
*/
__global__ void d_simpleRecursive_rgba(uint *id, uint *od, int w, int h,
float a) {
unsigned int x = blockIdx.x * blockDim.x + threadIdx.x;
if (x >= w) return;
id += x; // advance pointers to correct column
od += x;
// forward pass
float4 yp = rgbaIntToFloat(*id); // previous output
for (int y = 0; y < h; y++) {
float4 xc = rgbaIntToFloat(*id);
float4 yc =
xc + a * (yp - xc); // simple lerp between current and previous value
*od = rgbaFloatToInt(yc);
id += w;
od += w; // move to next row
yp = yc;
}
// reset pointers to point to last element in column
id -= w;
od -= w;
// reverse pass
// ensures response is symmetrical
yp = rgbaIntToFloat(*id);
for (int y = h - 1; y >= 0; y--) {
float4 xc = rgbaIntToFloat(*id);
float4 yc = xc + a * (yp - xc);
*od = rgbaFloatToInt((rgbaIntToFloat(*od) + yc) * 0.5f);
id -= w;
od -= w; // move to previous row
yp = yc;
}
}
/*
recursive Gaussian filter
parameters:
id - pointer to input data (RGBA image packed into 32-bit integers)
od - pointer to output data
w - image width
h - image height
a0-a3, b1, b2, coefp, coefn - filter parameters
*/
__global__ void d_recursiveGaussian_rgba(uint *id, uint *od, int w, int h,
float a0, float a1, float a2, float a3,
float b1, float b2, float coefp,
float coefn) {
unsigned int x = blockIdx.x * blockDim.x + threadIdx.x;
if (x >= w) return;
id += x; // advance pointers to correct column
od += x;
// forward pass
float4 xp = make_float4(0.0f); // previous input
float4 yp = make_float4(0.0f); // previous output
float4 yb = make_float4(0.0f); // previous output by 2
#if CLAMP_TO_EDGE
xp = rgbaIntToFloat(*id);
yb = coefp * xp;
yp = yb;
#endif
for (int y = 0; y < h; y++) {
float4 xc = rgbaIntToFloat(*id);
float4 yc = a0 * xc + a1 * xp - b1 * yp - b2 * yb;
*od = rgbaFloatToInt(yc);
id += w;
od += w; // move to next row
xp = xc;
yb = yp;
yp = yc;
}
// reset pointers to point to last element in column
id -= w;
od -= w;
// reverse pass
// ensures response is symmetrical
float4 xn = make_float4(0.0f);
float4 xa = make_float4(0.0f);
float4 yn = make_float4(0.0f);
float4 ya = make_float4(0.0f);
#if CLAMP_TO_EDGE
xn = xa = rgbaIntToFloat(*id);
yn = coefn * xn;
ya = yn;
#endif
for (int y = h - 1; y >= 0; y--) {
float4 xc = rgbaIntToFloat(*id);
float4 yc = a2 * xn + a3 * xa - b1 * yn - b2 * ya;
xa = xn;
xn = xc;
ya = yn;
yn = yc;
*od = rgbaFloatToInt(rgbaIntToFloat(*od) + yc);
id -= w;
od -= w; // move to previous row
}
}
#endif // #ifndef _GAUSSIAN_KERNEL_H_

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Microsoft Visual Studio Solution File, Format Version 12.00
# Visual Studio 2017
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