mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2026-10-23 21:28:17 +08:00
Add and update samples for cuda 11.0 support
This commit is contained in:
@@ -72,9 +72,9 @@ endif
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# architecture
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HOST_ARCH := $(shell uname -m)
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TARGET_ARCH ?= $(HOST_ARCH)
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ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 ppc64le armv7l))
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ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le armv7l))
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ifneq ($(TARGET_ARCH),$(HOST_ARCH))
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ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 ppc64le))
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ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le))
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TARGET_SIZE := 64
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else ifneq (,$(filter $(TARGET_ARCH),armv7l))
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TARGET_SIZE := 32
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@@ -85,8 +85,17 @@ ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 ppc64le armv7l))
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else
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$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
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endif
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# sbsa and aarch64 systems look similar. Need to differentiate them at host level for now.
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ifeq ($(HOST_ARCH),aarch64)
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ifeq ($(CUDA_PATH)/targets/sbsa-linux,$(shell ls -1d $(CUDA_PATH)/targets/sbsa-linux))
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HOST_ARCH := sbsa
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TARGET_ARCH := sbsa
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endif
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endif
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ifneq ($(TARGET_ARCH),$(HOST_ARCH))
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ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-ppc64le))
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ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-sbsa x86_64-ppc64le))
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$(error ERROR - cross compiling from $(HOST_ARCH) to $(TARGET_ARCH) is not supported!)
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endif
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endif
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@@ -141,6 +150,8 @@ else ifneq ($(TARGET_ARCH),$(HOST_ARCH))
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else ifeq ($(TARGET_OS), android)
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HOST_COMPILER ?= aarch64-linux-android-clang++
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endif
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else ifeq ($(TARGET_ARCH),sbsa)
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HOST_COMPILER ?= aarch64-linux-gnu-g++
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else ifeq ($(TARGET_ARCH),ppc64le)
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HOST_COMPILER ?= powerpc64le-linux-gnu-g++
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endif
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@@ -185,19 +196,27 @@ ifneq ($(TARGET_ARCH),$(HOST_ARCH))
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CCFLAGS += --sysroot=$(TARGET_FS)
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endif
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LDFLAGS += --sysroot=$(TARGET_FS)
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LDFLAGS += -rpath-link=$(TARGET_FS)/lib -L $(TARGET_FS)/lib
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LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib -L $(TARGET_FS)/usr/lib
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LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/aarch64-linux-gnu -L $(TARGET_FS)/usr/lib/aarch64-linux-gnu
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LDFLAGS += -rpath-link=$(TARGET_FS)/lib -L$(TARGET_FS)/lib
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LDFLAGS += -rpath-link=$(TARGET_FS)/lib/aarch64-linux-gnu -L$(TARGET_FS)/lib/aarch64-linux-gnu
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LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib -L$(TARGET_FS)/usr/lib
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LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/aarch64-linux-gnu -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
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LDFLAGS += --unresolved-symbols=ignore-in-shared-libs
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CCFLAGS += -isystem=$(TARGET_FS)/usr/include
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CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu
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CCFLAGS += -isystem=$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include
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CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu -I$(TARGET_FS)/usr/include/aarch64-linux-gnu
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endif
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endif
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ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
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CCFLAGS += -DWIN_INTERFACE_CUSTOM -I/usr/include/aarch64-qnx-gnu
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LDFLAGS += -lsocket
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LDFLAGS += -rpath=/usr/lib/aarch64-qnx-gnu -L/usr/lib/aarch64-qnx-gnu
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ifneq ($(TARGET_FS),)
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LDFLAGS += -rpath=$(TARGET_FS)/usr/lib -L $(TARGET_FS)/usr/lib
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LDFLAGS += -rpath=$(TARGET_FS)/usr/libnvidia -L $(TARGET_FS)/usr/libnvidia
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endif
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ifdef TARGET_OVERRIDE # cuda toolkit targets override
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NVCCFLAGS += -target-dir $(TARGET_OVERRIDE)
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endif
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endif
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endif
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ifeq ($(TARGET_OS),qnx)
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CCFLAGS += -DWIN_INTERFACE_CUSTOM
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LDFLAGS += -lsocket
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endif
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# Install directory of different arch
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@@ -206,6 +225,8 @@ ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
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CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-gnueabihf/
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else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
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CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux/
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else ifeq ($(TARGET_ARCH)-$(TARGET_OS),sbsa-linux)
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CUDA_INSTALL_TARGET_DIR = targets/sbsa-linux/
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else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-android)
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CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-androideabi/
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else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-android)
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@@ -259,8 +280,8 @@ ifeq ($(GENCODE_FLAGS),)
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$(foreach sm,$(SMS),$(eval GENCODE_FLAGS += -gencode arch=compute_$(sm),code=sm_$(sm)))
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ifeq ($(SMS),)
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# Generate PTX code from SM 30
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GENCODE_FLAGS += -gencode arch=compute_30,code=compute_30
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# Generate PTX code from SM 35
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GENCODE_FLAGS += -gencode arch=compute_35,code=compute_35
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endif
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# Generate PTX code from the highest SM architecture in $(SMS) to guarantee forward-compatibility
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83
Samples/cannyEdgeDetectorNPP/NsightEclipse.xml
Normal file
83
Samples/cannyEdgeDetectorNPP/NsightEclipse.xml
Normal file
@@ -0,0 +1,83 @@
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<?xml version="1.0" encoding="UTF-8"?>
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<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
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<entry>
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<name>cannyEdgeDetectorNPP</name>
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<description><![CDATA[An NPP CUDA Sample that demonstrates the recommended parameters to use with the nppiFilterCannyBorder_8u_C1R Canny Edge Detection image filter function. This function expects a single channel 8-bit grayscale input image. You can generate a grayscale image from a color image by first calling nppiColorToGray() or nppiRGBToGray(). The Canny Edge Detection function combines and improves on the techniques required to produce an edge detection image using multiple steps.]]></description>
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<devicecompilation>whole</devicecompilation>
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<fallback_min_ptx>true</fallback_min_ptx>
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<includepaths>
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<path>../../Common/UtilNPP</path>
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<path>../../Common/FreeImage/include</path>
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<path>./</path>
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<path>../</path>
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<path>../../common/inc</path>
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</includepaths>
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<keyconcepts>
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<concept level="basic">Performance Strategies</concept>
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<concept level="basic">Image Processing</concept>
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<concept level="basic">NPP Library</concept>
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</keyconcepts>
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<keywords>
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<keyword>CUDA</keyword>
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<keyword>NPP</keyword>
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<keyword>Image Processing</keyword>
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</keywords>
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<libraries>
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<library>nppisu_static</library>
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<library>nppif_static</library>
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<library>nppc_static</library>
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<library>culibos</library>
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<library>freeimage</library>
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</libraries>
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<librarypaths>
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<path>../../Common/FreeImage/lib/$(TARGET_OS)</path>
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<path>../../Common/FreeImage/lib/$(TARGET_OS)/$(TARGET_ARCH)</path>
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</librarypaths>
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<nsight_eclipse>true</nsight_eclipse>
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<primary_file>cannyEdgeDetectorNPP.cpp</primary_file>
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<required_dependencies>
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<dependency>FreeImage</dependency>
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<dependency>NPP</dependency>
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</required_dependencies>
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<scopes>
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<scope>1:CUDA Basic Topics</scope>
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<scope>1:Performance Strategies</scope>
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<scope>2:Image Processing</scope>
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<scope>2:Computer Vision</scope>
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</scopes>
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<sm-arch>sm35</sm-arch>
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<sm-arch>sm37</sm-arch>
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<sm-arch>sm50</sm-arch>
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<sm-arch>sm52</sm-arch>
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<sm-arch>sm60</sm-arch>
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<sm-arch>sm61</sm-arch>
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<sm-arch>sm70</sm-arch>
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<sm-arch>sm72</sm-arch>
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<sm-arch>sm75</sm-arch>
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<sm-arch>sm80</sm-arch>
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<supported_envs>
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<env>
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<arch>x86_64</arch>
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<platform>linux</platform>
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</env>
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<env>
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<platform>windows7</platform>
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</env>
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<env>
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<arch>x86_64</arch>
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<platform>macosx</platform>
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</env>
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<env>
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<arch>arm</arch>
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</env>
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<env>
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<arch>ppc64le</arch>
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<platform>linux</platform>
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</env>
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</supported_envs>
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<supported_sm_architectures>
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<include>all</include>
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</supported_sm_architectures>
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<title>Canny Edge Detector NPP</title>
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<type>exe</type>
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</entry>
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@@ -10,11 +10,11 @@ Performance Strategies, Image Processing, NPP Library
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## Supported SM Architectures
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[SM 3.0 ](https://developer.nvidia.com/cuda-gpus) [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)
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[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)
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## Supported OSes
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Linux, Windows, MacOSX
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Linux, Windows
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## Supported CPU Architecture
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@@ -27,7 +27,7 @@ x86_64, ppc64le, armv7l
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## Prerequisites
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Download and install the [CUDA Toolkit 10.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
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Download and install the [CUDA Toolkit 11.0](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
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Make sure the dependencies mentioned in [Dependencies]() section above are installed.
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## Build and Run
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@@ -67,29 +67,5 @@ The samples makefiles can take advantage of certain options:
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$ make HOST_COMPILER=g++
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```
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### Mac
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The Mac samples are built using makefiles. To use the makefiles, change directory into the sample directory you wish to build, and run make:
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```
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$ cd <sample_dir>
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$ make
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```
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The samples makefiles can take advantage of certain options:
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* **dbg=1** - build with debug symbols
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```
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$ make dbg=1
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```
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* **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".
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```
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$ make SMS="A B ..."
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```
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* **HOST_COMPILER=<host_compiler>** - override the default clang host compiler. See the [Mac Installation Guide](http://docs.nvidia.com/cuda/cuda-installation-guide-mac-os-x/index.html#system-requirements) for a list of supported host compilers.
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```
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$ make HOST_COMPILER=clang
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```
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## References (for more details)
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@@ -47,6 +47,27 @@
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#include <helper_cuda.h>
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#include <helper_string.h>
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inline int cudaDeviceInit(int argc, const char **argv) {
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int deviceCount;
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checkCudaErrors(cudaGetDeviceCount(&deviceCount));
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if (deviceCount == 0) {
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std::cerr << "CUDA error: no devices supporting CUDA." << std::endl;
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exit(EXIT_FAILURE);
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}
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int dev = findCudaDevice(argc, argv);
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cudaDeviceProp deviceProp;
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cudaGetDeviceProperties(&deviceProp, dev);
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std::cerr << "cudaSetDevice GPU" << dev << " = " << deviceProp.name
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<< std::endl;
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checkCudaErrors(cudaSetDevice(dev));
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return dev;
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}
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bool printfNPPinfo(int argc, char *argv[]) {
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const NppLibraryVersion *libVer = nppGetLibVersion();
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@@ -74,7 +95,7 @@ int main(int argc, char *argv[]) {
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std::string sFilename;
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char *filePath;
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int dev = findCudaDevice(argc, (const char **)argv);
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cudaDeviceInit(argc, (const char **)argv);
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if (printfNPPinfo(argc, argv) == false) {
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exit(EXIT_SUCCESS);
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@@ -62,7 +62,7 @@
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<OutputFile>$(OutDir)/cannyEdgeDetectorNPP.exe</OutputFile>
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</Link>
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<CudaCompile>
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<CodeGeneration>compute_30,compute_30;</CodeGeneration>
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<CodeGeneration>compute_35,compute_35;</CodeGeneration>
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<AdditionalOptions>-Xcompiler "/wd 4819" %(AdditionalOptions)</AdditionalOptions>
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<Include>./;../../Common</Include>
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<Defines>WIN32</Defines>
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@@ -62,7 +62,7 @@
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<OutputFile>$(OutDir)/cannyEdgeDetectorNPP.exe</OutputFile>
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</Link>
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<CudaCompile>
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<CodeGeneration>compute_30,compute_30;</CodeGeneration>
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<CodeGeneration>compute_35,compute_35;</CodeGeneration>
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<AdditionalOptions>-Xcompiler "/wd 4819" %(AdditionalOptions)</AdditionalOptions>
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<Include>./;../../Common</Include>
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<Defines>WIN32</Defines>
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@@ -62,7 +62,7 @@
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<OutputFile>$(OutDir)/cannyEdgeDetectorNPP.exe</OutputFile>
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</Link>
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<CudaCompile>
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<CodeGeneration>compute_30,compute_30;</CodeGeneration>
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<CodeGeneration>compute_35,compute_35;</CodeGeneration>
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<AdditionalOptions>-Xcompiler "/wd 4819" %(AdditionalOptions)</AdditionalOptions>
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<Include>./;../../Common</Include>
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<Defines>WIN32</Defines>
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@@ -67,7 +67,7 @@
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<OutputFile>$(OutDir)/cannyEdgeDetectorNPP.exe</OutputFile>
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</Link>
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<CudaCompile>
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<CodeGeneration>compute_30,compute_30;</CodeGeneration>
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<CodeGeneration>compute_35,compute_35;</CodeGeneration>
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<AdditionalOptions>-Xcompiler "/wd 4819" %(AdditionalOptions)</AdditionalOptions>
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<Include>./;../../Common</Include>
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<Defines>WIN32</Defines>
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@@ -63,7 +63,7 @@
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<OutputFile>$(OutDir)/cannyEdgeDetectorNPP.exe</OutputFile>
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</Link>
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<CudaCompile>
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<CodeGeneration>compute_30,compute_30;</CodeGeneration>
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<CodeGeneration>compute_35,compute_35;</CodeGeneration>
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<AdditionalOptions>-Xcompiler "/wd 4819" %(AdditionalOptions)</AdditionalOptions>
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<Include>./;../../Common</Include>
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<Defines>WIN32</Defines>
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Reference in New Issue
Block a user