mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2025-04-10 18:22:11 +01:00
Remove cppIntegration
This commit is contained in:
Rob Armstrong
parent
ff264a798f
commit
9d8f61431e
@ -4,7 +4,9 @@
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* Removed the following outdated samples:
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* `0_Introduction`
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* `c++11_cuda` demonstrating CUDA and C++ 11 interoperability (reason: obsolete)
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* `concurrentKernels.cu` demonstrating the ability to run multiple kernels simultaneously (reason: obsolete)
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* `concurrentKernels` demonstrating the ability to run multiple kernels simultaneously (reason: obsolete)
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* `cppIntegration` demonstrating calling between .cu and .cpp files (reason: obsolete)
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### CUDA 12.5
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@ -1,18 +0,0 @@
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{
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"configurations": [
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{
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"name": "Linux",
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"includePath": [
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"${workspaceFolder}/**",
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"${workspaceFolder}/../../../Common"
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],
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"defines": [],
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"compilerPath": "/usr/local/cuda/bin/nvcc",
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"cStandard": "gnu17",
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"cppStandard": "gnu++14",
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"intelliSenseMode": "linux-gcc-x64",
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"configurationProvider": "ms-vscode.makefile-tools"
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}
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],
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"version": 4
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}
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@ -1,7 +0,0 @@
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{
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"recommendations": [
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"nvidia.nsight-vscode-edition",
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"ms-vscode.cpptools",
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"ms-vscode.makefile-tools"
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]
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}
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@ -1,10 +0,0 @@
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{
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"configurations": [
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{
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"name": "CUDA C++: Launch",
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"type": "cuda-gdb",
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"request": "launch",
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"program": "${workspaceFolder}/cppIntegration"
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}
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]
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}
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@ -1,15 +0,0 @@
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{
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"version": "2.0.0",
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"tasks": [
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{
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"label": "sample",
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"type": "shell",
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"command": "make dbg=1",
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"problemMatcher": ["$nvcc"],
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"group": {
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"kind": "build",
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"isDefault": true
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}
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}
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]
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}
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@ -1,363 +0,0 @@
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################################################################################
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# Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions
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# are met:
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# * Redistributions of source code must retain the above copyright
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# notice, this list of conditions and the following disclaimer.
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# * Redistributions in binary form must reproduce the above copyright
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# notice, this list of conditions and the following disclaimer in the
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# documentation and/or other materials provided with the distribution.
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# * Neither the name of NVIDIA CORPORATION nor the names of its
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# contributors may be used to endorse or promote products derived
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# from this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#
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################################################################################
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#
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# Makefile project only supported on Mac OS X and Linux Platforms)
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#
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################################################################################
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# Location of the CUDA Toolkit
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CUDA_PATH ?= /usr/local/cuda
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##############################
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# start deprecated interface #
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##############################
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ifeq ($(x86_64),1)
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$(info WARNING - x86_64 variable has been deprecated)
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$(info WARNING - please use TARGET_ARCH=x86_64 instead)
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TARGET_ARCH ?= x86_64
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endif
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ifeq ($(ARMv7),1)
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$(info WARNING - ARMv7 variable has been deprecated)
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$(info WARNING - please use TARGET_ARCH=armv7l instead)
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TARGET_ARCH ?= armv7l
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endif
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ifeq ($(aarch64),1)
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$(info WARNING - aarch64 variable has been deprecated)
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$(info WARNING - please use TARGET_ARCH=aarch64 instead)
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TARGET_ARCH ?= aarch64
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endif
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ifeq ($(ppc64le),1)
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$(info WARNING - ppc64le variable has been deprecated)
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$(info WARNING - please use TARGET_ARCH=ppc64le instead)
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TARGET_ARCH ?= ppc64le
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endif
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ifneq ($(GCC),)
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$(info WARNING - GCC variable has been deprecated)
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$(info WARNING - please use HOST_COMPILER=$(GCC) instead)
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HOST_COMPILER ?= $(GCC)
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endif
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ifneq ($(abi),)
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$(error ERROR - abi variable has been removed)
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endif
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############################
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# end deprecated interface #
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############################
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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 $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le armv7l))
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ifneq ($(TARGET_ARCH),$(HOST_ARCH))
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ifneq (,$(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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endif
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else
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TARGET_SIZE := $(shell getconf LONG_BIT)
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endif
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else
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$(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 $(CUDA_PATH)/targets/sbsa-linux 2>/dev/null))
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HOST_ARCH := sbsa
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TARGET_ARCH := sbsa
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endif
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endif
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ifneq ($(TARGET_ARCH),$(HOST_ARCH))
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ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-sbsa x86_64-ppc64le))
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$(error ERROR - cross compiling from $(HOST_ARCH) to $(TARGET_ARCH) is not supported!)
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endif
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endif
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# When on native aarch64 system with userspace of 32-bit, change TARGET_ARCH to armv7l
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ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_SIZE),aarch64-aarch64-32)
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TARGET_ARCH = armv7l
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endif
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# operating system
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HOST_OS := $(shell uname -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
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TARGET_OS ?= $(HOST_OS)
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ifeq (,$(filter $(TARGET_OS),linux darwin qnx android))
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$(error ERROR - unsupported value $(TARGET_OS) for TARGET_OS!)
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endif
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# host compiler
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ifdef HOST_COMPILER
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CUSTOM_HOST_COMPILER = 1
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endif
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ifeq ($(TARGET_OS),darwin)
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ifeq ($(shell expr `xcodebuild -version | grep -i xcode | awk '{print $$2}' | cut -d'.' -f1` \>= 5),1)
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HOST_COMPILER ?= clang++
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endif
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else ifneq ($(TARGET_ARCH),$(HOST_ARCH))
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ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
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ifeq ($(TARGET_OS),linux)
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HOST_COMPILER ?= arm-linux-gnueabihf-g++
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else ifeq ($(TARGET_OS),qnx)
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ifeq ($(QNX_HOST),)
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$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
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endif
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ifeq ($(QNX_TARGET),)
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$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
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endif
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export QNX_HOST
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export QNX_TARGET
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HOST_COMPILER ?= $(QNX_HOST)/usr/bin/arm-unknown-nto-qnx6.6.0eabi-g++
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else ifeq ($(TARGET_OS),android)
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HOST_COMPILER ?= arm-linux-androideabi-g++
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endif
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else ifeq ($(TARGET_ARCH),aarch64)
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ifeq ($(TARGET_OS), linux)
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HOST_COMPILER ?= aarch64-linux-gnu-g++
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else ifeq ($(TARGET_OS),qnx)
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ifeq ($(QNX_HOST),)
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$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
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endif
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ifeq ($(QNX_TARGET),)
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$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
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endif
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export QNX_HOST
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export QNX_TARGET
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HOST_COMPILER ?= $(QNX_HOST)/usr/bin/q++
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else ifeq ($(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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endif
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HOST_COMPILER ?= g++
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NVCC := $(CUDA_PATH)/bin/nvcc -ccbin $(HOST_COMPILER)
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# internal flags
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NVCCFLAGS := -m${TARGET_SIZE}
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CCFLAGS :=
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LDFLAGS :=
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# build flags
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# Link flag for customized HOST_COMPILER with gcc realpath
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GCC_PATH := $(shell which gcc)
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ifeq ($(CUSTOM_HOST_COMPILER),1)
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ifneq ($(filter /%,$(HOST_COMPILER)),)
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ifneq ($(findstring gcc,$(HOST_COMPILER)),)
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ifneq ($(GCC_PATH),$(HOST_COMPILER))
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LDFLAGS += -lstdc++
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endif
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endif
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endif
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endif
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ifeq ($(TARGET_OS),darwin)
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LDFLAGS += -rpath $(CUDA_PATH)/lib
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CCFLAGS += -arch $(HOST_ARCH)
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else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
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LDFLAGS += --dynamic-linker=/lib/ld-linux-armhf.so.3
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CCFLAGS += -mfloat-abi=hard
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else ifeq ($(TARGET_OS),android)
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LDFLAGS += -pie
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CCFLAGS += -fpie -fpic -fexceptions
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endif
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ifneq ($(TARGET_ARCH),$(HOST_ARCH))
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ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
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ifneq ($(TARGET_FS),)
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GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
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ifeq ($(GCCVERSIONLTEQ46),1)
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CCFLAGS += --sysroot=$(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
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LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib
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LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
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endif
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endif
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ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
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ifneq ($(TARGET_FS),)
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GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
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ifeq ($(GCCVERSIONLTEQ46),1)
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CCFLAGS += --sysroot=$(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)/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 -I$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include/libdrm
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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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NVCCFLAGS += -D_QNX_SOURCE
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NVCCFLAGS += --qpp-config 8.3.0,gcc_ntoaarch64le
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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 += -L/usr/lib/aarch64-qnx-gnu
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CCFLAGS += "-Wl\,-rpath-link\,/usr/lib/aarch64-qnx-gnu"
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ifdef TARGET_OVERRIDE
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LDFLAGS += -lslog2
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endif
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ifneq ($(TARGET_FS),)
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LDFLAGS += -L$(TARGET_FS)/usr/lib
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CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/lib"
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LDFLAGS += -L$(TARGET_FS)/usr/libnvidia
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CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/libnvidia"
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CCFLAGS += -I$(TARGET_FS)/../include
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endif
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endif
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endif
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ifdef TARGET_OVERRIDE # cuda toolkit targets override
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NVCCFLAGS += -target-dir $(TARGET_OVERRIDE)
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endif
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# Install directory of different arch
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CUDA_INSTALL_TARGET_DIR :=
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ifeq ($(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)-$(TARGET_OS),aarch64-android)
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CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux-androideabi/
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else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-qnx)
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CUDA_INSTALL_TARGET_DIR = targets/ARMv7-linux-QNX/
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else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
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CUDA_INSTALL_TARGET_DIR = targets/aarch64-qnx/
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else ifeq ($(TARGET_ARCH),ppc64le)
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CUDA_INSTALL_TARGET_DIR = targets/ppc64le-linux/
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endif
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# Debug build flags
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ifeq ($(dbg),1)
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NVCCFLAGS += -g -G
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BUILD_TYPE := debug
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else
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BUILD_TYPE := release
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endif
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ALL_CCFLAGS :=
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ALL_CCFLAGS += $(NVCCFLAGS)
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ALL_CCFLAGS += $(EXTRA_NVCCFLAGS)
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ALL_CCFLAGS += $(addprefix -Xcompiler ,$(CCFLAGS))
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ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
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SAMPLE_ENABLED := 1
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ALL_LDFLAGS :=
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ALL_LDFLAGS += $(ALL_CCFLAGS)
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ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
|
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ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
|
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|
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# Common includes and paths for CUDA
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INCLUDES := -I../../../Common
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LIBRARIES :=
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################################################################################
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# Gencode arguments
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ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64 sbsa))
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||||
SMS ?= 53 61 70 72 75 80 86 87 90
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else
|
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SMS ?= 50 52 60 61 70 75 80 86 89 90
|
||||
endif
|
||||
|
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ifeq ($(SMS),)
|
||||
$(info >>> WARNING - no SM architectures have been specified - waiving sample <<<)
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SAMPLE_ENABLED := 0
|
||||
endif
|
||||
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ifeq ($(GENCODE_FLAGS),)
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# Generate SASS code for each SM architecture listed in $(SMS)
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$(foreach sm,$(SMS),$(eval GENCODE_FLAGS += -gencode arch=compute_$(sm),code=sm_$(sm)))
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|
||||
# Generate PTX code from the highest SM architecture in $(SMS) to guarantee forward-compatibility
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HIGHEST_SM := $(lastword $(sort $(SMS)))
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ifneq ($(HIGHEST_SM),)
|
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GENCODE_FLAGS += -gencode arch=compute_$(HIGHEST_SM),code=compute_$(HIGHEST_SM)
|
||||
endif
|
||||
endif
|
||||
|
||||
ALL_CCFLAGS += --threads 0 --std=c++11
|
||||
|
||||
ifeq ($(SAMPLE_ENABLED),0)
|
||||
EXEC ?= @echo "[@]"
|
||||
endif
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################################################################################
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# Target rules
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all: build
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build: cppIntegration
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||||
check.deps:
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ifeq ($(SAMPLE_ENABLED),0)
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||||
@echo "Sample will be waived due to the above missing dependencies"
|
||||
else
|
||||
@echo "Sample is ready - all dependencies have been met"
|
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endif
|
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|
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cppIntegration.o:cppIntegration.cu
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$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
|
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|
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cppIntegration_gold.o:cppIntegration_gold.cpp
|
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$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
|
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|
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main.o:main.cpp
|
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$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
|
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|
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cppIntegration: cppIntegration.o cppIntegration_gold.o main.o
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$(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)
|
||||
|
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run: build
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||||
$(EXEC) ./cppIntegration
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||||
|
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testrun: build
|
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|
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clean:
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rm -f cppIntegration cppIntegration.o cppIntegration_gold.o main.o
|
||||
rm -rf ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/cppIntegration
|
||||
|
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clobber: clean
|
||||
@ -1,72 +0,0 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
|
||||
<entry>
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||||
<name>cppIntegration</name>
|
||||
<cuda_api_list>
|
||||
<toolkit>cudaMalloc</toolkit>
|
||||
<toolkit>cudaMemcpy</toolkit>
|
||||
<toolkit>cudaFree</toolkit>
|
||||
</cuda_api_list>
|
||||
<description><![CDATA[This example demonstrates how to integrate CUDA into an existing C++ application, i.e. the CUDA entry point on host side is only a function which is called from C++ code and only the file containing this function is compiled with nvcc. It also demonstrates that vector types can be used from cpp.]]></description>
|
||||
<devicecompilation>whole</devicecompilation>
|
||||
<includepaths>
|
||||
<path>./</path>
|
||||
<path>../</path>
|
||||
<path>../../../Common</path>
|
||||
</includepaths>
|
||||
<keyconcepts>
|
||||
<concept level="basic">CPP-CUDA Integration</concept>
|
||||
</keyconcepts>
|
||||
<keywords>
|
||||
</keywords>
|
||||
<libraries>
|
||||
</libraries>
|
||||
<librarypaths>
|
||||
</librarypaths>
|
||||
<nsight_eclipse>true</nsight_eclipse>
|
||||
<primary_file>cppIntegration.cu</primary_file>
|
||||
<scopes>
|
||||
<scope>1:CUDA Basic Topics</scope>
|
||||
</scopes>
|
||||
<sm-arch>sm50</sm-arch>
|
||||
<sm-arch>sm52</sm-arch>
|
||||
<sm-arch>sm53</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>
|
||||
<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>x86_64</arch>
|
||||
<platform>macosx</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>
|
||||
<include>all</include>
|
||||
</supported_sm_architectures>
|
||||
<title>C++ Integration</title>
|
||||
<type>exe</type>
|
||||
</entry>
|
||||
@ -1,70 +0,0 @@
|
||||
# cppIntegration - C++ Integration
|
||||
|
||||
## Description
|
||||
|
||||
This example demonstrates how to integrate CUDA into an existing C++ application, i.e. the CUDA entry point on host side is only a function which is called from C++ code and only the file containing this function is compiled with nvcc. It also demonstrates that vector types can be used from cpp.
|
||||
|
||||
## Key Concepts
|
||||
|
||||
CPP-CUDA Integration
|
||||
|
||||
## Supported SM Architectures
|
||||
|
||||
[SM 5.0 ](https://developer.nvidia.com/cuda-gpus) [SM 5.2 ](https://developer.nvidia.com/cuda-gpus) [SM 5.3 ](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) [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)
|
||||
cudaMalloc, cudaMemcpy, cudaFree
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Download and install the [CUDA Toolkit 12.5](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)
|
||||
|
||||
@ -1,172 +0,0 @@
|
||||
/* 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.
|
||||
*/
|
||||
|
||||
/*
|
||||
* Example of integrating CUDA functions into an existing
|
||||
* application / framework.
|
||||
* Host part of the device code.
|
||||
* Compiled with Cuda compiler.
|
||||
*/
|
||||
|
||||
// System includes
|
||||
#include <stdlib.h>
|
||||
#include <stdio.h>
|
||||
#include <string.h>
|
||||
#include <math.h>
|
||||
#include <assert.h>
|
||||
|
||||
// CUDA runtime
|
||||
#include <cuda_runtime.h>
|
||||
|
||||
// helper functions and utilities to work with CUDA
|
||||
#include <helper_cuda.h>
|
||||
#include <helper_functions.h>
|
||||
|
||||
#ifndef MAX
|
||||
#define MAX(a, b) (a > b ? a : b)
|
||||
#endif
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
// declaration, forward
|
||||
|
||||
extern "C" void computeGold(char *reference, char *idata,
|
||||
const unsigned int len);
|
||||
extern "C" void computeGold2(int2 *reference, int2 *idata,
|
||||
const unsigned int len);
|
||||
|
||||
///////////////////////////////////////////////////////////////////////////////
|
||||
//! Simple test kernel for device functionality
|
||||
//! @param g_odata memory to process (in and out)
|
||||
///////////////////////////////////////////////////////////////////////////////
|
||||
__global__ void kernel(int *g_data) {
|
||||
// write data to global memory
|
||||
const unsigned int tid = threadIdx.x;
|
||||
int data = g_data[tid];
|
||||
|
||||
// use integer arithmetic to process all four bytes with one thread
|
||||
// this serializes the execution, but is the simplest solutions to avoid
|
||||
// bank conflicts for this very low number of threads
|
||||
// in general it is more efficient to process each byte by a separate thread,
|
||||
// to avoid bank conflicts the access pattern should be
|
||||
// g_data[4 * wtid + wid], where wtid is the thread id within the half warp
|
||||
// and wid is the warp id
|
||||
// see also the programming guide for a more in depth discussion.
|
||||
g_data[tid] =
|
||||
((((data << 0) >> 24) - 10) << 24) | ((((data << 8) >> 24) - 10) << 16) |
|
||||
((((data << 16) >> 24) - 10) << 8) | ((((data << 24) >> 24) - 10) << 0);
|
||||
}
|
||||
|
||||
///////////////////////////////////////////////////////////////////////////////
|
||||
//! Demonstration that int2 data can be used in the cpp code
|
||||
//! @param g_odata memory to process (in and out)
|
||||
///////////////////////////////////////////////////////////////////////////////
|
||||
__global__ void kernel2(int2 *g_data) {
|
||||
// write data to global memory
|
||||
const unsigned int tid = threadIdx.x;
|
||||
int2 data = g_data[tid];
|
||||
|
||||
// use integer arithmetic to process all four bytes with one thread
|
||||
// this serializes the execution, but is the simplest solutions to avoid
|
||||
// bank conflicts for this very low number of threads
|
||||
// in general it is more efficient to process each byte by a separate thread,
|
||||
// to avoid bank conflicts the access pattern should be
|
||||
// g_data[4 * wtid + wid], where wtid is the thread id within the half warp
|
||||
// and wid is the warp id
|
||||
// see also the programming guide for a more in depth discussion.
|
||||
g_data[tid].x = data.x - data.y;
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
//! Entry point for Cuda functionality on host side
|
||||
//! @param argc command line argument count
|
||||
//! @param argv command line arguments
|
||||
//! @param data data to process on the device
|
||||
//! @param len len of \a data
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
extern "C" bool runTest(const int argc, const char **argv, char *data,
|
||||
int2 *data_int2, unsigned int len) {
|
||||
// use command-line specified CUDA device, otherwise use device with highest
|
||||
// Gflops/s
|
||||
findCudaDevice(argc, (const char **)argv);
|
||||
|
||||
const unsigned int num_threads = len / 4;
|
||||
assert(0 == (len % 4));
|
||||
const unsigned int mem_size = sizeof(char) * len;
|
||||
const unsigned int mem_size_int2 = sizeof(int2) * len;
|
||||
|
||||
// allocate device memory
|
||||
char *d_data;
|
||||
checkCudaErrors(cudaMalloc((void **)&d_data, mem_size));
|
||||
// copy host memory to device
|
||||
checkCudaErrors(cudaMemcpy(d_data, data, mem_size, cudaMemcpyHostToDevice));
|
||||
// allocate device memory for int2 version
|
||||
int2 *d_data_int2;
|
||||
checkCudaErrors(cudaMalloc((void **)&d_data_int2, mem_size_int2));
|
||||
// copy host memory to device
|
||||
checkCudaErrors(cudaMemcpy(d_data_int2, data_int2, mem_size_int2,
|
||||
cudaMemcpyHostToDevice));
|
||||
|
||||
// setup execution parameters
|
||||
dim3 grid(1, 1, 1);
|
||||
dim3 threads(num_threads, 1, 1);
|
||||
dim3 threads2(len, 1, 1); // more threads needed fir separate int2 version
|
||||
// execute the kernel
|
||||
kernel<<<grid, threads>>>((int *)d_data);
|
||||
kernel2<<<grid, threads2>>>(d_data_int2);
|
||||
|
||||
// check if kernel execution generated and error
|
||||
getLastCudaError("Kernel execution failed");
|
||||
|
||||
// compute reference solutions
|
||||
char *reference = (char *)malloc(mem_size);
|
||||
computeGold(reference, data, len);
|
||||
int2 *reference2 = (int2 *)malloc(mem_size_int2);
|
||||
computeGold2(reference2, data_int2, len);
|
||||
|
||||
// copy results from device to host
|
||||
checkCudaErrors(cudaMemcpy(data, d_data, mem_size, cudaMemcpyDeviceToHost));
|
||||
checkCudaErrors(cudaMemcpy(data_int2, d_data_int2, mem_size_int2,
|
||||
cudaMemcpyDeviceToHost));
|
||||
|
||||
// check result
|
||||
bool success = true;
|
||||
|
||||
for (unsigned int i = 0; i < len; i++) {
|
||||
if (reference[i] != data[i] || reference2[i].x != data_int2[i].x ||
|
||||
reference2[i].y != data_int2[i].y) {
|
||||
success = false;
|
||||
}
|
||||
}
|
||||
|
||||
// cleanup memory
|
||||
checkCudaErrors(cudaFree(d_data));
|
||||
checkCudaErrors(cudaFree(d_data_int2));
|
||||
free(reference);
|
||||
free(reference2);
|
||||
|
||||
return success;
|
||||
}
|
||||
@ -1,67 +0,0 @@
|
||||
/* 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.
|
||||
*/
|
||||
|
||||
/*
|
||||
* Example of integrating CUDA functions into an existing
|
||||
* application / framework.
|
||||
* Reference solution computation.
|
||||
*/
|
||||
|
||||
// Required header to support CUDA vector types
|
||||
#include <vector_types.h>
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
// export C interface
|
||||
extern "C" void computeGold(char *reference, char *idata,
|
||||
const unsigned int len);
|
||||
extern "C" void computeGold2(int2 *reference, int2 *idata,
|
||||
const unsigned int len);
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
//! Compute reference data set
|
||||
//! Each element is multiplied with the number of threads / array length
|
||||
//! @param reference reference data, computed but preallocated
|
||||
//! @param idata input data as provided to device
|
||||
//! @param len number of elements in reference / idata
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
void computeGold(char *reference, char *idata, const unsigned int len) {
|
||||
for (unsigned int i = 0; i < len; ++i) reference[i] = idata[i] - 10;
|
||||
}
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
//! Compute reference data set for int2 version
|
||||
//! Each element is multiplied with the number of threads / array length
|
||||
//! @param reference reference data, computed but preallocated
|
||||
//! @param idata input data as provided to device
|
||||
//! @param len number of elements in reference / idata
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
void computeGold2(int2 *reference, int2 *idata, const unsigned int len) {
|
||||
for (unsigned int i = 0; i < len; ++i) {
|
||||
reference[i].x = idata[i].x - idata[i].y;
|
||||
reference[i].y = idata[i].y;
|
||||
}
|
||||
}
|
||||
@ -1,86 +0,0 @@
|
||||
/* 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.
|
||||
*/
|
||||
|
||||
/*
|
||||
* Example of integrating CUDA functions into an existing
|
||||
* application / framework.
|
||||
* CPP code representing the existing application / framework.
|
||||
* Compiled with default CPP compiler.
|
||||
*/
|
||||
|
||||
// includes, system
|
||||
#include <iostream>
|
||||
#include <stdlib.h>
|
||||
|
||||
// Required to include CUDA vector types
|
||||
#include <cuda_runtime.h>
|
||||
#include <vector_types.h>
|
||||
#include <helper_cuda.h>
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
// declaration, forward
|
||||
extern "C" bool runTest(const int argc, const char **argv, char *data,
|
||||
int2 *data_int2, unsigned int len);
|
||||
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
// Program main
|
||||
////////////////////////////////////////////////////////////////////////////////
|
||||
int main(int argc, char **argv) {
|
||||
// input data
|
||||
int len = 16;
|
||||
// the data has some zero padding at the end so that the size is a multiple of
|
||||
// four, this simplifies the processing as each thread can process four
|
||||
// elements (which is necessary to avoid bank conflicts) but no branching is
|
||||
// necessary to avoid out of bounds reads
|
||||
char str[] = {82, 111, 118, 118, 121, 42, 97, 121,
|
||||
124, 118, 110, 56, 10, 10, 10, 10};
|
||||
|
||||
// Use int2 showing that CUDA vector types can be used in cpp code
|
||||
int2 i2[16];
|
||||
|
||||
for (int i = 0; i < len; i++) {
|
||||
i2[i].x = str[i];
|
||||
i2[i].y = 10;
|
||||
}
|
||||
|
||||
bool bTestResult;
|
||||
|
||||
// run the device part of the program
|
||||
bTestResult = runTest(argc, (const char **)argv, str, i2, len);
|
||||
|
||||
std::cout << str << std::endl;
|
||||
|
||||
char str_device[16];
|
||||
|
||||
for (int i = 0; i < len; i++) {
|
||||
str_device[i] = (char)(i2[i].x);
|
||||
}
|
||||
|
||||
std::cout << str_device << std::endl;
|
||||
|
||||
exit(bTestResult ? EXIT_SUCCESS : EXIT_FAILURE);
|
||||
}
|
||||
Loading…
x
Reference in New Issue
Block a user