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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Samples/dwtHaar1D/.vscode/launch.json vendored Normal file
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{
"configurations": [
{
"name": "CUDA C++: Launch",
"type": "cuda-gdb",
"request": "launch",
"program": "${workspaceFolder}/dwtHaar1D"
}
]
}

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

337
Samples/dwtHaar1D/Makefile Normal file
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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
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
# Common includes and paths for CUDA
INCLUDES := -I../../Common
LIBRARIES :=
################################################################################
# Gencode arguments
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64))
SMS ?= 35 37 50 52 60 61 70 72 75 80 86
else
SMS ?= 35 37 50 52 60 61 70 75 80 86
endif
ifeq ($(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 ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: dwtHaar1D
check.deps:
ifeq ($(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
dwtHaar1D.o:dwtHaar1D.cu
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
dwtHaar1D: dwtHaar1D.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
$(EXEC) ./dwtHaar1D
clean:
rm -f dwtHaar1D dwtHaar1D.o
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/dwtHaar1D
clobber: clean

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>dwtHaar1D</name>
<description><![CDATA[Discrete Haar wavelet decomposition for 1D signals with a length which is a power of 2.]]></description>
<devicecompilation>whole</devicecompilation>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../Common</path>
</includepaths>
<keyconcepts>
<concept level="advanced">Image Processing</concept>
<concept level="advanced">Video Compression</concept>
</keyconcepts>
<keywords>
</keywords>
<libraries>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>dwtHaar1D.cu</primary_file>
<scopes>
<scope>1:CUDA Advanced Topics</scope>
<scope>2:Image Processing</scope>
<scope>2:Data Compression</scope>
<scope>2:Video Codecs</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>
<env>
<arch>ppc64le</arch>
<platform>linux</platform>
</env>
</supported_envs>
<supported_sm_architectures>
<include>all</include>
</supported_sm_architectures>
<title>1D Discrete Haar Wavelet Decomposition</title>
<type>exe</type>
</entry>

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# dwtHaar1D - 1D Discrete Haar Wavelet Decomposition
## Description
Discrete Haar wavelet decomposition for 1D signals with a length which is a power of 2.
## Key Concepts
Image Processing, Video Compression
## 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, ppc64le, armv7l
## CUDA APIs involved
## Prerequisites
Download and install the [CUDA Toolkit 11.5](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)

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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.
*/
/*
* 1D DWT for Haar wavelet and signals with a length which is a power of 2.
* The code reduces bank conflicts and non-coalesced reads / writes as
* appropriate but does not fully remove them because the computational
* overhead to achieve this would outweighs the benefit (see inline comments
* for more details).
* Large signals are subdivided into sub-signals with 512 elements and the
* wavelet transform for these is computed with one block over 10 decomposition
* levels. The resulting signal consisting of the approximation coefficients at
* level X is then processed in a subsequent step on the device. This requires
* interblock synchronization which is only possible on host side.
* Detail coefficients which have been computed are not further referenced
* during the decomposition so that they can be stored directly in their final
* position in global memory. The transform and its storing scheme preserve
* locality in the coefficients so that these writes are coalesced.
* Approximation coefficients are stored in shared memory because they are
* needed to compute the subsequent decomposition step. The top most
* approximation coefficient for a sub-signal processed by one block is stored
* in a special global memory location to simplify the processing after the
* interblock synchronization.
* Most books on wavelets explain the Haar wavelet decomposition. A good freely
* available resource is the Wavelet primer by Stollnitz et al.
* http://grail.cs.washington.edu/projects/wavelets/article/wavelet1.pdf
* http://grail.cs.washington.edu/projects/wavelets/article/wavelet2.pdf
* The basic of all Wavelet transforms is to decompose a signal into
* approximation (a) and detail (d) coefficients where the detail tends to be
* small or zero which allows / simplifies compression. The following "graphs"
* demonstrate the transform for a signal
* of length eight. The index always describes the decomposition level where
* a coefficient arises. The input signal is interpreted as approximation signal
* at level 0. The coefficients computed on the device are stored in the same
* scheme as in the example. This data structure is particularly well suited for
* compression and also preserves the hierarchical structure of the
decomposition.
-------------------------------------------------
| a_0 | a_0 | a_0 | a_0 | a_0 | a_0 | a_0 | a_0 |
-------------------------------------------------
-------------------------------------------------
| a_1 | a_1 | a_1 | a_1 | d_1 | d_1 | d_1 | d_1 |
-------------------------------------------------
-------------------------------------------------
| a_2 | a_2 | d_2 | d_2 | d_1 | d_1 | d_1 | d_1 |
-------------------------------------------------
-------------------------------------------------
| a_3 | d_3 | d_2 | d_2 | d_1 | d_1 | d_1 | d_1 |
-------------------------------------------------
* Host code.
*/
#ifdef _WIN32
#define NOMINMAX
#endif
// includes, system
#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <math.h>
#include <assert.h>
// includes, project
#include <helper_functions.h>
#include <helper_cuda.h>
// constants which are used in host and device code
#define INV_SQRT_2 0.70710678118654752440f;
const unsigned int LOG_NUM_BANKS = 4;
const unsigned int NUM_BANKS = 16;
////////////////////////////////////////////////////////////////////////////////
// includes, kernels
#include "dwtHaar1D_kernel.cuh"
////////////////////////////////////////////////////////////////////////////////
// declaration, forward
void runTest(int argc, char **argv);
bool getLevels(unsigned int len, unsigned int *levels);
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int main(int argc, char **argv) {
// run test
runTest(argc, argv);
}
////////////////////////////////////////////////////////////////////////////////
//! Perform the wavelet decomposition
////////////////////////////////////////////////////////////////////////////////
void runTest(int argc, char **argv) {
bool bResult = false; // flag for final validation of the results
char *s_fname = NULL, *r_gold_fname = NULL;
char r_fname[256];
const char usage[] = {
"\nUsage:\n"
" dwtHaar1D --signal=<signal_file> --result=<result_file> "
"--gold=<gold_file>\n\n"
" <signal_file> Input file containing the signal\n"
" <result_file> Output file storing the result of the wavelet "
"decomposition\n"
" <gold_file> Input file containing the reference result of the "
"wavelet decomposition\n"
"\nExample:\n"
" ./dwtHaar1D\n"
" --signal=signal.dat\n"
" --result=result.dat\n"
" --gold=regression.gold.dat\n"};
printf("%s Starting...\n\n", argv[0]);
// use command-line specified CUDA device, otherwise use device with highest
// Gflops/s
findCudaDevice(argc, (const char **)argv);
// file names, either specified as cmd line args or use default
if (argc == 4) {
char *tmp_sfname, *tmp_rfname, *tmp_goldfname;
if ((getCmdLineArgumentString(argc, (const char **)argv, "signal",
&tmp_sfname) != true) ||
(getCmdLineArgumentString(argc, (const char **)argv, "result",
&tmp_rfname) != true) ||
(getCmdLineArgumentString(argc, (const char **)argv, "gold",
&tmp_goldfname) != true)) {
fprintf(stderr, "Invalid input syntax.\n%s", usage);
exit(EXIT_FAILURE);
}
s_fname = sdkFindFilePath(tmp_sfname, argv[0]);
r_gold_fname = sdkFindFilePath(tmp_goldfname, argv[0]);
strcpy(r_fname, tmp_rfname);
} else {
s_fname = sdkFindFilePath("signal.dat", argv[0]);
r_gold_fname = sdkFindFilePath("regression.gold.dat", argv[0]);
strcpy(r_fname, "result.dat");
}
printf("source file = \"%s\"\n", s_fname);
printf("reference file = \"%s\"\n", r_fname);
printf("gold file = \"%s\"\n", r_gold_fname);
// read in signal
unsigned int slength = 0;
float *signal = NULL;
if (s_fname == NULL) {
fprintf(stderr, "Cannot find the file containing the signal.\n%s", usage);
exit(EXIT_FAILURE);
}
if (sdkReadFile(s_fname, &signal, &slength, false) == true) {
printf("Reading signal from \"%s\"\n", s_fname);
} else {
exit(EXIT_FAILURE);
}
// get the number of decompositions necessary to perform a full decomposition
unsigned int dlevels_complete = 0;
if (true != getLevels(slength, &dlevels_complete)) {
// error message
fprintf(stderr, "Signal length not supported.\n");
// cleanup and abort
free(signal);
exit(EXIT_FAILURE);
}
// device in data
float *d_idata = NULL;
// device out data
float *d_odata = NULL;
// device approx_final data
float *approx_final = NULL;
// The very final approximation coefficient has to be written to the output
// data, all others are reused as input data in the next global step and
// therefore have to be written to the input data again.
// The following flag indicates where to copy approx_final data
// - 0 is input, 1 is output
int approx_is_input;
// allocate device mem
const unsigned int smem_size = sizeof(float) * slength;
checkCudaErrors(cudaMalloc((void **)&d_idata, smem_size));
checkCudaErrors(cudaMalloc((void **)&d_odata, smem_size));
checkCudaErrors(cudaMalloc((void **)&approx_final, smem_size));
// copy input data to device
checkCudaErrors(
cudaMemcpy(d_idata, signal, smem_size, cudaMemcpyHostToDevice));
// total number of threads
// in the first decomposition step always one thread computes the average and
// detail signal for one pair of adjacent values
unsigned int num_threads_total_left = slength / 2;
// decomposition levels performed in the current / next step
unsigned int dlevels_step = dlevels_complete;
// 1D signal so the arrangement of elements is also 1D
dim3 block_size;
dim3 grid_size;
// number of decomposition levels left after one iteration on the device
unsigned int dlevels_left = dlevels_complete;
// if less or equal 1k elements, then the data can be processed in one block,
// this avoids the Wait-For-Idle (WFI) on host side which is necessary if the
// computation is split across multiple SM's if enough input data
if (dlevels_complete <= 10) {
// decomposition can be performed at once
block_size.x = num_threads_total_left;
approx_is_input = 0;
} else {
// 512 threads per block
grid_size.x = (num_threads_total_left / 512);
block_size.x = 512;
// 512 threads corresponds to 10 decomposition steps
dlevels_step = 10;
dlevels_left -= 10;
approx_is_input = 1;
}
// Initialize d_odata to 0.0f
initValue<<<grid_size, block_size>>>(d_odata, 0.0f);
// do until full decomposition is accomplished
while (0 != num_threads_total_left) {
// double the number of threads as bytes
unsigned int mem_shared = (2 * block_size.x) * sizeof(float);
// extra memory requirements to avoid bank conflicts
mem_shared += ((2 * block_size.x) / NUM_BANKS) * sizeof(float);
// run kernel
dwtHaar1D<<<grid_size, block_size, mem_shared>>>(
d_idata, d_odata, approx_final, dlevels_step, num_threads_total_left,
block_size.x);
// Copy approx_final to appropriate location
if (approx_is_input) {
checkCudaErrors(cudaMemcpy(d_idata, approx_final, grid_size.x * 4,
cudaMemcpyDeviceToDevice));
} else {
checkCudaErrors(cudaMemcpy(d_odata, approx_final, grid_size.x * 4,
cudaMemcpyDeviceToDevice));
}
// update level variables
if (dlevels_left < 10) {
// approx_final = d_odata;
approx_is_input = 0;
}
// more global steps necessary
dlevels_step = (dlevels_left > 10) ? dlevels_left - 10 : dlevels_left;
dlevels_left -= 10;
// after each step only half the threads are used any longer
// therefore after 10 steps 2^10 less threads
num_threads_total_left = num_threads_total_left >> 10;
// update block and grid size
grid_size.x =
(num_threads_total_left / 512) + (0 != (num_threads_total_left % 512))
? 1
: 0;
if (grid_size.x <= 1) {
block_size.x = num_threads_total_left;
}
}
// get the result back from the server
// allocate mem for the result
float *odata = (float *)malloc(smem_size);
checkCudaErrors(
cudaMemcpy(odata, d_odata, smem_size, cudaMemcpyDeviceToHost));
// post processing
// write file for regression test
if (r_fname == NULL) {
fprintf(stderr,
"Cannot write the output file storing the result of the wavelet "
"decomposition.\n%s",
usage);
exit(EXIT_FAILURE);
}
if (sdkWriteFile(r_fname, odata, slength, 0.001f, false) == true) {
printf("Writing result to \"%s\"\n", r_fname);
} else {
exit(EXIT_FAILURE);
}
// load the reference solution
unsigned int len_reference = 0;
float *reference = NULL;
if (r_gold_fname == NULL) {
fprintf(stderr,
"Cannot read the file containing the reference result of the "
"wavelet decomposition.\n%s",
usage);
exit(EXIT_FAILURE);
}
if (sdkReadFile(r_gold_fname, &reference, &len_reference, false) == true) {
printf("Reading reference result from \"%s\"\n", r_gold_fname);
} else {
exit(EXIT_FAILURE);
}
assert(slength == len_reference);
// compare the computed solution and the reference
bResult = (bool)sdkCompareL2fe(reference, odata, slength, 0.001f);
free(reference);
// free allocated host and device memory
checkCudaErrors(cudaFree(d_odata));
checkCudaErrors(cudaFree(d_idata));
checkCudaErrors(cudaFree(approx_final));
free(signal);
free(odata);
free(s_fname);
free(r_gold_fname);
printf(bResult ? "Test success!\n" : "Test failure!\n");
}
////////////////////////////////////////////////////////////////////////////////
//! Get number of decomposition levels to perform a full decomposition
//! Also check if the input signal size is suitable
//! @return true if the number of decomposition levels could be determined
//! and the signal length is supported by the implementation,
//! otherwise false
//! @param len length of input signal
//! @param levels number of decomposition levels necessary to perform a full
//! decomposition
////////////////////////////////////////////////////////////////////////////////
bool getLevels(unsigned int len, unsigned int *levels) {
bool retval = false;
// currently signals up to a length of 2^20 supported
for (unsigned int i = 0; i < 20; ++i) {
if (len == (1 << i)) {
*levels = i;
retval = true;
break;
}
}
return retval;
}

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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.
*/
/*
* 1D DWT for Haar wavelet and signals with a length which is a power of 2.
* The code reduces bank conflicts and non-coalesced reads / writes as
* appropriate but does not fully remove them because the computational
* overhead to achieve this would outweighs the benefit (see inline comments
* for more details).
* Large signals are subdivided into sub-signals with 512 elements and the
* wavelet transform for these is computed with one block over 10 decomposition
* levels. The resulting signal consisting of the approximation coefficients at
* level X is then processed in a subsequent step on the device. This requires
* interblock synchronization which is only possible on host side.
* Detail coefficients which have been computed are not further referenced
* during the decomposition so that they can be stored directly in their final
* position in global memory. The transform and its storing scheme preserve
* locality in the coefficients so that these writes are coalesced.
* Approximation coefficients are stored in shared memory because they are
* needed to compute the subsequent decomposition step. The top most
* approximation coefficient for a sub-signal processed by one block is stored
* in a special global memory location to simplify the processing after the
* interblock synchronization.
* Most books on wavelets explain the Haar wavelet decomposition. A good freely
* available resource is the Wavelet primer by Stollnitz et al.
* http://grail.cs.washington.edu/projects/wavelets/article/wavelet1.pdf
* http://grail.cs.washington.edu/projects/wavelets/article/wavelet2.pdf
* The basic of all Wavelet transforms is to decompose a signal into
* approximation (a) and detail (d) coefficients where the detail tends to be
* small or zero which allows / simplifies compression. The following "graphs"
* demonstrate the transform for a signal
* of length eight. The index always describes the decomposition level where
* a coefficient arises. The input signal is interpreted as approximation signal
* at level 0. The coefficients computed on the device are stored in the same
* scheme as in the example. This data structure is particularly well suited for
* compression and also preserves the hierarchical structure of the
decomposition.
-------------------------------------------------
| a_0 | a_0 | a_0 | a_0 | a_0 | a_0 | a_0 | a_0 |
-------------------------------------------------
-------------------------------------------------
| a_1 | a_1 | a_1 | a_1 | d_1 | d_1 | d_1 | d_1 |
-------------------------------------------------
-------------------------------------------------
| a_2 | a_2 | d_2 | d_2 | d_1 | d_1 | d_1 | d_1 |
-------------------------------------------------
-------------------------------------------------
| a_3 | d_3 | d_2 | d_2 | d_1 | d_1 | d_1 | d_1 |
-------------------------------------------------
* Device Code.
*/
#ifndef _DWTHAAR1D_KERNEL_H_
#define _DWTHAAR1D_KERNEL_H_
#include <cooperative_groups.h>
namespace cg = cooperative_groups;
////////////////////////////////////////////////////////////////////////////////
//! @param id input data
//! @param od output data
//! @param value
////////////////////////////////////////////////////////////////////////////////
__global__ void initValue(float *od, float value) {
// Handle to thread block group
cg::thread_block cta = cg::this_thread_block();
// position of write into global memory
unsigned int index = (blockIdx.x * blockDim.x) + threadIdx.x;
od[index] = value;
// sync after each decomposition step
cg::sync(cta);
}
////////////////////////////////////////////////////////////////////////////////
//! Compute partial wavelet decomposition on the GPU using Haar basis
//! For each thread block the full decomposition is computed but these results
//! have to be combined
//! Use one thread to perform the full decomposition
//! @param id input data
//! @param od output data
//! @param approx_final place to store the final approximation coefficient for
//! the subsignal
//! @param dlevels number of decomposition levels for this transform
//! @param slength_step_half half signal length for current decomposition
//! level (offset for storing detail coefficients in
//! global memory
//! @param bdim block dimension
////////////////////////////////////////////////////////////////////////////////
__global__ void dwtHaar1D(float *id, float *od, float *approx_final,
const unsigned int dlevels,
const unsigned int slength_step_half,
const int bdim) {
// Handle to thread block group
cg::thread_block cta = cg::this_thread_block();
// shared memory for part of the signal
extern __shared__ float shared[];
// thread runtime environment, 1D parametrization
const int gdim = gridDim.x;
// const int bdim = blockDim.x;
const int bid = blockIdx.x;
const int tid = threadIdx.x;
// global thread id (w.r.t. to total data set)
const int tid_global = (bid * bdim) + tid;
unsigned int idata = (bid * (2 * bdim)) + tid;
// read data from global memory
shared[tid] = id[idata];
shared[tid + bdim] = id[idata + bdim];
cg::sync(cta);
// this operation has a two way bank conflicts for all threads, this are two
// additional cycles for each warp -- all alternatives to avoid this bank
// conflict are more expensive than the one cycle introduced by serialization
float data0 = shared[2 * tid];
float data1 = shared[(2 * tid) + 1];
cg::sync(cta);
// detail coefficient, not further referenced so directly store in
// global memory
od[tid_global + slength_step_half] = (data0 - data1) * INV_SQRT_2;
// offset to avoid bank conflicts
// see the scan example for a more detailed description
unsigned int atid = tid + (tid >> LOG_NUM_BANKS);
// approximation coefficient
// store in shared memory for further decomposition steps in this global step
shared[atid] = (data0 + data1) * INV_SQRT_2;
// all threads have to write approximation coefficient to shared memory before
// next steps can take place
cg::sync(cta);
// early out if possible
// the compiler removes this part from the source because dlevels is
// a constant shader input
// note: syncthreads in bodies of branches can lead to dead-locks unless
// the condition evaluates the same way for ALL threads of a block, as in
// this case
if (dlevels > 1) {
// offset to second element in shared element which has to be used for the
// decomposition, effectively 2^(i - 1)
unsigned int offset_neighbor = 1;
// number of active threads per decomposition level
// identical to the offset for the detail coefficients
unsigned int num_threads = bdim >> 1;
// index for the first element of the pair to process
// the representation is still compact (and therefore still tid * 2)
// because the first step operated on registers and only the result has been
// written to shared memory
unsigned int idata0 = tid * 2;
// offset levels to make the loop more efficient
for (unsigned int i = 1; i < dlevels; ++i) {
// Non-coalesced writes occur if the number of active threads becomes
// less than 16 for a block because the start address for the first
// block is not always aligned with 64 byte which is necessary for
// coalesced access. However, the problem only occurs at high levels
// with only a small number of active threads so that the total number of
// non-coalesced access is rather small and does not justify the
// computations which are necessary to avoid these uncoalesced writes
// (this has been tested and verified)
if (tid < num_threads) {
// update stride, with each decomposition level the stride grows by a
// factor of 2
unsigned int idata1 = idata0 + offset_neighbor;
// position of write into global memory
unsigned int g_wpos = (num_threads * gdim) + (bid * num_threads) + tid;
// compute wavelet decomposition step
// offset to avoid bank conflicts
unsigned int c_idata0 = idata0 + (idata0 >> LOG_NUM_BANKS);
unsigned int c_idata1 = idata1 + (idata1 >> LOG_NUM_BANKS);
// detail coefficient, not further modified so directly store
// in global memory
od[g_wpos] = (shared[c_idata0] - shared[c_idata1]) * INV_SQRT_2;
// approximation coefficient
// note that the representation in shared memory becomes rather sparse
// (with a lot of holes inbetween) but the storing scheme in global
// memory guarantees that the common representation (approx, detail_0,
// detail_1, ...)
// is achieved
shared[c_idata0] = (shared[c_idata0] + shared[c_idata1]) * INV_SQRT_2;
// update storage offset for details
num_threads = num_threads >> 1; // div 2
offset_neighbor <<= 1; // mul 2
idata0 = idata0 << 1; // mul 2
}
// sync after each decomposition step
cg::sync(cta);
}
// write the top most level element for the next decomposition steps
// which are performed after an interlock synchronization on host side
if (0 == tid) {
approx_final[bid] = shared[0];
}
} // end early out if possible
}
#endif // #ifndef _DWTHAAR1D_KERNEL_H_

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