add and update samples with CUDA 11.3 support

This commit is contained in:
Rutwik Choughule
2021-04-16 11:54:26 +05:30
parent 067cb65523
commit 568b39bd5b
214 changed files with 6590 additions and 3856 deletions

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################################################################################
# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of NVIDIA CORPORATION nor the names of its
# contributors may be used to endorse or promote products derived
# from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
# EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
# PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
# CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
# EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
# PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
# PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
# OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
#
################################################################################
#
# Makefile project only supported on Mac OS X and Linux Platforms)
#
################################################################################
# Location of the CUDA Toolkit
CUDA_PATH ?= /usr/local/cuda
##############################
# start deprecated interface #
##############################
ifeq ($(x86_64),1)
$(info WARNING - x86_64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=x86_64 instead)
TARGET_ARCH ?= x86_64
endif
ifeq ($(ARMv7),1)
$(info WARNING - ARMv7 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=armv7l instead)
TARGET_ARCH ?= armv7l
endif
ifeq ($(aarch64),1)
$(info WARNING - aarch64 variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=aarch64 instead)
TARGET_ARCH ?= aarch64
endif
ifeq ($(ppc64le),1)
$(info WARNING - ppc64le variable has been deprecated)
$(info WARNING - please use TARGET_ARCH=ppc64le instead)
TARGET_ARCH ?= ppc64le
endif
ifneq ($(GCC),)
$(info WARNING - GCC variable has been deprecated)
$(info WARNING - please use HOST_COMPILER=$(GCC) instead)
HOST_COMPILER ?= $(GCC)
endif
ifneq ($(abi),)
$(error ERROR - abi variable has been removed)
endif
############################
# end deprecated interface #
############################
# architecture
HOST_ARCH := $(shell uname -m)
TARGET_ARCH ?= $(HOST_ARCH)
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le armv7l))
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifneq (,$(filter $(TARGET_ARCH),x86_64 aarch64 sbsa ppc64le))
TARGET_SIZE := 64
else ifneq (,$(filter $(TARGET_ARCH),armv7l))
TARGET_SIZE := 32
endif
else
TARGET_SIZE := $(shell getconf LONG_BIT)
endif
else
$(error ERROR - unsupported value $(TARGET_ARCH) for TARGET_ARCH!)
endif
# sbsa and aarch64 systems look similar. Need to differentiate them at host level for now.
ifeq ($(HOST_ARCH),aarch64)
ifeq ($(CUDA_PATH)/targets/sbsa-linux,$(shell ls -1d $(CUDA_PATH)/targets/sbsa-linux 2>/dev/null))
HOST_ARCH := sbsa
TARGET_ARCH := sbsa
endif
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq (,$(filter $(HOST_ARCH)-$(TARGET_ARCH),aarch64-armv7l x86_64-armv7l x86_64-aarch64 x86_64-sbsa x86_64-ppc64le))
$(error ERROR - cross compiling from $(HOST_ARCH) to $(TARGET_ARCH) is not supported!)
endif
endif
# When on native aarch64 system with userspace of 32-bit, change TARGET_ARCH to armv7l
ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_SIZE),aarch64-aarch64-32)
TARGET_ARCH = armv7l
endif
# operating system
HOST_OS := $(shell uname -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
TARGET_OS ?= $(HOST_OS)
ifeq (,$(filter $(TARGET_OS),linux darwin qnx android))
$(error ERROR - unsupported value $(TARGET_OS) for TARGET_OS!)
endif
# host compiler
ifeq ($(TARGET_OS),darwin)
ifeq ($(shell expr `xcodebuild -version | grep -i xcode | awk '{print $$2}' | cut -d'.' -f1` \>= 5),1)
HOST_COMPILER ?= clang++
endif
else ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
ifeq ($(TARGET_OS),linux)
HOST_COMPILER ?= arm-linux-gnueabihf-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/arm-unknown-nto-qnx6.6.0eabi-g++
else ifeq ($(TARGET_OS),android)
HOST_COMPILER ?= arm-linux-androideabi-g++
endif
else ifeq ($(TARGET_ARCH),aarch64)
ifeq ($(TARGET_OS), linux)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_OS),qnx)
ifeq ($(QNX_HOST),)
$(error ERROR - QNX_HOST must be passed to the QNX host toolchain)
endif
ifeq ($(QNX_TARGET),)
$(error ERROR - QNX_TARGET must be passed to the QNX target toolchain)
endif
export QNX_HOST
export QNX_TARGET
HOST_COMPILER ?= $(QNX_HOST)/usr/bin/q++
else ifeq ($(TARGET_OS), android)
HOST_COMPILER ?= aarch64-linux-android-clang++
endif
else ifeq ($(TARGET_ARCH),sbsa)
HOST_COMPILER ?= aarch64-linux-gnu-g++
else ifeq ($(TARGET_ARCH),ppc64le)
HOST_COMPILER ?= powerpc64le-linux-gnu-g++
endif
endif
HOST_COMPILER ?= g++
NVCC := $(CUDA_PATH)/bin/nvcc -ccbin $(HOST_COMPILER)
# internal flags
NVCCFLAGS := -m${TARGET_SIZE}
CCFLAGS :=
LDFLAGS :=
# build flags
ifeq ($(TARGET_OS),darwin)
LDFLAGS += -rpath $(CUDA_PATH)/lib
CCFLAGS += -arch $(HOST_ARCH)
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
LDFLAGS += --dynamic-linker=/lib/ld-linux-armhf.so.3
CCFLAGS += -mfloat-abi=hard
else ifeq ($(TARGET_OS),android)
LDFLAGS += -pie
CCFLAGS += -fpie -fpic -fexceptions
endif
ifneq ($(TARGET_ARCH),$(HOST_ARCH))
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
ifneq ($(TARGET_FS),)
GCCVERSIONLTEQ46 := $(shell expr `$(HOST_COMPILER) -dumpversion` \<= 4.6)
ifeq ($(GCCVERSIONLTEQ46),1)
CCFLAGS += --sysroot=$(TARGET_FS)
endif
LDFLAGS += --sysroot=$(TARGET_FS)
LDFLAGS += -rpath-link=$(TARGET_FS)/lib -L$(TARGET_FS)/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/lib/aarch64-linux-gnu -L$(TARGET_FS)/lib/aarch64-linux-gnu
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib -L$(TARGET_FS)/usr/lib
LDFLAGS += -rpath-link=$(TARGET_FS)/usr/lib/aarch64-linux-gnu -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
LDFLAGS += --unresolved-symbols=ignore-in-shared-libs
CCFLAGS += -isystem=$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include -I$(TARGET_FS)/usr/include/libdrm
CCFLAGS += -isystem=$(TARGET_FS)/usr/include/aarch64-linux-gnu -I$(TARGET_FS)/usr/include/aarch64-linux-gnu
endif
endif
ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
NVCCFLAGS += --qpp-config 5.4.0,gcc_ntoaarch64le
CCFLAGS += -DWIN_INTERFACE_CUSTOM -I/usr/include/aarch64-qnx-gnu
LDFLAGS += -lsocket
LDFLAGS += -L/usr/lib/aarch64-qnx-gnu
CCFLAGS += "-Wl\,-rpath-link\,/usr/lib/aarch64-qnx-gnu"
ifdef TARGET_OVERRIDE
LDFLAGS += -lslog2
endif
ifneq ($(TARGET_FS),)
LDFLAGS += -L$(TARGET_FS)/usr/lib
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/lib"
LDFLAGS += -L$(TARGET_FS)/usr/libnvidia
CCFLAGS += "-Wl\,-rpath-link\,$(TARGET_FS)/usr/libnvidia"
CCFLAGS += -I$(TARGET_FS)/../include
endif
endif
endif
ifdef TARGET_OVERRIDE # cuda toolkit targets override
NVCCFLAGS += -target-dir $(TARGET_OVERRIDE)
endif
# Install directory of different arch
CUDA_INSTALL_TARGET_DIR :=
ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-linux)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-gnueabihf/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-linux)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),sbsa-linux)
CUDA_INSTALL_TARGET_DIR = targets/sbsa-linux/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-android)
CUDA_INSTALL_TARGET_DIR = targets/armv7-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-android)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-linux-androideabi/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),armv7l-qnx)
CUDA_INSTALL_TARGET_DIR = targets/ARMv7-linux-QNX/
else ifeq ($(TARGET_ARCH)-$(TARGET_OS),aarch64-qnx)
CUDA_INSTALL_TARGET_DIR = targets/aarch64-qnx/
else ifeq ($(TARGET_ARCH),ppc64le)
CUDA_INSTALL_TARGET_DIR = targets/ppc64le-linux/
endif
# Debug build flags
ifeq ($(dbg),1)
NVCCFLAGS += -g -G
BUILD_TYPE := debug
else
BUILD_TYPE := release
endif
ALL_CCFLAGS :=
ALL_CCFLAGS += $(NVCCFLAGS)
ALL_CCFLAGS += $(EXTRA_NVCCFLAGS)
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(CCFLAGS))
ALL_CCFLAGS += $(addprefix -Xcompiler ,$(EXTRA_CCFLAGS))
SAMPLE_ENABLED := 1
# This sample is not supported on Mac OSX
ifeq ($(TARGET_OS),darwin)
$(info >>> WARNING - simpleCUBLAS_LU is not supported on Mac OSX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
# This sample is not supported on ARMv7
ifeq ($(TARGET_ARCH),armv7l)
$(info >>> WARNING - simpleCUBLAS_LU is not supported on ARMv7 - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
# This sample is not supported on QNX
ifeq ($(TARGET_OS),qnx)
$(info >>> WARNING - simpleCUBLAS_LU is not supported on QNX - waiving sample <<<)
SAMPLE_ENABLED := 0
endif
ALL_LDFLAGS :=
ALL_LDFLAGS += $(ALL_CCFLAGS)
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
# Common includes and paths for CUDA
INCLUDES := -I../../Common
LIBRARIES :=
################################################################################
# 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
LIBRARIES += -lcublas
ifeq ($(SAMPLE_ENABLED),0)
EXEC ?= @echo "[@]"
endif
################################################################################
# Target rules
all: build
build: simpleCUBLAS_LU
check.deps:
ifeq ($(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
simpleCUBLAS_LU.o:simpleCUBLAS_LU.cpp
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
simpleCUBLAS_LU: simpleCUBLAS_LU.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
$(EXEC) ./simpleCUBLAS_LU
clean:
rm -f simpleCUBLAS_LU simpleCUBLAS_LU.o
rm -rf ../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/simpleCUBLAS_LU
clobber: clean

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<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
<entry>
<name>simpleCUBLAS_LU</name>
<description><![CDATA[CUDA sample demonstrating cuBLAS API cublasDgetrfBatched() for lower-upper (LU) decomposition of a matrix.]]></description>
<devicecompilation>whole</devicecompilation>
<includepaths>
<path>./</path>
<path>../</path>
<path>../../common/inc</path>
</includepaths>
<keyconcepts>
<concept level="basic">CUBLAS Library</concept>
<concept level="basic">LU decomposition</concept>
</keyconcepts>
<keywords>
<keyword>CUDA</keyword>
<keyword>CUBLAS</keyword>
<keyword>Linear Algebra</keyword>
<keyword>LU decomposition</keyword>
</keywords>
<libraries>
<library>cublas</library>
</libraries>
<librarypaths>
</librarypaths>
<nsight_eclipse>true</nsight_eclipse>
<primary_file>simpleCUBLAS_LU.cpp</primary_file>
<required_dependencies>
<dependency>CUBLAS</dependency>
</required_dependencies>
<scopes>
<scope>1:CUDA Basic Topics</scope>
<scope>3:Linear Algebra</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>aarch64</arch>
</env>
<env>
<arch>ppc64le</arch>
<platform>linux</platform>
</env>
</supported_envs>
<supported_sm_architectures>
<include>all</include>
</supported_sm_architectures>
<title>Simple CUBLAS LU</title>
<type>exe</type>
</entry>

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# simpleCUBLAS_LU - Simple CUBLAS LU
## Description
CUDA sample demonstrating cuBLAS API cublasDgetrfBatched() for lower-upper (LU) decomposition of a matrix.
## Key Concepts
CUBLAS Library, LU decomposition
## 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, aarch64
## CUDA APIs involved
## Dependencies needed to build/run
[CUBLAS](../../README.md#cublas)
## Prerequisites
Download and install the [CUDA Toolkit 11.3](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
## Build and Run
### Windows
The Windows samples are built using the Visual Studio IDE. Solution files (.sln) are provided for each supported version of Visual Studio, using the format:
```
*_vs<version>.sln - for Visual Studio <version>
```
Each individual sample has its own set of solution files in its directory:
To build/examine all the samples at once, the complete solution files should be used. To build/examine a single sample, the individual sample solution files should be used.
> **Note:** Some samples require that the Microsoft DirectX SDK (June 2010 or newer) be installed and that the VC++ directory paths are properly set up (**Tools > Options...**). Check DirectX Dependencies section for details."
### Linux
The Linux samples are built using makefiles. To use the makefiles, change the current directory to the sample directory you wish to build, and run make:
```
$ cd <sample_dir>
$ make
```
The samples makefiles can take advantage of certain options:
* **TARGET_ARCH=<arch>** - cross-compile targeting a specific architecture. Allowed architectures are x86_64, ppc64le, aarch64.
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=aarch64` <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.
*/
/*
* This example demonstrates how to use the cuBLAS library API
* for lower-upper (LU) decomposition of a matrix. LU decomposition
* factors a matrix as the product of upper triangular matrix and
* lower trianglular matrix.
*
* https://en.wikipedia.org/wiki/LU_decomposition
*
* This sample uses 10000 matrices of size 4x4 and performs
* LU decomposition of them using batched decomposition API
* of cuBLAS library. To test the correctness of upper and lower
* matrices generated, they are multiplied and compared with the
* original input matrix.
*
*/
#include <stdio.h>
#include <stdlib.h>
// cuda libraries and helpers
#include <cublas_v2.h>
#include <cuda_runtime.h>
#include <helper_cuda.h>
// configurable parameters
// dimension of matrix
#define N 4
#define BATCH_SIZE 10000
// use double precision data type
#define DOUBLE_PRECISION /* comment this to use single precision */
#ifdef DOUBLE_PRECISION
#define DATA_TYPE double
#define MAX_ERROR 1e-15
#else
#define DATA_TYPE float
#define MAX_ERROR 1e-6
#endif /* DOUBLE_PRCISION */
// use pivot vector while decomposing
#define PIVOT /* comment this to disable pivot use */
// helper functions
// wrapper around cublas<t>getrfBatched()
cublasStatus_t cublasXgetrfBatched(cublasHandle_t handle, int n,
DATA_TYPE* const A[], int lda, int* P,
int* info, int batchSize) {
#ifdef DOUBLE_PRECISION
return cublasDgetrfBatched(handle, n, A, lda, P, info, batchSize);
#else
return cublasSgetrfBatched(handle, n, A, lda, P, info, batchSize);
#endif
}
// wrapper around malloc
// clears the allocated memory to 0
// terminates the program if malloc fails
void* xmalloc(size_t size) {
void* ptr = malloc(size);
if (ptr == NULL) {
printf("> ERROR: malloc for size %zu failed..\n", size);
exit(EXIT_FAILURE);
}
memset(ptr, 0, size);
return ptr;
}
// initalize identity matrix
void initIdentityMatrix(DATA_TYPE* mat) {
// clear the matrix
memset(mat, 0, N * N * sizeof(DATA_TYPE));
// set all diagonals to 1
for (int i = 0; i < N; i++) {
mat[(i * N) + i] = 1.0;
}
}
// initialize matrix with all elements as 0
void initZeroMatrix(DATA_TYPE* mat) {
memset(mat, 0, N * N * sizeof(DATA_TYPE));
}
// fill random value in column-major matrix
void initRandomMatrix(DATA_TYPE* mat) {
for (int i = 0; i < N; i++) {
for (int j = 0; j < N; j++) {
mat[(j * N) + i] =
(DATA_TYPE)1.0 + ((DATA_TYPE)rand() / (DATA_TYPE)RAND_MAX);
}
}
// diagonal dominant matrix to insure it is invertible matrix
for (int i = 0; i < N; i++) {
mat[(i * N) + i] += (DATA_TYPE)N;
}
}
// print column-major matrix
void printMatrix(DATA_TYPE* mat) {
for (int i = 0; i < N; i++) {
for (int j = 0; j < N; j++) {
printf("%20.16f ", mat[(j * N) + i]);
}
printf("\n");
}
printf("\n");
}
// matrix mulitplication
void matrixMultiply(DATA_TYPE* res, DATA_TYPE* mat1, DATA_TYPE* mat2) {
initZeroMatrix(res);
for (int i = 0; i < N; i++) {
for (int j = 0; j < N; j++) {
for (int k = 0; k < N; k++) {
res[(j * N) + i] += mat1[(k * N) + i] * mat2[(j * N) + k];
}
}
}
}
// check matrix equality
bool checkRelativeError(DATA_TYPE* mat1, DATA_TYPE* mat2, DATA_TYPE maxError) {
DATA_TYPE err = (DATA_TYPE)0.0;
DATA_TYPE refNorm = (DATA_TYPE)0.0;
DATA_TYPE relError = (DATA_TYPE)0.0;
DATA_TYPE relMaxError = (DATA_TYPE)0.0;
for (int i = 0; i < N * N; i++) {
refNorm = abs(mat1[i]);
err = abs(mat1[i] - mat2[i]);
if (refNorm != 0.0 && err > 0.0) {
relError = err / refNorm;
relMaxError = MAX(relMaxError, relError);
}
if (relMaxError > maxError) return false;
}
return true;
}
// decode lower and upper matrix from single matrix
// returned by getrfBatched()
void getLUdecoded(DATA_TYPE* mat, DATA_TYPE* L, DATA_TYPE* U) {
// init L as identity matrix
initIdentityMatrix(L);
// copy lower triangular values from mat to L (skip diagonal)
for (int i = 0; i < N; i++) {
for (int j = 0; j < i; j++) {
L[(j * N) + i] = mat[(j * N) + i];
}
}
// init U as all zero
initZeroMatrix(U);
// copy upper triangular values from mat to U
for (int i = 0; i < N; i++) {
for (int j = i; j < N; j++) {
U[(j * N) + i] = mat[(j * N) + i];
}
}
}
// generate permutation matrix from pivot vector
void getPmatFromPivot(DATA_TYPE* Pmat, int* P) {
int pivot[N];
// pivot vector in base-1
// convert it to base-0
for (int i = 0; i < N; i++) {
P[i]--;
}
// generate permutation vector from pivot
// initialize pivot with identity sequence
for (int k = 0; k < N; k++) {
pivot[k] = k;
}
// swap the indices according to pivot vector
for (int k = 0; k < N; k++) {
int q = P[k];
// swap pivot(k) and pivot(q)
int s = pivot[k];
int t = pivot[q];
pivot[k] = t;
pivot[q] = s;
}
// generate permutation matrix from pivot vector
initZeroMatrix(Pmat);
for (int i = 0; i < N; i++) {
int j = pivot[i];
Pmat[(j * N) + i] = (DATA_TYPE)1.0;
}
}
int main(int argc, char** argv) {
// cuBLAS variables
cublasStatus_t status;
cublasHandle_t handle;
// host variables
size_t matSize = N * N * sizeof(DATA_TYPE);
DATA_TYPE* h_AarrayInput;
DATA_TYPE* h_AarrayOutput;
DATA_TYPE* h_ptr_array[BATCH_SIZE];
int* h_pivotArray;
int* h_infoArray;
// device variables
DATA_TYPE* d_Aarray;
DATA_TYPE** d_ptr_array;
int* d_pivotArray;
int* d_infoArray;
int err_count = 0;
// seed the rand() function with time
srand(12345);
// find cuda device
printf("> initializing..\n");
int dev = findCudaDevice(argc, (const char**)argv);
if (dev == -1) {
return (EXIT_FAILURE);
}
// initialize cuBLAS
status = cublasCreate(&handle);
if (status != CUBLAS_STATUS_SUCCESS) {
printf("> ERROR: cuBLAS initialization failed..\n");
return (EXIT_FAILURE);
}
#ifdef DOUBLE_PRECISION
printf("> using DOUBLE precision..\n");
#else
printf("> using SINGLE precision..\n");
#endif
#ifdef PIVOT
printf("> pivot ENABLED..\n");
#else
printf("> pivot DISABLED..\n");
#endif
// allocate memory for host variables
h_AarrayInput = (DATA_TYPE*)xmalloc(BATCH_SIZE * matSize);
h_AarrayOutput = (DATA_TYPE*)xmalloc(BATCH_SIZE * matSize);
h_pivotArray = (int*)xmalloc(N * BATCH_SIZE * sizeof(int));
h_infoArray = (int*)xmalloc(BATCH_SIZE * sizeof(int));
// allocate memory for device variables
checkCudaErrors(cudaMalloc((void**)&d_Aarray, BATCH_SIZE * matSize));
checkCudaErrors(
cudaMalloc((void**)&d_pivotArray, N * BATCH_SIZE * sizeof(int)));
checkCudaErrors(cudaMalloc((void**)&d_infoArray, BATCH_SIZE * sizeof(int)));
checkCudaErrors(
cudaMalloc((void**)&d_ptr_array, BATCH_SIZE * sizeof(DATA_TYPE*)));
// fill matrix with random data
printf("> generating random matrices..\n");
for (int i = 0; i < BATCH_SIZE; i++) {
initRandomMatrix(h_AarrayInput + (i * N * N));
}
// copy data to device from host
printf("> copying data from host memory to GPU memory..\n");
checkCudaErrors(cudaMemcpy(d_Aarray, h_AarrayInput, BATCH_SIZE * matSize,
cudaMemcpyHostToDevice));
// create pointer array for matrices
for (int i = 0; i < BATCH_SIZE; i++) h_ptr_array[i] = d_Aarray + (i * N * N);
// copy pointer array to device memory
checkCudaErrors(cudaMemcpy(d_ptr_array, h_ptr_array,
BATCH_SIZE * sizeof(DATA_TYPE*),
cudaMemcpyHostToDevice));
// perform LU decomposition
printf("> performing LU decomposition..\n");
#ifdef PIVOT
status = cublasXgetrfBatched(handle, N, d_ptr_array, N, d_pivotArray,
d_infoArray, BATCH_SIZE);
#else
status = cublasXgetrfBatched(handle, N, d_ptr_array, N, NULL, d_infoArray,
BATCH_SIZE);
#endif /* PIVOT */
if (status != CUBLAS_STATUS_SUCCESS) {
printf("> ERROR: cublasDgetrfBatched() failed with error %s..\n",
_cudaGetErrorEnum(status));
return (EXIT_FAILURE);
}
// copy data to host from device
printf("> copying data from GPU memory to host memory..\n");
checkCudaErrors(cudaMemcpy(h_AarrayOutput, d_Aarray, BATCH_SIZE * matSize,
cudaMemcpyDeviceToHost));
checkCudaErrors(cudaMemcpy(h_infoArray, d_infoArray, BATCH_SIZE * sizeof(int),
cudaMemcpyDeviceToHost));
#ifdef PIVOT
checkCudaErrors(cudaMemcpy(h_pivotArray, d_pivotArray,
N * BATCH_SIZE * sizeof(int),
cudaMemcpyDeviceToHost));
#endif /* PIVOT */
// verify the result
printf("> verifying the result..\n");
for (int i = 0; i < BATCH_SIZE; i++) {
if (h_infoArray[i] == 0) {
DATA_TYPE* A = h_AarrayInput + (i * N * N);
DATA_TYPE* LU = h_AarrayOutput + (i * N * N);
DATA_TYPE L[N * N];
DATA_TYPE U[N * N];
getLUdecoded(LU, L, U);
// test P * A = L * U
int* P = h_pivotArray + (i * N);
DATA_TYPE Pmat[N * N];
#ifdef PIVOT
getPmatFromPivot(Pmat, P);
#else
initIdentityMatrix(Pmat);
#endif /* PIVOT */
// perform matrix multiplication
DATA_TYPE PxA[N * N];
DATA_TYPE LxU[N * N];
matrixMultiply(PxA, Pmat, A);
matrixMultiply(LxU, L, U);
// check for equality of matrices
if (!checkRelativeError(PxA, LxU, (DATA_TYPE)MAX_ERROR)) {
printf("> ERROR: accuracy check failed for matrix number %05d..\n",
i + 1);
err_count++;
}
} else if (h_infoArray[i] > 0) {
printf(
"> execution for matrix %05d is successful, but U is singular and "
"U(%d,%d) = 0..\n",
i + 1, h_infoArray[i] - 1, h_infoArray[i] - 1);
} else // (h_infoArray[i] < 0)
{
printf("> ERROR: matrix %05d have an illegal value at index %d = %lf..\n",
i + 1, -h_infoArray[i],
*(h_AarrayInput + (i * N * N) + (-h_infoArray[i])));
}
}
// free device variables
checkCudaErrors(cudaFree(d_ptr_array));
checkCudaErrors(cudaFree(d_infoArray));
checkCudaErrors(cudaFree(d_pivotArray));
checkCudaErrors(cudaFree(d_Aarray));
// free host variables
if (h_infoArray) free(h_infoArray);
if (h_pivotArray) free(h_pivotArray);
if (h_AarrayOutput) free(h_AarrayOutput);
if (h_AarrayInput) free(h_AarrayInput);
// destroy cuBLAS handle
status = cublasDestroy(handle);
if (status != CUBLAS_STATUS_SUCCESS) {
printf("> ERROR: cuBLAS uninitialization failed..\n");
return (EXIT_FAILURE);
}
if (err_count > 0) {
printf("> TEST FAILED for %d matrices, with precision: %g\n", err_count,
MAX_ERROR);
return (EXIT_FAILURE);
}
printf("> TEST SUCCESSFUL, with precision: %g\n", MAX_ERROR);
return (EXIT_SUCCESS);
}

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