mirror of
https://github.com/NVIDIA/cuda-samples.git
synced 2025-04-05 14:58:38 +08:00
Compare commits
1 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
1fa9c59db4 |
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@ -1,6 +1,6 @@
|
|||
## Changelog
|
||||
|
||||
### CUDA 12.1
|
||||
### CUDA 12.2
|
||||
* libNVVM samples received updates
|
||||
* Fixed jitLto Case issues
|
||||
* Enabled HOST_COMPILER flag to the makefiles for GCC which is untested but may still work.
|
||||
|
|
|
|||
18
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/.vscode/c_cpp_properties.json
vendored
Normal file
18
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/.vscode/c_cpp_properties.json
vendored
Normal file
|
|
@ -0,0 +1,18 @@
|
|||
{
|
||||
"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
|
||||
}
|
||||
7
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/.vscode/extensions.json
vendored
Normal file
7
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/.vscode/extensions.json
vendored
Normal file
|
|
@ -0,0 +1,7 @@
|
|||
{
|
||||
"recommendations": [
|
||||
"nvidia.nsight-vscode-edition",
|
||||
"ms-vscode.cpptools",
|
||||
"ms-vscode.makefile-tools"
|
||||
]
|
||||
}
|
||||
10
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/.vscode/launch.json
vendored
Normal file
10
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/.vscode/launch.json
vendored
Normal file
|
|
@ -0,0 +1,10 @@
|
|||
{
|
||||
"configurations": [
|
||||
{
|
||||
"name": "CUDA C++: Launch",
|
||||
"type": "cuda-gdb",
|
||||
"request": "launch",
|
||||
"program": "${workspaceFolder}/cuDLALayerwiseStatsHybrid"
|
||||
}
|
||||
]
|
||||
}
|
||||
15
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/.vscode/tasks.json
vendored
Normal file
15
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/.vscode/tasks.json
vendored
Normal file
|
|
@ -0,0 +1,15 @@
|
|||
{
|
||||
"version": "2.0.0",
|
||||
"tasks": [
|
||||
{
|
||||
"label": "sample",
|
||||
"type": "shell",
|
||||
"command": "make dbg=1",
|
||||
"problemMatcher": ["$nvcc"],
|
||||
"group": {
|
||||
"kind": "build",
|
||||
"isDefault": true
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
400
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/Makefile
Normal file
400
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/Makefile
Normal file
|
|
@ -0,0 +1,400 @@
|
|||
################################################################################
|
||||
# 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.
|
||||
#
|
||||
################################################################################
|
||||
#
|
||||
# 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 $(TARGET_OS) for TARGET_OS!)
|
||||
endif
|
||||
|
||||
# host compiler
|
||||
ifdef HOST_COMPILER
|
||||
CUSTOM_HOST_COMPILER = 1
|
||||
endif
|
||||
|
||||
ifeq ($(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 += -D_QNX_SOURCE
|
||||
NVCCFLAGS += --qpp-config 8.3.0,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 Linux x86_64
|
||||
ifeq ($(TARGET_OS),linux)
|
||||
ifeq ($(TARGET_ARCH),x86_64)
|
||||
$(info >>> WARNING - cuDLALayerwiseStatsHybrid is not supported on Linux x86_64 - waiving sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
endif
|
||||
|
||||
# This sample is not supported on Mac OSX
|
||||
ifeq ($(TARGET_OS),darwin)
|
||||
$(info >>> WARNING - cuDLALayerwiseStatsHybrid 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 - cuDLALayerwiseStatsHybrid is not supported on ARMv7 - waiving sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
|
||||
# This sample is not supported on sbsa
|
||||
ifeq ($(TARGET_ARCH),sbsa)
|
||||
$(info >>> WARNING - cuDLALayerwiseStatsHybrid is not supported on sbsa - 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 :=
|
||||
|
||||
################################################################################
|
||||
|
||||
#Detect if installed version of GCC supports required C++11
|
||||
ifeq ($(TARGET_OS),linux)
|
||||
empty :=
|
||||
space := $(empty) $(empty)
|
||||
GCCVERSIONSTRING := $(shell expr `$(HOST_COMPILER) -dumpversion`)
|
||||
#Create version number without "."
|
||||
GCCVERSION := $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f1 -d.)
|
||||
GCCVERSION += $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f2 -d.)
|
||||
GCCVERSION += $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f3 -d.)
|
||||
# Make sure the version number has at least 3 decimals
|
||||
GCCVERSION += 00
|
||||
# Remove spaces from the version number
|
||||
GCCVERSION := $(subst $(space),$(empty),$(GCCVERSION))
|
||||
#$(warning $(GCCVERSION))
|
||||
|
||||
IS_MIN_VERSION := $(shell expr `echo $(GCCVERSION)` \>= 47000)
|
||||
ifneq ($(CUSTOM_HOST_COMPILER), 1)
|
||||
ifeq ($(IS_MIN_VERSION), 1)
|
||||
$(info >>> GCC Version is greater or equal to 4.7.0 <<<)
|
||||
else
|
||||
$(info >>> Waiving build. Minimum GCC version required is 4.7.0<<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
else
|
||||
$(warning >>> Custom HOST_COMPILER set; skipping GCC version check. This may lead to unintended behavior. Please note the minimum equivalent GCC version is 4.7.0 <<<)
|
||||
endif
|
||||
endif
|
||||
|
||||
# Gencode arguments
|
||||
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64 sbsa))
|
||||
SMS ?= 53 61 70 72 75 80 86 87 90
|
||||
else
|
||||
SMS ?= 50 52 60 61 70 75 80 86 89 90
|
||||
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 += --std=c++11 --threads 0
|
||||
|
||||
LIBRARIES += -lcudla
|
||||
|
||||
ifeq ($(SAMPLE_ENABLED),0)
|
||||
EXEC ?= @echo "[@]"
|
||||
endif
|
||||
|
||||
################################################################################
|
||||
|
||||
# Target rules
|
||||
all: build
|
||||
|
||||
build: cuDLALayerwiseStatsHybrid
|
||||
|
||||
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
|
||||
|
||||
main.o:main.cu
|
||||
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
|
||||
|
||||
cuDLALayerwiseStatsHybrid: main.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) ./cuDLALayerwiseStatsHybrid
|
||||
|
||||
testrun: build
|
||||
|
||||
clean:
|
||||
rm -f cuDLALayerwiseStatsHybrid main.o
|
||||
rm -rf ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/cuDLALayerwiseStatsHybrid
|
||||
|
||||
clobber: clean
|
||||
|
|
@ -0,0 +1,71 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
|
||||
<entry>
|
||||
<name>cuDLALayerwiseStatsHybrid</name>
|
||||
<cflags>
|
||||
<flag>--std=c++11</flag>
|
||||
</cflags>
|
||||
<cuda_api_list>
|
||||
<toolkit>cudaStreamCreateWithFlags</toolkit>
|
||||
<toolkit>cudaStreamDestroy</toolkit>
|
||||
<toolkit>cudaFree</toolkit>
|
||||
<toolkit>cudaGetErrorName</toolkit>
|
||||
<toolkit>cudaSetDevice</toolkit>
|
||||
<toolkit>cudaStreamSynchronize</toolkit>
|
||||
<toolkit>cudaMalloc</toolkit>
|
||||
<toolkit>cudaMemsetAsync</toolkit>
|
||||
<toolkit>cudaMemcpyAsync</toolkit>
|
||||
</cuda_api_list>
|
||||
<description><![CDATA[This sample is used to provide layerwise statistics to the application in the cuDLA hybrid mode wherein DLA is programmed using CUDA.]]></description>
|
||||
<devicecompilation>whole</devicecompilation>
|
||||
<includepaths>
|
||||
<path>./</path>
|
||||
<path>../</path>
|
||||
<path>../../../Common</path>
|
||||
</includepaths>
|
||||
<keyconcepts>
|
||||
<concept level="basic">cuDLA</concept>
|
||||
<concept level="advanced">Data Parallel Algorithms</concept>
|
||||
<concept level="advanced">Image Processing</concept>
|
||||
</keyconcepts>
|
||||
<keywords>
|
||||
<keyword>CUDA</keyword>
|
||||
<keyword>CPP11</keyword>
|
||||
</keywords>
|
||||
<libraries>
|
||||
<library>cudla</library>
|
||||
</libraries>
|
||||
<librarypaths>
|
||||
</librarypaths>
|
||||
<nsight_eclipse>true</nsight_eclipse>
|
||||
<primary_file>main.cu</primary_file>
|
||||
<scopes>
|
||||
<scope>1:CUDA Advanced Topics</scope>
|
||||
<scope>1:cuDLA</scope>
|
||||
</scopes>
|
||||
<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>aarch64</arch>
|
||||
<platform>linux</platform>
|
||||
</env>
|
||||
<env>
|
||||
<arch>aarch64</arch>
|
||||
<platform>qnx</platform>
|
||||
</env>
|
||||
</supported_envs>
|
||||
<supported_sm_architectures>
|
||||
<from>6.0</from>
|
||||
</supported_sm_architectures>
|
||||
<title>cuDLA Layerwise statistics HybridMode</title>
|
||||
<type>exe</type>
|
||||
</entry>
|
||||
60
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/README.md
Normal file
60
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/README.md
Normal file
|
|
@ -0,0 +1,60 @@
|
|||
# cuDLALayerwiseStatsHybrid - cuDLA Layerwise statistics HybridMode
|
||||
|
||||
## Description
|
||||
|
||||
This sample is used to provide layerwise statistics to the application in the cuDLA hybrid mode wherein DLA is programmed using CUDA.
|
||||
|
||||
## Key Concepts
|
||||
|
||||
cuDLA, Data Parallel Algorithms, Image Processing
|
||||
|
||||
## Supported SM Architectures
|
||||
|
||||
[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, QNX
|
||||
|
||||
## Supported CPU Architecture
|
||||
|
||||
aarch64
|
||||
|
||||
## CUDA APIs involved
|
||||
|
||||
### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
|
||||
cudaStreamCreateWithFlags, cudaStreamDestroy, cudaFree, cudaGetErrorName, cudaSetDevice, cudaStreamSynchronize, cudaMalloc, cudaMemsetAsync, cudaMemcpyAsync
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Download and install the [CUDA Toolkit 12.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
|
||||
|
||||
## Build and Run
|
||||
|
||||
### 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 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=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)
|
||||
|
||||
898
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/main.cu
Normal file
898
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsHybrid/main.cu
Normal file
|
|
@ -0,0 +1,898 @@
|
|||
/* Copyright (c) 2023, 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.
|
||||
*/
|
||||
|
||||
#include "cudla.h"
|
||||
#include "cuda_runtime.h"
|
||||
#include "cudlaExternalEtbl.hpp"
|
||||
|
||||
#include <cstdio>
|
||||
#include <cstdlib>
|
||||
#include <cstring>
|
||||
#include <sys/stat.h>
|
||||
#include <fstream>
|
||||
#include <sstream>
|
||||
|
||||
#define MAX_FILENAME_LEN 200
|
||||
#define RESERVED_SUFFIX_LEN 10
|
||||
|
||||
#define DPRINTF(...) printf(__VA_ARGS__)
|
||||
|
||||
static void printTensorDesc(cudlaModuleTensorDescriptor* tensorDesc) {
|
||||
DPRINTF("\tTENSOR NAME : %s\n", tensorDesc->name);
|
||||
DPRINTF("\tsize: %lu\n", tensorDesc->size);
|
||||
|
||||
DPRINTF("\tdims: [%lu, %lu, %lu, %lu]\n", tensorDesc->n, tensorDesc->c,
|
||||
tensorDesc->h, tensorDesc->w);
|
||||
|
||||
DPRINTF("\tdata fmt: %d\n", tensorDesc->dataFormat);
|
||||
DPRINTF("\tdata type: %d\n", tensorDesc->dataType);
|
||||
DPRINTF("\tdata category: %d\n", tensorDesc->dataCategory);
|
||||
DPRINTF("\tpixel fmt: %d\n", tensorDesc->pixelFormat);
|
||||
DPRINTF("\tpixel mapping: %d\n", tensorDesc->pixelMapping);
|
||||
DPRINTF("\tstride[0]: %d\n", tensorDesc->stride[0]);
|
||||
DPRINTF("\tstride[1]: %d\n", tensorDesc->stride[1]);
|
||||
DPRINTF("\tstride[2]: %d\n", tensorDesc->stride[2]);
|
||||
DPRINTF("\tstride[3]: %d\n", tensorDesc->stride[3]);
|
||||
}
|
||||
|
||||
typedef struct {
|
||||
cudlaDevHandle devHandle;
|
||||
cudlaModule moduleHandle;
|
||||
unsigned char* loadableData;
|
||||
cudaStream_t stream;
|
||||
uint32_t numInputTensors;
|
||||
uint32_t numOutputTensors;
|
||||
uint32_t numOutputTaskStatistics;
|
||||
unsigned char** inputBuffer;
|
||||
unsigned char** outputBuffer;
|
||||
unsigned char** statisticsOutputBuffer;
|
||||
void** inputBufferGPU;
|
||||
void** outputBufferGPU;
|
||||
void** outputTaskStatisticsGPU;
|
||||
void **csv;
|
||||
cudlaModuleTensorDescriptor* inputTensorDesc;
|
||||
cudlaModuleTensorDescriptor* outputTensorDesc;
|
||||
cudlaModuleTensorDescriptor* outputTaskStatisticsDesc;
|
||||
uint64_t** inputBufferRegisteredPtr;
|
||||
uint64_t** outputBufferRegisteredPtr;
|
||||
uint64_t** outputTaskStatisticsRegisteredPtr;
|
||||
uint64_t** outputStatisticsBufferRegisteredPtr;
|
||||
} ResourceList;
|
||||
|
||||
void cleanUp(ResourceList* resourceList);
|
||||
|
||||
void cleanUp(ResourceList* resourceList) {
|
||||
uint32_t ii = 0;
|
||||
if (resourceList->inputTensorDesc != NULL) {
|
||||
free(resourceList->inputTensorDesc);
|
||||
resourceList->inputTensorDesc = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->outputTensorDesc != NULL) {
|
||||
free(resourceList->outputTensorDesc);
|
||||
resourceList->outputTensorDesc = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->outputTaskStatisticsDesc != NULL) {
|
||||
free(resourceList->outputTaskStatisticsDesc);
|
||||
resourceList->outputTaskStatisticsDesc = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->loadableData != NULL) {
|
||||
free(resourceList->loadableData);
|
||||
resourceList->loadableData = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->moduleHandle != NULL) {
|
||||
cudlaModuleUnload(resourceList->moduleHandle, 0);
|
||||
resourceList->moduleHandle = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->devHandle != NULL) {
|
||||
cudlaDestroyDevice(resourceList->devHandle);
|
||||
resourceList->devHandle = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->inputBufferGPU != NULL) {
|
||||
for (ii = 0; ii < resourceList->numInputTensors; ii++) {
|
||||
if ((resourceList->inputBufferGPU)[ii] != NULL) {
|
||||
cudaFree((resourceList->inputBufferGPU)[ii]);
|
||||
(resourceList->inputBufferGPU)[ii] = NULL;
|
||||
}
|
||||
}
|
||||
free(resourceList->inputBufferGPU);
|
||||
resourceList->inputBufferGPU = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->outputBufferGPU != NULL) {
|
||||
for (ii = 0; ii < resourceList->numOutputTensors; ii++) {
|
||||
if ((resourceList->outputBufferGPU)[ii] != NULL) {
|
||||
cudaFree((resourceList->outputBufferGPU)[ii]);
|
||||
(resourceList->outputBufferGPU)[ii] = NULL;
|
||||
}
|
||||
}
|
||||
free(resourceList->outputBufferGPU);
|
||||
resourceList->outputBufferGPU = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->outputTaskStatisticsGPU != NULL) {
|
||||
for (ii = 0; ii < resourceList->numOutputTaskStatistics; ii++) {
|
||||
if ((resourceList->outputTaskStatisticsGPU)[ii] != NULL) {
|
||||
cudaFree((resourceList->outputTaskStatisticsGPU)[ii]);
|
||||
(resourceList->outputTaskStatisticsGPU)[ii] = NULL;
|
||||
}
|
||||
}
|
||||
free(resourceList->outputTaskStatisticsGPU);
|
||||
resourceList->outputTaskStatisticsGPU = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->csv != NULL) {
|
||||
for (ii = 0; ii < resourceList->numOutputTaskStatistics; ii++) {
|
||||
if ((resourceList->csv)[ii] != NULL)
|
||||
{
|
||||
free((resourceList->csv)[ii]);
|
||||
(resourceList->csv)[ii] = NULL;
|
||||
}
|
||||
}
|
||||
free(resourceList->csv);
|
||||
resourceList->csv = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->inputBuffer != NULL) {
|
||||
for (ii = 0; ii < resourceList->numInputTensors; ii++) {
|
||||
if ((resourceList->inputBuffer)[ii] != NULL) {
|
||||
free((resourceList->inputBuffer)[ii]);
|
||||
(resourceList->inputBuffer)[ii] = NULL;
|
||||
}
|
||||
}
|
||||
free(resourceList->inputBuffer);
|
||||
resourceList->inputBuffer = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->outputBuffer != NULL) {
|
||||
for (ii = 0; ii < resourceList->numOutputTensors; ii++) {
|
||||
if ((resourceList->outputBuffer)[ii] != NULL)
|
||||
{
|
||||
free((resourceList->outputBuffer)[ii]);
|
||||
(resourceList->outputBuffer)[ii] = NULL;
|
||||
}
|
||||
}
|
||||
free(resourceList->outputBuffer);
|
||||
resourceList->outputBuffer = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->statisticsOutputBuffer != NULL) {
|
||||
for (ii = 0; ii < resourceList->numOutputTaskStatistics; ii++) {
|
||||
if ((resourceList->statisticsOutputBuffer)[ii] != NULL) {
|
||||
free((resourceList->statisticsOutputBuffer)[ii]);
|
||||
(resourceList->statisticsOutputBuffer)[ii] = NULL;
|
||||
}
|
||||
}
|
||||
free(resourceList->statisticsOutputBuffer);
|
||||
resourceList->statisticsOutputBuffer = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->stream != NULL) {
|
||||
cudaStreamDestroy(resourceList->stream);
|
||||
resourceList->stream = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->inputBufferRegisteredPtr != NULL) {
|
||||
free(resourceList->inputBufferRegisteredPtr);
|
||||
resourceList->inputBufferRegisteredPtr = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->outputBufferRegisteredPtr != NULL) {
|
||||
free(resourceList->outputBufferRegisteredPtr);
|
||||
resourceList->outputBufferRegisteredPtr = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->outputTaskStatisticsRegisteredPtr != NULL) {
|
||||
free(resourceList->outputTaskStatisticsRegisteredPtr);
|
||||
resourceList->outputTaskStatisticsRegisteredPtr = NULL;
|
||||
}
|
||||
|
||||
if (resourceList->outputStatisticsBufferRegisteredPtr != NULL) {
|
||||
free(resourceList->outputStatisticsBufferRegisteredPtr);
|
||||
resourceList->outputStatisticsBufferRegisteredPtr = NULL;
|
||||
}
|
||||
|
||||
resourceList->numInputTensors = 0;
|
||||
resourceList->numOutputTensors = 0;
|
||||
resourceList->numOutputTaskStatistics = 0;
|
||||
}
|
||||
|
||||
int main(int argc, char** argv) {
|
||||
cudlaDevHandle devHandle;
|
||||
cudlaModule moduleHandle;
|
||||
cudlaStatus err;
|
||||
uint32_t statSupport = 0;
|
||||
uint32_t dlaFreqInMHz = 0;
|
||||
FILE* fp = NULL;
|
||||
struct stat st;
|
||||
size_t file_size;
|
||||
size_t actually_read = 0;
|
||||
unsigned char *loadableData = NULL;
|
||||
char filename[MAX_FILENAME_LEN];
|
||||
const char* suffix = ".csv";
|
||||
|
||||
cudaStream_t stream;
|
||||
cudaError_t result;
|
||||
const char* errPtr = NULL;
|
||||
|
||||
ResourceList resourceList;
|
||||
|
||||
memset(&resourceList, 0x00, sizeof(ResourceList));
|
||||
|
||||
if ((argc != 4) && (argc != 5)) {
|
||||
DPRINTF("Usage : ./test_cudla_layerwise_stats_L0_hybrid_test1 <loadable> <freqMHZ> <statSupport> <filename prefix>\n");
|
||||
return 1;
|
||||
}
|
||||
|
||||
if (argc == 5) {
|
||||
if((strlen(argv[4])) > (MAX_FILENAME_LEN - RESERVED_SUFFIX_LEN))
|
||||
{
|
||||
DPRINTF("Filename prefix length is too big, greater than maximum permissible prefix length of %u \n",(MAX_FILENAME_LEN - RESERVED_SUFFIX_LEN));
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
// Read loadable into buffer.
|
||||
fp = fopen(argv[1], "rb");
|
||||
if (fp == NULL) {
|
||||
DPRINTF("Cannot open file %s\n", argv[1]);
|
||||
return 1;
|
||||
}
|
||||
|
||||
if (stat(argv[1], &st) != 0) {
|
||||
DPRINTF("Cannot stat file\n");
|
||||
return 1;
|
||||
}
|
||||
|
||||
file_size = st.st_size;
|
||||
DPRINTF("The file size = %ld\n", file_size);
|
||||
|
||||
dlaFreqInMHz = atoi(argv[2]);
|
||||
statSupport = atoi(argv[3]);
|
||||
|
||||
loadableData = (unsigned char *)malloc(file_size);
|
||||
if (loadableData == NULL) {
|
||||
DPRINTF("Cannot Allocate memory for loadable\n");
|
||||
return 1;
|
||||
}
|
||||
|
||||
actually_read = fread(loadableData, 1, file_size, fp);
|
||||
if ( actually_read != file_size ) {
|
||||
free(loadableData);
|
||||
DPRINTF("Read wrong size\n");
|
||||
return 1;
|
||||
}
|
||||
fclose(fp);
|
||||
|
||||
resourceList.loadableData = loadableData;
|
||||
|
||||
// Initialize CUDA.
|
||||
result = cudaFree(0);
|
||||
if (result != cudaSuccess) {
|
||||
errPtr = cudaGetErrorName(result);
|
||||
DPRINTF("Error in creating cudaFree = %s\n", errPtr);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
result = cudaSetDevice(0);
|
||||
if (result != cudaSuccess) {
|
||||
errPtr = cudaGetErrorName(result);
|
||||
DPRINTF("Error in creating cudaSetDevice = %s\n", errPtr);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
err = cudlaCreateDevice(0, &devHandle, CUDLA_CUDA_DLA);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in cuDLA create device = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
DPRINTF("Device created successfully\n");
|
||||
resourceList.devHandle = devHandle;
|
||||
|
||||
err = cudlaModuleLoadFromMemory(devHandle, loadableData, file_size, &moduleHandle, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in cudlaModuleLoadFromMemory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
} else {
|
||||
DPRINTF("Successfully loaded module\n");
|
||||
}
|
||||
|
||||
resourceList.moduleHandle = moduleHandle;
|
||||
|
||||
// Create CUDA stream.
|
||||
result = cudaStreamCreateWithFlags(&stream, cudaStreamNonBlocking);
|
||||
|
||||
if (result != cudaSuccess) {
|
||||
errPtr = cudaGetErrorName(result);
|
||||
DPRINTF("Error in creating cuda stream = %s\n", errPtr);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.stream = stream;
|
||||
|
||||
// Get tensor attributes.
|
||||
uint32_t numInputTensors = 0;
|
||||
uint32_t numOutputTensors = 0;
|
||||
uint32_t numOutputTaskStatistics = 0;
|
||||
|
||||
cudlaModuleAttribute attribute;
|
||||
|
||||
err = cudlaModuleGetAttributes(moduleHandle, CUDLA_NUM_INPUT_TENSORS, &attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting numInputTensors = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
numInputTensors = attribute.numInputTensors;
|
||||
DPRINTF("numInputTensors = %d\n", numInputTensors);
|
||||
|
||||
err = cudlaModuleGetAttributes(moduleHandle, CUDLA_NUM_OUTPUT_TENSORS, &attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting numOutputTensors = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
numOutputTensors = attribute.numOutputTensors;
|
||||
DPRINTF("numOutputTensors = %d\n", numOutputTensors);
|
||||
|
||||
// using the same attributes to get num_output_task_statistics_tensors
|
||||
attribute.numOutputTensors = 0;
|
||||
|
||||
err = cudlaModuleGetAttributes(moduleHandle, CUDLA_NUM_OUTPUT_TASK_STATISTICS, &attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting numOutputTensors = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
numOutputTaskStatistics = attribute.numOutputTensors;
|
||||
DPRINTF("numOutputTaskStatistics = %d\n", numOutputTaskStatistics);
|
||||
|
||||
if(numOutputTaskStatistics == 0) {
|
||||
DPRINTF("Layerwise stats is not supported for this Loadable \n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.numInputTensors = numInputTensors;
|
||||
resourceList.numOutputTensors = numOutputTensors;
|
||||
resourceList.numOutputTaskStatistics = numOutputTaskStatistics;
|
||||
|
||||
cudlaModuleTensorDescriptor* inputTensorDesc =
|
||||
(cudlaModuleTensorDescriptor*)malloc(sizeof(cudlaModuleTensorDescriptor)*numInputTensors);
|
||||
cudlaModuleTensorDescriptor* outputTensorDesc =
|
||||
(cudlaModuleTensorDescriptor*)malloc(sizeof(cudlaModuleTensorDescriptor)*numOutputTensors);
|
||||
|
||||
if ((inputTensorDesc == NULL) || (outputTensorDesc == NULL)) {
|
||||
if (inputTensorDesc != NULL) {
|
||||
free(inputTensorDesc);
|
||||
inputTensorDesc = NULL;
|
||||
}
|
||||
|
||||
if (outputTensorDesc != NULL) {
|
||||
free(outputTensorDesc);
|
||||
outputTensorDesc = NULL;
|
||||
}
|
||||
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.inputTensorDesc = inputTensorDesc;
|
||||
resourceList.outputTensorDesc = outputTensorDesc;
|
||||
|
||||
cudlaModuleTensorDescriptor* outputTaskStatisticsDesc =
|
||||
(cudlaModuleTensorDescriptor*)malloc(sizeof(cudlaModuleTensorDescriptor)*numOutputTaskStatistics);
|
||||
if (outputTaskStatisticsDesc == NULL) {
|
||||
free(outputTaskStatisticsDesc);
|
||||
outputTaskStatisticsDesc = NULL;
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.outputTaskStatisticsDesc = outputTaskStatisticsDesc;
|
||||
|
||||
attribute.inputTensorDesc = inputTensorDesc;
|
||||
err = cudlaModuleGetAttributes(moduleHandle,
|
||||
CUDLA_INPUT_TENSOR_DESCRIPTORS,
|
||||
&attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting input tensor descriptor = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("Printing input tensor descriptor\n");
|
||||
printTensorDesc(inputTensorDesc);
|
||||
|
||||
attribute.outputTensorDesc = outputTensorDesc;
|
||||
err = cudlaModuleGetAttributes(moduleHandle,
|
||||
CUDLA_OUTPUT_TENSOR_DESCRIPTORS,
|
||||
&attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting output tensor descriptor = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("Printing output tensor descriptor\n");
|
||||
printTensorDesc(outputTensorDesc);
|
||||
|
||||
attribute.outputTensorDesc = outputTaskStatisticsDesc;
|
||||
err = cudlaModuleGetAttributes(moduleHandle,
|
||||
CUDLA_OUTPUT_TASK_STATISTICS_DESCRIPTORS,
|
||||
&attribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in getting task statistics descriptor = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
DPRINTF("Printing output task statistics descriptor size\n");
|
||||
for (uint32_t ii = 0; ii < numOutputTaskStatistics; ii++) {
|
||||
DPRINTF("The size of %u descriptor is %lu\n", ii,outputTaskStatisticsDesc[ii].size);
|
||||
}
|
||||
|
||||
// Setup the input and output buffers which will be used as an input to CUDA.
|
||||
unsigned char** inputBuffer = (unsigned char **)malloc(sizeof(unsigned char *)*numInputTensors);
|
||||
if (inputBuffer == NULL) {
|
||||
DPRINTF("Error in allocating memory for input buffer array\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(inputBuffer, 0x00, sizeof(unsigned char *)*numInputTensors);
|
||||
resourceList.inputBuffer = inputBuffer;
|
||||
for (uint32_t ii = 0; ii < numInputTensors; ii++) {
|
||||
inputBuffer[ii] = (unsigned char* )malloc(inputTensorDesc[ii].size);
|
||||
if (inputBuffer[ii] == NULL) {
|
||||
DPRINTF("Error in allocating input memory\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(inputBuffer[ii], 0x01, inputTensorDesc[ii].size);
|
||||
}
|
||||
|
||||
unsigned char** outputBuffer = (unsigned char **)malloc(sizeof(unsigned char *)*numOutputTensors);
|
||||
if (outputBuffer == NULL) {
|
||||
DPRINTF("Error in allocating memory for output buffer array\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(outputBuffer, 0x00, sizeof(unsigned char *)*numOutputTensors);
|
||||
resourceList.outputBuffer = outputBuffer;
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTensors; ii++) {
|
||||
outputBuffer[ii] = (unsigned char* )malloc(outputTensorDesc[ii].size);
|
||||
if (outputBuffer[ii] == NULL) {
|
||||
DPRINTF("Error in allocating output memory\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(outputBuffer[ii], 0x00, outputTensorDesc[ii].size);
|
||||
}
|
||||
|
||||
unsigned char** statisticsOutputBuffer = (unsigned char **)malloc(sizeof(unsigned char *)*numOutputTaskStatistics);
|
||||
if (statisticsOutputBuffer == NULL) {
|
||||
DPRINTF("Error in allocating memory for output buffer array\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(statisticsOutputBuffer, 0x00, sizeof(unsigned char *)*numOutputTaskStatistics);
|
||||
resourceList.statisticsOutputBuffer = statisticsOutputBuffer;
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTaskStatistics; ii++) {
|
||||
statisticsOutputBuffer[ii] = (unsigned char* )malloc(outputTaskStatisticsDesc[ii].size);
|
||||
if (outputBuffer[ii] == NULL) {
|
||||
DPRINTF("Error in allocating output memory\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(statisticsOutputBuffer[ii], 0x00, outputTaskStatisticsDesc[ii].size);
|
||||
}
|
||||
|
||||
// Allocate memory on GPU.
|
||||
void** inputBufferGPU = (void **)malloc(sizeof(void *)*numInputTensors);
|
||||
if (inputBufferGPU == NULL) {
|
||||
DPRINTF("Error in allocating memory for input buffer GPU array\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(inputBufferGPU, 0x00, sizeof(void *)*numInputTensors);
|
||||
resourceList.inputBufferGPU = inputBufferGPU;
|
||||
|
||||
for (uint32_t ii = 0; ii < numInputTensors; ii++) {
|
||||
result = cudaMalloc(&(inputBufferGPU[ii]), inputTensorDesc[ii].size);
|
||||
if (result != cudaSuccess)
|
||||
{
|
||||
DPRINTF("Error in allocating input memory on GPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
void** outputBufferGPU = (void **)malloc(sizeof(void *)*numOutputTensors);
|
||||
if (outputBufferGPU == NULL) {
|
||||
DPRINTF("Error in allocating memory for output buffer GPU array\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(outputBufferGPU, 0x00, sizeof(void *)*numOutputTensors);
|
||||
resourceList.outputBufferGPU = outputBufferGPU;
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTensors; ii++) {
|
||||
result = cudaMalloc(&(outputBufferGPU[ii]), outputTensorDesc[ii].size);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in allocating output memory on GPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
void** outputTaskStatisticsGPU = (void **)malloc(sizeof(void *)*numOutputTaskStatistics);
|
||||
if (outputTaskStatisticsGPU == NULL) {
|
||||
DPRINTF("Error in allocating memory for output task statistics GPU array\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(outputTaskStatisticsGPU, 0x00, sizeof(void *)*numOutputTaskStatistics);
|
||||
resourceList.outputTaskStatisticsGPU = outputTaskStatisticsGPU;
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTaskStatistics; ii++) {
|
||||
result = cudaMalloc(&(outputTaskStatisticsGPU[ii]), outputTaskStatisticsDesc[ii].size);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in allocating task statistics memory on GPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
uint64_t** inputBufferRegisteredPtr = (uint64_t **)malloc(sizeof(uint64_t*)*numInputTensors);
|
||||
uint64_t** outputBufferRegisteredPtr = (uint64_t **)malloc(sizeof(uint64_t*)*numOutputTensors);
|
||||
uint64_t** outputTaskStatisticsRegisteredPtr = (uint64_t **)malloc(sizeof(uint64_t*)*numOutputTaskStatistics);
|
||||
|
||||
if ((inputBufferRegisteredPtr == NULL) || (outputBufferRegisteredPtr == NULL) || (outputTaskStatisticsRegisteredPtr == NULL)) {
|
||||
if (inputBufferRegisteredPtr != NULL) {
|
||||
free(inputBufferRegisteredPtr);
|
||||
inputBufferRegisteredPtr = NULL;
|
||||
}
|
||||
|
||||
if (outputBufferRegisteredPtr != NULL) {
|
||||
free(outputBufferRegisteredPtr);
|
||||
outputBufferRegisteredPtr = NULL;
|
||||
}
|
||||
|
||||
if (outputTaskStatisticsRegisteredPtr != NULL) {
|
||||
free(outputTaskStatisticsRegisteredPtr);
|
||||
outputTaskStatisticsRegisteredPtr = NULL;
|
||||
}
|
||||
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.inputBufferRegisteredPtr = inputBufferRegisteredPtr;
|
||||
resourceList.outputBufferRegisteredPtr = outputBufferRegisteredPtr;
|
||||
resourceList.outputTaskStatisticsRegisteredPtr = outputTaskStatisticsRegisteredPtr;
|
||||
|
||||
// Register the CUDA-allocated buffers.
|
||||
for (uint32_t ii = 0; ii < numInputTensors; ii++) {
|
||||
err = cudlaMemRegister(devHandle,
|
||||
(uint64_t* )(inputBufferGPU[ii]),
|
||||
inputTensorDesc[ii].size,
|
||||
&(inputBufferRegisteredPtr[ii]),
|
||||
0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering input memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTensors; ii++) {
|
||||
err = cudlaMemRegister(devHandle,
|
||||
(uint64_t* )(outputBufferGPU[ii]),
|
||||
outputTensorDesc[ii].size,
|
||||
&(outputBufferRegisteredPtr[ii]),
|
||||
0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering output memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTaskStatistics; ii++) {
|
||||
err = cudlaMemRegister(devHandle,
|
||||
(uint64_t* )(outputTaskStatisticsGPU[ii]),
|
||||
outputTaskStatisticsDesc[ii].size,
|
||||
&(outputTaskStatisticsRegisteredPtr[ii]),
|
||||
CUDLA_TASK_STATISTICS);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering statistics output memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
DPRINTF("ALL MEMORY REGISTERED SUCCESSFULLY\n");
|
||||
|
||||
// Copy data from CPU buffers to GPU buffers.
|
||||
for (uint32_t ii = 0; ii < numInputTensors; ii++) {
|
||||
result = cudaMemcpyAsync(inputBufferGPU[ii], inputBuffer[ii], inputTensorDesc[ii].size, cudaMemcpyHostToDevice, stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in enqueueing memcpy for input\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTensors; ii++) {
|
||||
result = cudaMemsetAsync(outputBufferGPU[ii], 0, outputTensorDesc[ii].size, stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in enqueueing memset for output\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTaskStatistics; ii++) {
|
||||
result = cudaMemsetAsync(outputTaskStatisticsGPU[ii], 0, outputTaskStatisticsDesc[ii].size, stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in enqueueing memset for statistics output\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
uint64_t *outputStatisticsBufferRegisteredPtr[numOutputTensors + numOutputTaskStatistics] = {0};
|
||||
uint32_t index = 0;
|
||||
for (; index < numOutputTensors ; index++) {
|
||||
outputStatisticsBufferRegisteredPtr[index] = ((outputBufferRegisteredPtr[index]));
|
||||
}
|
||||
|
||||
for (uint32_t jj=0; jj < numOutputTaskStatistics ; jj++) {
|
||||
outputStatisticsBufferRegisteredPtr[index++] = ((outputTaskStatisticsRegisteredPtr[jj]));
|
||||
}
|
||||
|
||||
// Enqueue a cuDLA task.
|
||||
cudlaTask task;
|
||||
task.moduleHandle = moduleHandle;
|
||||
task.outputTensor = (uint64_t * const*)&outputStatisticsBufferRegisteredPtr;
|
||||
|
||||
if(statSupport == 1) {
|
||||
task.numOutputTensors = (numOutputTensors + numOutputTaskStatistics);
|
||||
DPRINTF("Layerwise profiling is requested \n");
|
||||
} else {
|
||||
task.numOutputTensors = numOutputTensors;
|
||||
DPRINTF("Layerwise profiling is not requested \n");
|
||||
}
|
||||
|
||||
task.numInputTensors = numInputTensors;
|
||||
task.inputTensor = inputBufferRegisteredPtr;
|
||||
task.waitEvents = NULL;
|
||||
task.signalEvents = NULL;
|
||||
|
||||
err = cudlaSubmitTask(devHandle, &task, 1, stream, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("no of output tensor %u \n",(task.numOutputTensors));
|
||||
DPRINTF("Error in submitting task\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("SUBMIT IS DONE !!!\n");
|
||||
|
||||
result = cudaStreamSynchronize(stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in synchronizing stream = %s\n", cudaGetErrorName(result));
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
// Wait for stream operations to finish and bring output buffer to CPU.
|
||||
for (uint32_t ii = 0; ii < numOutputTensors; ii++) {
|
||||
result = cudaMemcpyAsync(outputBuffer[ii], outputBufferGPU[ii],
|
||||
outputTensorDesc[ii].size, cudaMemcpyDeviceToHost, stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in bringing result back to CPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
result = cudaStreamSynchronize(stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in synchronizing stream\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
if(statSupport == 1) {
|
||||
// copy statistics data to cpu
|
||||
for (uint32_t ii = 0; ii < numOutputTaskStatistics; ii++) {
|
||||
result = cudaMemcpyAsync(statisticsOutputBuffer[ii], outputTaskStatisticsGPU[ii],
|
||||
outputTaskStatisticsDesc[ii].size, cudaMemcpyDeviceToHost, stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in bringing result back to CPU\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
result = cudaStreamSynchronize(stream);
|
||||
if (result != cudaSuccess) {
|
||||
DPRINTF("Error in synchronizing stream\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
// To get the last index of the filename prefix in which statistics will be dumped
|
||||
uint32_t index = 0;
|
||||
if (argc == 5) {
|
||||
while(argv[4][index]!='\0') {
|
||||
index++;
|
||||
}
|
||||
}
|
||||
|
||||
const cudlaExternalEtbl* etbl = NULL;
|
||||
if (cudlaGetExternalExportTable(&etbl,0) != cudlaSuccess) {
|
||||
DPRINTF("Error in getting export table\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
void** csv = (void **)malloc(sizeof(void *)*numOutputTaskStatistics);
|
||||
if (csv == NULL) {
|
||||
DPRINTF("Error in allocating memory for csv stream\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(csv, 0x00, sizeof(void *)*numOutputTaskStatistics);
|
||||
resourceList.csv = csv;
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTaskStatistics; ii++) {
|
||||
cudlaTranslateCsvAttribute csvAttribute;
|
||||
uint64_t csvStreamLength = 0;
|
||||
|
||||
err = etbl->etiTranslateStats(devHandle,statisticsOutputBuffer[ii],dlaFreqInMHz,ii,CUDLA_GET_CSV_LENGTH,&csvAttribute);
|
||||
csv[ii] = (void* )malloc(csvAttribute.csvStreamLength);
|
||||
csvStreamLength = csvAttribute.csvStreamLength;
|
||||
DPRINTF("size for statistics buffer %u is %lu \n",ii,csvStreamLength);
|
||||
|
||||
if (csv[ii] == NULL) {
|
||||
DPRINTF("Error in allocating memory for csv stream\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
memset(csv[ii], 0x00, csvAttribute.csvStreamLength);
|
||||
|
||||
csvAttribute.csvStreamStats = csv[ii];
|
||||
err = etbl->etiTranslateStats(devHandle,statisticsOutputBuffer[ii],dlaFreqInMHz,ii,CUDLA_GET_CSV_STATS,&csvAttribute);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in translating stats\n");
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
if (argc == 5) {
|
||||
sprintf(filename,"%s%u%s", argv[4],(ii+1),suffix);
|
||||
fp = fopen(filename, "w+");
|
||||
if (fp == NULL) {
|
||||
DPRINTF("Cannot open file %s\n", filename);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
uint32_t ret_val = fwrite(csv[ii],sizeof(char),csvStreamLength,fp);
|
||||
if(ret_val != csvStreamLength) {
|
||||
DPRINTF("number of elements written to file is %u \n", ret_val);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
fclose(fp);
|
||||
} else {
|
||||
DPRINTF("%s \n",(char *)csv[ii]);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// unregister the CUDA-allocated buffers.
|
||||
for (uint32_t ii = 0; ii < numInputTensors; ii++) {
|
||||
err = cudlaMemUnregister(devHandle,
|
||||
(inputBufferRegisteredPtr[ii]));
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering input memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTensors; ii++) {
|
||||
err = cudlaMemUnregister(devHandle,
|
||||
(outputBufferRegisteredPtr[ii]));
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering output memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
for (uint32_t ii = 0; ii < numOutputTaskStatistics; ii++) {
|
||||
err = cudlaMemUnregister(devHandle,
|
||||
(outputTaskStatisticsRegisteredPtr[ii]));
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in registering output memory = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
}
|
||||
|
||||
DPRINTF("ALL MEMORY UNREGISTERED SUCCESSFULLY\n");
|
||||
|
||||
result = cudaStreamDestroy(stream);
|
||||
if (result != cudaSuccess) {
|
||||
errPtr = cudaGetErrorName(result);
|
||||
DPRINTF("Error in destroying cuda stream = %s\n", errPtr);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
}
|
||||
|
||||
resourceList.stream = NULL;
|
||||
|
||||
err = cudlaModuleUnload(moduleHandle, 0);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in cudlaModuleUnload = %d\n", err);
|
||||
cleanUp(&resourceList);
|
||||
return 1;
|
||||
} else {
|
||||
DPRINTF("Successfully unloaded module\n");
|
||||
}
|
||||
|
||||
resourceList.moduleHandle = NULL;
|
||||
|
||||
err = cudlaDestroyDevice(devHandle);
|
||||
if (err != cudlaSuccess) {
|
||||
DPRINTF("Error in cuDLA destroy device = %d\n", err);
|
||||
return 1;
|
||||
}
|
||||
DPRINTF("Device destroyed successfully\n");
|
||||
|
||||
resourceList.devHandle = NULL;
|
||||
|
||||
cleanUp(&resourceList);
|
||||
|
||||
DPRINTF("cuDLALayerwiseStatsHybrid DONE !!!\n");
|
||||
|
||||
return 0;
|
||||
}
|
||||
18
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/.vscode/c_cpp_properties.json
vendored
Normal file
18
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/.vscode/c_cpp_properties.json
vendored
Normal file
|
|
@ -0,0 +1,18 @@
|
|||
{
|
||||
"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
|
||||
}
|
||||
7
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/.vscode/extensions.json
vendored
Normal file
7
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/.vscode/extensions.json
vendored
Normal file
|
|
@ -0,0 +1,7 @@
|
|||
{
|
||||
"recommendations": [
|
||||
"nvidia.nsight-vscode-edition",
|
||||
"ms-vscode.cpptools",
|
||||
"ms-vscode.makefile-tools"
|
||||
]
|
||||
}
|
||||
10
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/.vscode/launch.json
vendored
Normal file
10
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/.vscode/launch.json
vendored
Normal file
|
|
@ -0,0 +1,10 @@
|
|||
{
|
||||
"configurations": [
|
||||
{
|
||||
"name": "CUDA C++: Launch",
|
||||
"type": "cuda-gdb",
|
||||
"request": "launch",
|
||||
"program": "${workspaceFolder}/cuDLALayerwiseStatsStandalone"
|
||||
}
|
||||
]
|
||||
}
|
||||
15
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/.vscode/tasks.json
vendored
Normal file
15
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/.vscode/tasks.json
vendored
Normal file
|
|
@ -0,0 +1,15 @@
|
|||
{
|
||||
"version": "2.0.0",
|
||||
"tasks": [
|
||||
{
|
||||
"label": "sample",
|
||||
"type": "shell",
|
||||
"command": "make dbg=1",
|
||||
"problemMatcher": ["$nvcc"],
|
||||
"group": {
|
||||
"kind": "build",
|
||||
"isDefault": true
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
403
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/Makefile
Normal file
403
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/Makefile
Normal file
|
|
@ -0,0 +1,403 @@
|
|||
################################################################################
|
||||
# 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.
|
||||
#
|
||||
################################################################################
|
||||
#
|
||||
# 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
|
||||
ifdef HOST_COMPILER
|
||||
CUSTOM_HOST_COMPILER = 1
|
||||
endif
|
||||
|
||||
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 += -D_QNX_SOURCE
|
||||
NVCCFLAGS += --qpp-config 8.3.0,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 Linux x86_64
|
||||
ifeq ($(TARGET_OS),linux)
|
||||
ifeq ($(TARGET_ARCH),x86_64)
|
||||
$(info >>> WARNING - cuDLALayerwiseStatsStandalone is not supported on Linux x86_64 - waiving sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
endif
|
||||
|
||||
# This sample is not supported on Mac OSX
|
||||
ifeq ($(TARGET_OS),darwin)
|
||||
$(info >>> WARNING - cuDLALayerwiseStatsStandalone is not supported on Mac OSX - waiving sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
|
||||
# This sample is not supported on ARMv7
|
||||
ifeq ($(TARGET_ARCH),armv7l)
|
||||
$(info >>> WARNING - cuDLALayerwiseStatsStandalone is not supported on ARMv7 - waiving sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
|
||||
# This sample is not supported on sbsa
|
||||
ifeq ($(TARGET_ARCH),sbsa)
|
||||
$(info >>> WARNING - cuDLALayerwiseStatsStandalone is not supported on sbsa - waiving sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
|
||||
ALL_LDFLAGS :=
|
||||
ALL_LDFLAGS += $(ALL_CCFLAGS)
|
||||
ALL_LDFLAGS += $(addprefix -Xlinker ,$(LDFLAGS))
|
||||
ALL_LDFLAGS += $(addprefix -Xlinker ,$(EXTRA_LDFLAGS))
|
||||
|
||||
# Common includes and paths for CUDA
|
||||
INCLUDES := -I../../../Common
|
||||
LIBRARIES :=
|
||||
|
||||
################################################################################
|
||||
|
||||
# Makefile include to help find NVSCI Libraries
|
||||
include ./findnvsci.mk
|
||||
|
||||
#Detect if installed version of GCC supports required C++11
|
||||
ifeq ($(TARGET_OS),linux)
|
||||
empty :=
|
||||
space := $(empty) $(empty)
|
||||
GCCVERSIONSTRING := $(shell expr `$(HOST_COMPILER) -dumpversion`)
|
||||
#Create version number without "."
|
||||
GCCVERSION := $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f1 -d.)
|
||||
GCCVERSION += $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f2 -d.)
|
||||
GCCVERSION += $(shell expr `echo $(GCCVERSIONSTRING)` | cut -f3 -d.)
|
||||
# Make sure the version number has at least 3 decimals
|
||||
GCCVERSION += 00
|
||||
# Remove spaces from the version number
|
||||
GCCVERSION := $(subst $(space),$(empty),$(GCCVERSION))
|
||||
#$(warning $(GCCVERSION))
|
||||
|
||||
IS_MIN_VERSION := $(shell expr `echo $(GCCVERSION)` \>= 47000)
|
||||
ifneq ($(CUSTOM_HOST_COMPILER), 1)
|
||||
ifeq ($(IS_MIN_VERSION), 1)
|
||||
$(info >>> GCC Version is greater or equal to 4.7.0 <<<)
|
||||
else
|
||||
$(info >>> Waiving build. Minimum GCC version required is 4.7.0<<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
else
|
||||
$(warning >>> Custom HOST_COMPILER set; skipping GCC version check. This may lead to unintended behavior. Please note the minimum equivalent GCC version is 4.7.0 <<<)
|
||||
endif
|
||||
endif
|
||||
|
||||
# Gencode arguments
|
||||
ifeq ($(TARGET_ARCH),$(filter $(TARGET_ARCH),armv7l aarch64 sbsa))
|
||||
SMS ?= 53 61 70 72 75 80 86 87 90
|
||||
else
|
||||
SMS ?= 50 52 60 61 70 75 80 86 89 90
|
||||
endif
|
||||
|
||||
ifeq ($(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 += --std=c++11 --threads 0
|
||||
|
||||
LIBRARIES += -lcudla -lnvscibuf -lnvscisync
|
||||
|
||||
ifeq ($(SAMPLE_ENABLED),0)
|
||||
EXEC ?= @echo "[@]"
|
||||
endif
|
||||
|
||||
################################################################################
|
||||
|
||||
# Target rules
|
||||
all: build
|
||||
|
||||
build: cuDLALayerwiseStatsStandalone
|
||||
|
||||
check.deps:
|
||||
ifeq ($(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
|
||||
|
||||
main.o:main.cpp
|
||||
$(EXEC) $(NVCC) $(INCLUDES) $(ALL_CCFLAGS) $(GENCODE_FLAGS) -o $@ -c $<
|
||||
|
||||
cuDLALayerwiseStatsStandalone: main.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
|
||||
$(EXEC) ./cuDLALayerwiseStatsStandalone
|
||||
|
||||
testrun: build
|
||||
|
||||
clean:
|
||||
rm -f cuDLALayerwiseStatsStandalone main.o
|
||||
rm -rf ../../../bin/$(TARGET_ARCH)/$(TARGET_OS)/$(BUILD_TYPE)/cuDLALayerwiseStatsStandalone
|
||||
|
||||
clobber: clean
|
||||
|
|
@ -0,0 +1,65 @@
|
|||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<!DOCTYPE entry SYSTEM "SamplesInfo.dtd">
|
||||
<entry>
|
||||
<name>cuDLALayerwiseStatsStandalone</name>
|
||||
<cflags>
|
||||
<flag>--std=c++11</flag>
|
||||
</cflags>
|
||||
<description><![CDATA[This sample is used to provide layerwise statistics to the application in cuDLA standalone mode where DLA is programmed without using CUDA.]]></description>
|
||||
<devicecompilation>whole</devicecompilation>
|
||||
<includepaths>
|
||||
<path>./</path>
|
||||
<path>../</path>
|
||||
<path>../../../Common</path>
|
||||
</includepaths>
|
||||
<keyconcepts>
|
||||
<concept level="basic">cuDLA</concept>
|
||||
<concept level="advanced">Data Parallel Algorithms</concept>
|
||||
<concept level="advanced">Image Processing</concept>
|
||||
</keyconcepts>
|
||||
<keywords>
|
||||
<keyword>CUDA</keyword>
|
||||
<keyword>CPP11</keyword>
|
||||
</keywords>
|
||||
<libraries>
|
||||
<library>cudla</library>
|
||||
<library>nvscibuf</library>
|
||||
<library>nvscisync</library>
|
||||
</libraries>
|
||||
<librarypaths>
|
||||
</librarypaths>
|
||||
<nsight_eclipse>true</nsight_eclipse>
|
||||
<primary_file>main.cpp</primary_file>
|
||||
<required_dependencies>
|
||||
<dependency>NVSCI</dependency>
|
||||
</required_dependencies>
|
||||
<scopes>
|
||||
<scope>1:CUDA Advanced Topics</scope>
|
||||
<scope>1:cuDLA</scope>
|
||||
</scopes>
|
||||
<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>aarch64</arch>
|
||||
<platform>linux</platform>
|
||||
</env>
|
||||
<env>
|
||||
<arch>aarch64</arch>
|
||||
<platform>qnx</platform>
|
||||
</env>
|
||||
</supported_envs>
|
||||
<supported_sm_architectures>
|
||||
<from>6.0</from>
|
||||
</supported_sm_architectures>
|
||||
<title>cuDLA Layerwise Statistics Standalone Mode</title>
|
||||
<type>exe</type>
|
||||
</entry>
|
||||
|
|
@ -0,0 +1,61 @@
|
|||
# cuDLALayerwiseStatsStandalone - cuDLA Layerwise Statistics Standalone Mode
|
||||
|
||||
## Description
|
||||
|
||||
This sample is used to provide layerwise statistics to the application in cuDLA standalone mode where DLA is programmed without using CUDA.
|
||||
|
||||
## Key Concepts
|
||||
|
||||
cuDLA, Data Parallel Algorithms, Image Processing
|
||||
|
||||
## Supported SM Architectures
|
||||
|
||||
[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, QNX
|
||||
|
||||
## Supported CPU Architecture
|
||||
|
||||
aarch64
|
||||
|
||||
## CUDA APIs involved
|
||||
|
||||
## Dependencies needed to build/run
|
||||
[NVSCI](../../../README.md#nvsci)
|
||||
|
||||
## Prerequisites
|
||||
|
||||
Download and install the [CUDA Toolkit 12.2](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
|
||||
Make sure the dependencies mentioned in [Dependencies]() section above are installed.
|
||||
|
||||
## Build and Run
|
||||
|
||||
### 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 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=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)
|
||||
|
||||
|
|
@ -0,0 +1,144 @@
|
|||
################################################################################
|
||||
# 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.
|
||||
#
|
||||
#################################################################################
|
||||
# findnvsci.mk is used to find the NVSCI Libraries and headers
|
||||
#
|
||||
################################################################################
|
||||
|
||||
# Determine OS platform and unix distribution
|
||||
ifeq ("$(TARGET_OS)","linux")
|
||||
# first search lsb_release
|
||||
DISTRO = $(shell lsb_release -i -s 2>/dev/null | tr "[:upper:]" "[:lower:]")
|
||||
ifeq ("$(DISTRO)","")
|
||||
# second search and parse /etc/issue
|
||||
DISTRO = $(shell more /etc/issue | awk '{print $$1}' | sed '1!d' | sed -e "/^$$/d" 2>/dev/null | tr "[:upper:]" "[:lower:]")
|
||||
# ensure data from /etc/issue is valid
|
||||
ifeq (,$(filter $(DISTRO),ubuntu fedora red rhel centos suse))
|
||||
DISTRO =
|
||||
endif
|
||||
ifeq ("$(DISTRO)","")
|
||||
# third, we can search in /etc/os-release or /etc/{distro}-release
|
||||
DISTRO = $(shell awk '/ID/' /etc/*-release | sed 's/ID=//' | grep -v "VERSION" | grep -v "ID" | grep -v "DISTRIB")
|
||||
endif
|
||||
endif
|
||||
endif
|
||||
|
||||
ifeq ("$(TARGET_OS)","linux")
|
||||
# $(info) >> findegl.mk -> LINUX path <<<)
|
||||
# Each set of Linux Distros have different paths for where to find their OpenGL libraries reside
|
||||
UBUNTU = $(shell echo $(DISTRO) | grep -i ubuntu >/dev/null 2>&1; echo $$?)
|
||||
FEDORA = $(shell echo $(DISTRO) | grep -i fedora >/dev/null 2>&1; echo $$?)
|
||||
RHEL = $(shell echo $(DISTRO) | grep -i 'red\|rhel' >/dev/null 2>&1; echo $$?)
|
||||
CENTOS = $(shell echo $(DISTRO) | grep -i centos >/dev/null 2>&1; echo $$?)
|
||||
SUSE = $(shell echo $(DISTRO) | grep -i 'suse\|sles' >/dev/null 2>&1; echo $$?)
|
||||
KYLIN = $(shell echo $(DISTRO) | grep -i kylin >/dev/null 2>&1; echo $$?)
|
||||
ifeq ("$(UBUNTU)","0")
|
||||
ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-armv7l)
|
||||
GLPATH := /usr/arm-linux-gnueabihf/lib
|
||||
GLLINK := -L/usr/arm-linux-gnueabihf/lib
|
||||
ifneq ($(TARGET_FS),)
|
||||
GLPATH += $(TARGET_FS)/usr/lib/arm-linux-gnueabihf
|
||||
GLLINK += -L$(TARGET_FS)/usr/lib/arm-linux-gnueabihf
|
||||
endif
|
||||
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH),x86_64-aarch64)
|
||||
GLPATH := /usr/aarch64-linux-gnu/lib
|
||||
GLLINK := -L/usr/aarch64-linux-gnu/lib
|
||||
ifneq ($(TARGET_FS),)
|
||||
GLPATH += $(TARGET_FS)/usr/lib
|
||||
GLPATH += $(TARGET_FS)/usr/lib/aarch64-linux-gnu
|
||||
GLLINK += -L$(TARGET_FS)/usr/lib/aarch64-linux-gnu
|
||||
endif
|
||||
else
|
||||
UBUNTU_PKG_NAME = $(shell which dpkg >/dev/null 2>&1 && dpkg -l 'nvidia-*' | grep '^ii' | awk '{print $$2}' | head -1)
|
||||
ifneq ("$(UBUNTU_PKG_NAME)","")
|
||||
GLPATH ?= /usr/lib/$(UBUNTU_PKG_NAME)
|
||||
GLLINK ?= -L/usr/lib/$(UBUNTU_PKG_NAME)
|
||||
endif
|
||||
DFLT_PATH ?= /usr/lib
|
||||
endif
|
||||
endif
|
||||
ifeq ("$(SUSE)","0")
|
||||
GLPATH ?= /usr/X11R6/lib64
|
||||
GLLINK ?= -L/usr/X11R6/lib64
|
||||
DFLT_PATH ?= /usr/lib64
|
||||
endif
|
||||
ifeq ("$(FEDORA)","0")
|
||||
GLPATH ?= /usr/lib64/nvidia
|
||||
GLLINK ?= -L/usr/lib64/nvidia
|
||||
DFLT_PATH ?= /usr/lib64
|
||||
endif
|
||||
ifeq ("$(RHEL)","0")
|
||||
GLPATH ?= /usr/lib64/nvidia
|
||||
GLLINK ?= -L/usr/lib64/nvidia
|
||||
DFLT_PATH ?= /usr/lib64
|
||||
endif
|
||||
ifeq ("$(CENTOS)","0")
|
||||
GLPATH ?= /usr/lib64/nvidia
|
||||
GLLINK ?= -L/usr/lib64/nvidia
|
||||
DFLT_PATH ?= /usr/lib64
|
||||
endif
|
||||
ifeq ("$(KYLIN)","0")
|
||||
GLPATH ?= /usr/lib64/nvidia
|
||||
GLLINK ?= -L/usr/lib64/nvidia
|
||||
DFLT_PATH ?= /usr/lib64
|
||||
endif
|
||||
|
||||
NVSCIBUFLIB := $(shell find -L $(GLPATH) $(DFLT_PATH) -name libnvscibuf.so -print 2>/dev/null)
|
||||
NVSCISYNCLIB := $(shell find -L $(GLPATH) $(DFLT_PATH) -name libnvscisync.so -print 2>/dev/null)
|
||||
|
||||
ifeq ("$(NVSCIBUFLIB)","")
|
||||
$(info >>> WARNING - libnvscibuf.so not found, Waiving the sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
|
||||
ifeq ("$(NVSCISYNCLIB)","")
|
||||
$(info >>> WARNING - libnvscisync.so not found, Waiving the sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
|
||||
HEADER_SEARCH_PATH ?= $(TARGET_FS)/usr/include
|
||||
ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-armv7l-linux)
|
||||
HEADER_SEARCH_PATH += /usr/arm-linux-gnueabihf/include
|
||||
else ifeq ($(HOST_ARCH)-$(TARGET_ARCH)-$(TARGET_OS),x86_64-aarch64-linux)
|
||||
HEADER_SEARCH_PATH += /usr/aarch64-linux-gnu/include
|
||||
endif
|
||||
|
||||
NVSCIBUFHEADER := $(shell find -L $(HEADER_SEARCH_PATH) -name nvscibuf.h -print 2>/dev/null)
|
||||
NVSCISYNCHEADER := $(shell find -L $(HEADER_SEARCH_PATH) -name nvscisync.h -print 2>/dev/null)
|
||||
|
||||
ifeq ("$(NVSCIBUFHEADER)","")
|
||||
$(info >>> WARNING - nvscibuf.h not found, Waiving the sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
ifeq ("$(NVSCISYNCHEADER)","")
|
||||
$(info >>> WARNING - nvscisync.h not found, Waiving the sample <<<)
|
||||
SAMPLE_ENABLED := 0
|
||||
endif
|
||||
else
|
||||
endif
|
||||
|
||||
1348
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/main.cpp
Normal file
1348
Samples/4_CUDA_Libraries/cuDLALayerwiseStatsStandalone/main.cpp
Normal file
File diff suppressed because it is too large
Load Diff
|
|
@ -552,7 +552,6 @@ int main(int argc, char *argv[]) {
|
|||
checkCudaErrors(cusparseScatter(cusparseHandle, vecz, vecx));
|
||||
checkCudaErrors(cusparseDestroySpVec(vecz));
|
||||
|
||||
|
||||
checkCudaErrors(cudaDeviceSynchronize());
|
||||
|
||||
stop = second();
|
||||
|
|
|
|||
|
|
@ -31,12 +31,13 @@
|
|||
* https://vulkan-tutorial.com/
|
||||
*/
|
||||
|
||||
#include <stdexcept>
|
||||
#include <iostream>
|
||||
#include <fstream>
|
||||
#include <algorithm>
|
||||
#include <fstream>
|
||||
#include <functional>
|
||||
#include <iostream>
|
||||
#include <limits>
|
||||
#include <set>
|
||||
#include <stdexcept>
|
||||
#include <string.h>
|
||||
|
||||
#include "VulkanBaseApp.h"
|
||||
|
|
|
|||
|
|
@ -31,14 +31,16 @@
|
|||
* https://vulkan-tutorial.com/
|
||||
*/
|
||||
|
||||
#include <stdexcept>
|
||||
#include <iostream>
|
||||
#include <fstream>
|
||||
#include <algorithm>
|
||||
#include <fstream>
|
||||
#include <functional>
|
||||
#include <iostream>
|
||||
#include <limits>
|
||||
#include <set>
|
||||
#include <stdexcept>
|
||||
#include <string.h>
|
||||
|
||||
|
||||
#include "VulkanBaseApp.h"
|
||||
#include "VulkanCudaInterop.h"
|
||||
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user