initial build

This commit is contained in:
Roland Grinis 2021-06-27 22:12:02 +01:00
parent 84937ecaca
commit 95d2b5b8d9
8 changed files with 195 additions and 19 deletions

View File

@ -18,14 +18,8 @@ the [GNU](https://gcc.gnu.org/) toolchain. For `GPU` kernels, we require a compa
installation. If you are on Windows, we recommend setting up installation. If you are on Windows, we recommend setting up
everything on [WSL](https://docs.nvidia.com/cuda/wsl-user-guide/index.html). everything on [WSL](https://docs.nvidia.com/cuda/wsl-user-guide/index.html).
To install the library, you have to publish To install the library, simply publish it locally:
locally `kmath-core`, `kmath-tensors` with `kmath-noa`:
``` ```
./gradlew -q :kmath-core:publishToMavenLocal :kmath-tensors:publishToMavenLocal :kmath-noa:publishToMavenLocal ./gradlew -q :kmath-noa:publishToMavenLocal
``` ```
This builds `jtorch` a JNI wrapper for `NOA/LibTorch`, placed inside:
`~/.konan/third-party/kmath-noa-<version>/cpp-build`

View File

@ -27,23 +27,32 @@ val cppSources = projectDir.resolve("src/main/cpp")
val cudaHome: String? = System.getenv("CUDA_HOME") val cudaHome: String? = System.getenv("CUDA_HOME")
val cudaDefault = file("/usr/local/cuda").exists() val cudaDefault = file("/usr/local/cuda").exists()
val cudaFound = cudaHome?.isNotEmpty() ?: false or cudaDefault val cudaFound = cudaHome?.isNotEmpty() ?: false or cudaDefault
val cmakeArchive = "cmake-3.20.5-linux-x86_64"
val cmakeArchive = "cmake-3.20.5-Linux-x86_64"
val torchArchive = "libtorch" val torchArchive = "libtorch"
val cmakeCmd = "$thirdPartyDir/$cmakeArchive/bin/cmake" val cmakeCmd = "$thirdPartyDir/cmake/$cmakeArchive/bin/cmake"
val ninjaCmd = "$thirdPartyDir/ninja" val ninjaCmd = "$thirdPartyDir/ninja/ninja"
val generateJNIHeader by tasks.registering {
println(cmakeCmd)
doLast {
exec {
workingDir(projectDir.resolve("src/main/java/space/kscience/kmath/noa"))
commandLine("$javaHome/bin/javac", "-h", cppSources , "JNoa.java")
}
}
}
val downloadCMake by tasks.registering(Download::class) { val downloadCMake by tasks.registering(Download::class) {
val tarFile = "$cmakeArchive.tar.gz" val tarFile = "$cmakeArchive.tar.gz"
src("https://github.com/Kitware/CMake/releases/download/v3.20.5/$tarFile") src("https://github.com/Kitware/CMake/releases/download/v3.20.5/$tarFile")
dest(File(thirdPartyDir, tarFile)) dest(File("$thirdPartyDir/cmake", tarFile))
overwrite(false) overwrite(false)
} }
val downloadNinja by tasks.registering(Download::class) { val downloadNinja by tasks.registering(Download::class) {
src("https://github.com/ninja-build/ninja/releases/download/v1.10.2/ninja-linux.zip") src("https://github.com/ninja-build/ninja/releases/download/v1.10.2/ninja-linux.zip")
dest(File(thirdPartyDir, "ninja-linux.zip")) dest(File("$thirdPartyDir/ninja", "ninja-linux.zip"))
overwrite(false) overwrite(false)
} }
@ -53,24 +62,72 @@ val downloadTorch by tasks.registering(Download::class) {
val cpuUrl = "https://download.pytorch.org/libtorch/cpu/${torchVersion}cpu.zip" val cpuUrl = "https://download.pytorch.org/libtorch/cpu/${torchVersion}cpu.zip"
val url = if (cudaFound) cudaUrl else cpuUrl val url = if (cudaFound) cudaUrl else cpuUrl
src(url) src(url)
dest(File(thirdPartyDir, "$torchArchive.zip")) dest(File("$thirdPartyDir/torch", "$torchArchive.zip"))
overwrite(false) overwrite(false)
} }
val extractCMake by tasks.registering(Copy::class) { val extractCMake by tasks.registering(Copy::class) {
dependsOn(downloadCMake) dependsOn(downloadCMake)
from(tarTree(resources.gzip(downloadCMake.get().dest))) from(tarTree(resources.gzip(downloadCMake.get().dest)))
into(thirdPartyDir) into("$thirdPartyDir/cmake")
} }
val extractNinja by tasks.registering(Copy::class) { val extractNinja by tasks.registering(Copy::class) {
dependsOn(downloadNinja) dependsOn(downloadNinja)
from(zipTree(downloadNinja.get().dest)) from(zipTree(downloadNinja.get().dest))
into(thirdPartyDir) into("$thirdPartyDir/ninja")
} }
val extractTorch by tasks.registering(Copy::class) { val extractTorch by tasks.registering(Copy::class) {
dependsOn(downloadTorch) dependsOn(downloadTorch)
from(zipTree(downloadTorch.get().dest)) from(zipTree(downloadTorch.get().dest))
into(thirdPartyDir) into("$thirdPartyDir/torch")
} }
val configureCpp by tasks.registering {
dependsOn(extractCMake)
dependsOn(extractNinja)
dependsOn(extractTorch)
onlyIf { !file(cppBuildDir).exists() }
doLast {
exec {
workingDir(thirdPartyDir)
commandLine("mkdir", "-p", cppBuildDir)
}
exec {
workingDir(cppBuildDir)
commandLine(
cmakeCmd,
cppSources,
"-GNinja",
"-DCMAKE_MAKE_PROGRAM=$ninjaCmd",
"-DCMAKE_PREFIX_PATH=$thirdPartyDir/torch/$torchArchive",
"-DJAVA_HOME=$javaHome",
"-DCMAKE_BUILD_TYPE=Release",
"-DBUILD_NOA_CUDA=${if(!cudaFound) "ON" else "OFF"}"
)
}
}
}
val cleanCppBuild by tasks.registering {
onlyIf { file(cppBuildDir).exists() }
doLast {
exec {
workingDir(thirdPartyDir)
commandLine("rm", "-rf", cppBuildDir)
}
}
}
val buildCpp by tasks.registering {
dependsOn(configureCpp)
doLast {
exec {
workingDir(cppBuildDir)
commandLine(cmakeCmd, "--build", ".", "--config", "Release")
}
}
}
tasks["compileJava"].dependsOn(buildCpp)

View File

@ -0,0 +1,37 @@
cmake_minimum_required(VERSION 3.12)
project(JNOA LANGUAGES C CXX)
# Require C++17
set(CMAKE_CXX_STANDARD 17)
find_package(Torch REQUIRED)
find_package(JNI REQUIRED)
include(FetchContent)
if(NOT TARGET noa)
FetchContent_Declare(
noa
GIT_REPOSITORY https://github.com/grinisrit/noa.git
GIT_TAG kmath)
FetchContent_GetProperties(noa)
if(NOT noa_POPULATED)
FetchContent_Populate(noa)
set(INSTALL_NOA OFF CACHE BOOL "")
set(BUILD_NOA_TESTS OFF CACHE BOOL "")
set(BUILD_NOA_BENCHMARKS OFF CACHE BOOL "")
add_subdirectory(
${noa_SOURCE_DIR}
${noa_BINARY_DIR})
endif()
endif()
add_library(jnoa SHARED jnoa.cc)
target_include_directories(jnoa PRIVATE ${JNI_INCLUDE_DIRS})
target_link_libraries(jnoa PRIVATE torch NOA::NOA)
target_compile_options(jnoa PRIVATE -Wall -Wextra -Wpedantic -O3 -fPIC)

View File

@ -0,0 +1,17 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
#include <noa/ghmc.hh>
#include <torch/torch.h>
#include "space_kscience_kmath_noa_JNoa.h"
JNIEXPORT jboolean JNICALL Java_space_kscience_kmath_noa_JNoa_cudaIsAvailable(JNIEnv *, jclass)
{
return torch::cuda::is_available();
}

View File

@ -0,0 +1,21 @@
/* DO NOT EDIT THIS FILE - it is machine generated */
#include <jni.h>
/* Header for class space_kscience_kmath_noa_JNoa */
#ifndef _Included_space_kscience_kmath_noa_JNoa
#define _Included_space_kscience_kmath_noa_JNoa
#ifdef __cplusplus
extern "C" {
#endif
/*
* Class: space_kscience_kmath_noa_JNoa
* Method: cudaIsAvailable
* Signature: ()Z
*/
JNIEXPORT jboolean JNICALL Java_space_kscience_kmath_noa_JNoa_cudaIsAvailable
(JNIEnv *, jclass);
#ifdef __cplusplus
}
#endif
#endif

View File

@ -0,0 +1,24 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.noa;
public class JNoa {
static {
String jNoaPath = System.getProperty("user.home") +
"/.konan/third-party/kmath-noa-0.3.0-dev-14/cpp-build/libjnoa.so";
try {
System.load(jNoaPath);
} catch (UnsatisfiedLinkError e) {
System.err.println("Failed to load native NOA library from:\n" +
jNoaPath +"\n" + e);
System.exit(1);
}
}
public static native boolean cudaIsAvailable();
}

View File

@ -0,0 +1,10 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.noa
public fun cudaAvailable(): Boolean {
return JNoa.cudaIsAvailable()
}

View File

@ -0,0 +1,16 @@
/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
package space.kscience.kmath.noa
import kotlin.test.Test
class TestUtils {
@Test
fun checkCuda() {
println(cudaAvailable())
}
}