技术与工具 – California Sunshine

CUDA Development with CLion

CLion from JetBrains provides very good support on CUDA development. This post will mainly talk about how to create a CUDA project in CLion in Windows and how to solve problem when using CUDA 11.2.

Prerequisites

Before creating CUDA project in CLion, please install the following softwares.

CUDA Toolkit 11.2 for Windows. Check this link.
Visual Studio 2019 Community. Check this link.

After installation, in CLion, make sure your Toolchain’s architecture is amd64.

Create CUDA Project In CLion

When creating new project in CLion, simply select “CUDA Executable” as the template.

Let’s modify the default main.cu and test if CUDA is working.

#include <iostream>

using namespace std;

static void HandleError( cudaError_t err,
                         const char *file,
                         int line ) {
    if (err != cudaSuccess) {
        printf( "%s in %s at line %d\n", cudaGetErrorString( err ),
                file, line );
        exit( EXIT_FAILURE );
    }
}
#define HANDLE_ERROR( err ) (HandleError( err, __FILE__, __LINE__ ))

__global__ void add(int a, int b, int* c) {
    *c = a + b;
}

int main() {
    int count;
    HANDLE_ERROR(cudaGetDeviceCount(&count));

    cout << "Found " << count << " device(s)" << endl;

    for (int i = 0; i < count; ++i) {
        cudaDeviceProp prop;

        HANDLE_ERROR(cudaGetDeviceProperties(&prop, i));
        cout << "Device name: " << prop.name << endl;
        cout << "Total Memory: " << prop.totalGlobalMem / 1024.0 / 1024.0 << "MB" << endl;
        cout << "Max Threads per Block: " << prop.maxThreadsPerBlock << endl;
        cout << "Compute capability: " << prop.major << "." << prop.minor << endl;
    }

    int result;
    int* devResult;

    HANDLE_ERROR(cudaMalloc((void**)&devResult, sizeof(int)));

    add<<<1, 1>>>(7, 8, devResult);

    HANDLE_ERROR(cudaMemcpy(&result, devResult, sizeof(int), cudaMemcpyDeviceToHost));

    cout << "7 + 8 = " << result << endl;

    cudaFree(devResult);

    return 0;
}

#include <iostream>

using namespace std;

static void HandleError( cudaError_t err,

const char *file,

int line ) {

if (err != cudaSuccess) {

printf( "%s in %s at line %d\n", cudaGetErrorString( err ),

file, line );

exit( EXIT_FAILURE );

}

#define HANDLE_ERROR( err ) (HandleError( err, __FILE__, __LINE__ ))

__global__ void add(int a, int b, int* c) {

*c = a + b;

}

int main() {

int count;

HANDLE_ERROR(cudaGetDeviceCount(&count));

cout << "Found " << count << " device(s)" << endl;

for (int i = 0; i < count; ++i) {

cudaDeviceProp prop;

HANDLE_ERROR(cudaGetDeviceProperties(&prop, i));

cout << "Device name: " << prop.name << endl;

cout << "Total Memory: " << prop.totalGlobalMem / 1024.0 / 1024.0 << "MB" << endl;

cout << "Max Threads per Block: " << prop.maxThreadsPerBlock << endl;

cout << "Compute capability: " << prop.major << "." << prop.minor << endl;

}

int result;

int* devResult;

HANDLE_ERROR(cudaMalloc((void**)&devResult, sizeof(int)));

add<<<1, 1>>>(7, 8, devResult);

HANDLE_ERROR(cudaMemcpy(&result, devResult, sizeof(int), cudaMemcpyDeviceToHost));

cout << "7 + 8 = " << result << endl;

cudaFree(devResult);

return 0;

}

After build and run, you should see the following output.

H:\source\CLionProjects\CudaInLion\cmake-build-debug\CudaInLion.exe
Found 1 device(s)
Device name: GeForce GTX 970
Total Memory: 4096MB
Max Threads per Block: 1024
Compute capability: 5.2
7 + 8 = 15

H:\source\CLionProjects\CudaInLion\cmake-build-debug\CudaInLion.exe

Found 1 device(s)

Device name: GeForce GTX 970

Total Memory: 4096MB

Max Threads per Block: 1024

Compute capability: 5.2

7 + 8 = 15

Now CUDA is working in CLion project!

Trouble shooting

When having the issue related to vcvars64.bat…

At the beginning, I got the following issue

“Could not set up the environment for Microsoft Visual Studio using ‘C:/Program Files (x86)/Microsoft Visual Studio/2019/Community/VC/Tools/MSVC/14.26.28801/bin/HostX64/x64/../../../../../../../VC/Auxiliary/Build/vcvars64.bat’

After some searching, the problem is due to %PATH% is too long. You need to remove the unnecessary paths from %PATH%. Actually, if you see any double quote in %PATH%, please also remove them.

When having the issue “Use of undeclared identifier cudaConfigureCall“

I also saw the following issue,

You probably are using CUDA 11. In this version, the version.txt file was removed. Instead, version.json was introduced. To solve this issue, you can simply create a version.txt with following context and copy it to where the CUDA is installed.

CUDA Version 11.2

1	CUDA Version 11.2

After opening the CLion, the problem will be gone.

References

Mindmap of Mongodb

Build NPM Proxy Server on Nexus OSS 3.21

I had good experience with Nexus OSS 2.x and it was very easy to use. Based on it, the team built up Maven proxy server and Java private repository. The server had been served for many years and it helped team to finish thousands of builds without any problem.

To have better NPM repository support, it’s time to upgrade to a newer version of Nexus. Compared with JFrog’s Artifactory OSS, NPM and Gradle repository support is included in Nexus OSS version already.

Installation

The latest Nexus OSS version can be download from here. Unzip it and go to /bin folder to start it. I am using Windows 10, so Nexus OSS can be installed as a Windows Service. Then you can start/stop the Nexus OSS server in Services Management.

./nexus.exe install

1	./nexus.exe install

When server starts, you can access the web page, default is http://localhost:8081.

Note: For the first time run, there needs to update the admin user’s password. Follow the instructions to finish it.

Create NPM repository

By default, there are Maven repo (can be used by Gradle as well) and NuGet repo. To have a NPM repo, you need to manually create it.

Use “admin” to log into Nexus, Open “Repositories” page and click “Create repository“.

Select “npm proxy” in the Recipe list,

Put a name of the repository, such as “npm-all” and the “remote storage”.

Click “Create repository” to finish the creation. Now a npm proxy server is ready for serving. The repo URL is http://localhost:8081/repository/npm-all/.

NPM and Yarn Configuration

For npm and yarn, you can use the following commands to use this proxy server respectively.

# npm
npm config set registry http://localhost:8081/repository/npm-all/

# yarn
yarn config set registry http://localhost:8081/repository/npm-all/

# npm

npm config set registry http://localhost:8081/repository/npm-all/

# yarn

yarn config set registry http://localhost:8081/repository/npm-all/

All done!

Sonarqube API design I

Some notes about Sonarqube API design – need it to inject PCLint repository from sonar-cxx to Sonarqube Enterprise Edition.

Bytecode Editor – a good plugin of IDEA

偶然的机会发现在一个好用的IDEA插件－－Bytecode Editor，可以用来快速的修改Java的字节码。推荐大家试试！记得点左上角的重编译按钮哦。

Use Atlassian Confluence API to Copy and Create New Pages

For team management, we have a Confluence space to do weekly reporting. In that space, usually, one page is for a week and each page has the same template. So to copy these pages becomes a very boring work. No worries, there are Confluence APIs to help.

Installation and Connection to Confluence

Very simple and pip will help to finish everything.

pip install atlassian-python-api

1	pip install atlassian-python-api

After installation, use the following code to connect to Confluence.

from atlassian import Confluence

confluence = Confluence(
    url='http://localhost:8090',
    username='your_user_name',
    password='your_passwd',
    verify_ssl=False) # in my case, I ignored the SSL verification

from atlassian import Confluence

confluence = Confluence(

url='http://localhost:8090',

username='your_user_name',

password='your_passwd',

verify_ssl=False) # in my case, I ignored the SSL verification

Copy and Create New Page

Before creating new page, you need to get the body content of the template page.

# retrieve the page id.
page_id = confluence.get_page_id("space_a", "template page name")

# retrieve the page, including its content.
page = confluence.get_page_by_id(page_id, expand='body.storage')

# the body HTML.
print(page['body']['storage']['value'])

# retrieve the page id.

page_id = confluence.get_page_id("space_a", "template page name")

# retrieve the page, including its content.

page = confluence.get_page_by_id(page_id, expand='body.storage')

# the body HTML.

print(page['body']['storage']['value'])

Pay attention to the expand=’body.storage’. Without it, the returned page only contains the basic information, no body HTML.

Now you have the body and the rest work is a just for-loop.

for i in range(1, 53):
    print('Creating page for ww{}'.format(i))
    
    # use the same above to retrieve the parent page's id.
    confluence.create_page('', '2019 WW({})'.format(i), content, parent_id=34511303)
    time.sleep(1)

for i in range(1, 53):

print('Creating page for ww{}'.format(i))

# use the same above to retrieve the parent page's id.

confluence.create_page('', '2019 WW({})'.format(i), content, parent_id=34511303)

time.sleep(1)

Also you can use confluence.update_page() to update some existing pages.

References

Install Ubuntu 16.04 into Raspberry Pi 3 B+

After some investigation, I finally figured out how to install Ubuntu 16.04 into the new Raspberry Pi 3 B+.

Because the bootloader has been updated, with existing Ubuntu 16.04 images, Raspberry Pi 3 B+ can’t be booted. You will be stuck at the rainbow screen.

To fix it, the bootloader and some other driver files needs to be replaced. Here are the detailed instructions.