how can i use cuda with nodejs

Cuda is Nivida provided api that lets c/c++ use gpu for some stuff, even though i don't what that some stuff is & would like to know, from what i saw the gains were remarkable. Also cuda only works for nivida gpus...

There does exist a module for nodejs, but it's only for 64bit version of windows, yet there exists cuda for 32bit version as well so only thing missing binding/extension for nodejs to cuda in c++. And There is no sign of documents anywhere on github or internet about that module. Last commits were like 1/2 year+ ago.

If it's all possible than it'd be very great. As nodejs would be able to use gpu for operations, putting it in the whole new level for web stuff, and other applications. Also given parallel nature of nodejs it fits perfectly with gpu's parallel nature.

Suppose there is no module that exists right now. What are my choices.

it's been done already by someone else: http://www.cs.cmu.edu/afs/cs/academic/class/15418-s12/www/competition/r2jitu.com/418/final_report.pdf

user2129444.. 10

这是一个binding.gyp文件,它将使用两个源文件hello.cpp,goodby.cu和goodby1.cu构建节点扩展.

{
  ## for windows, be sure to do node-gyp rebuild -msvs_version=2013, 
  ## and run under a msvs shell

  ## for all targets 
  'conditions': [
    [ 'OS=="win"', {'variables': {'obj': 'obj'}}, 
    {'variables': {'obj': 'o'}}]],

  "targets": [
{
 "target_name": "hello",
 "sources": [ "hello.cpp", "goodby.cu", "goodby1.cu",], 

 'rules': [{
     'extension': 'cu',           
     'inputs': ['<(RULE_INPUT_PATH)'],
     'outputs':[ '<(INTERMEDIATE_DIR)/<(RULE_INPUT_ROOT).<(obj)'],
     'conditions': [
      [ 'OS=="win"',  
        {'rule_name': 'cuda on windows',
         'message': "compile cuda file on windows",
         'process_outputs_as_sources': 0,
         'action': ['nvcc -c <(_inputs) -o  <(_outputs)'],
         }, 
       {'rule_name': 'cuda on linux',
         'message': "compile cuda file on linux",
         'process_outputs_as_sources': 1,
         'action': ['nvcc','-Xcompiler','-fpic','-c',
            '<@(_inputs)','-o','<@(_outputs)'],
    }]]}],

   'conditions': [
    [ 'OS=="mac"', {
      'libraries': ['-framework CUDA'],
      'include_dirs': ['/usr/local/include'],
      'library_dirs': ['/usr/local/lib'],
    }],
    [ 'OS=="linux"', {
      'libraries': ['-lcuda', '-lcudart'],
      'include_dirs': ['/usr/local/include'],
      'library_dirs': ['/usr/local/lib', '/usr/local/cuda/lib64'],
    }],
    [ 'OS=="win"', {
      'conditions': [
        ['target_arch=="x64"',
          {
            'variables': { 'arch': 'x64' }
          }, {
            'variables': { 'arch': 'Win32' }
          }
        ],
      ],
      'variables': {
        'cuda_root%': '$(CUDA_PATH)'
      },
      'libraries': [
        '-l<(cuda_root)/lib/<(arch)/cuda.lib',
        '-l<(cuda_root)/lib/<(arch)/cudart.lib',
      ],
      "include_dirs": [
        "<(cuda_root)/include",
      ],
    }, {
      "include_dirs": [
        "/usr/local/cuda/include"
      ],
    }]
  ]
}
]
}

Julian de Bh.. 9

连接CUDA和Node.js的最自然方式是通过" addon ",它允许您将c ++代码公开给在节点上运行的javascript程序.

Node本身是一个构建在v8 javascript引擎之上的c ++应用程序,addons是一种编写c ++库的方式,javascript库可以使用它们,就像节点自己的库一样.

从外面看,插件看起来就像一个模块.c ++被编译成动态库,然后像任何其他模块一样暴露给节点.例如my-addon.cc - >(编译) - > my-addon.dylib - >(node-gyp) - > my-addon.node - >var myFoo = require('my-addon').foo()

从插件内部,您可以使用v8和Node API与Jav​​ascript环境进行交互,并使用普通的c ++ API访问CUDA.

在这个级别上有许多活动部件.简单到将值从一个传递给另一个就意味着当你将javascript值包装/解包到适当的c ++类型时,你需要担心c ++内存管理和javascript垃圾收集器.

好消息是,大多数问题都很好,很好的文档和支持库很多,例如,nan会立即运行一个骨架插件,而在CUDA方面,你正在讨论他们正常的c ++界面,有卡车装载的文档和教程.