Python Multiprocessing with PyCUDA

参考：https://stackoverflow.com/questions/5904872/python-multiprocessing-with-pycuda

You need to get all your bananas lined up on the CUDA side of things first, then think about the best way to get this done in Python [shameless rep whoring, I know].

The CUDA multi-GPU model is pretty straightforward pre 4.0 - each GPU has its own context, and each context must be established by a different host thread. So the idea in pseudocode is:

1. Application starts, process uses the API to determine the number of usable GPUS (beware things like compute mode in Linux)
2. Application launches a new host thread per GPU, passing a GPU id. Each thread implicitly/explicitly calls equivalent of cuCtxCreate() passing the GPU id it has been assigned
3. Profit!

In Python, this might look something like this:

  

   

    

     

    
    

     

      import threading
     
    
   

    

     

    
    

     

      from pycuda import driver
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      class gpuThread(threading.Thread):
     
    
   

    

     

    
    

     
 def __init__(self, gpuid):
     
    
   

    

     

    
    

     

       threading.Thread.__init__(self)
     
    
   

    

     

    
    

     
 self.ctx  = driver.Device(gpuid).make_context()
     
    
   

    

     

    
    

     
 self.device = self.ctx.get_device()
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 def run(self):
     
    
   

    

     

    
    

     

       print "%s has device %s, api version %s"  \
     
    
   

    

     

    
    

     

       % (self.getName(), self.device.name(), self.ctx.get_api_version())
     
    
   

    

     

    
    

     
 # Profit!
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     
 def join(self):
     
    
   

    

     

    
    

     
 self.ctx.detach()
     
    
   

    

     

    
    

     

       threading.Thread.join(self)
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      driver.init()
     
    
   

    

     

    
    

     

      ngpus = driver.Device.count()
     
    
   

    

     

    
    

     

      for i in range(ngpus):
     
    
   

    

     

    
    

     

       t = gpuThread(i)
     
    
   

    

     

    
    

     

       t.start()
     
    
   

    

     

    
    

     

       t.join()
     
    
  
 

This assumes it is safe to just establish a context without any checking of the device beforehand. Ideally you would check the compute mode to make sure it is safe to try, then use an exception handler in case a device is busy. But hopefully this gives the basic idea.

文章来源: blog.csdn.net，作者：网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/79705484