Similar to comm.gather, comm.reduce takes an array of input elements in each process and returns an array of output elements to the root process. The output elements contain the reduced result.
- Title Page
- Copyright and Credits
- Dedication
- About Packt
- Contributors
- Preface
- Getting Started with Parallel Computing and Python
- Thread-Based Parallelism
- What is a thread?
- Python threading module
- Defining a thread
- Determining the current thread
- Defining a thread subclass
- Thread synchronization with a lock
- Thread synchronization with RLock
- Thread synchronization with semaphores
- Thread synchronization with a condition
- Thread synchronization with an event
- Thread synchronization with a barrier
- Thread communication using a queue
- Process-Based Parallelism
- Message Passing
- Technical requirements
- Understanding the MPI structure
- Using the mpi4py Python module
- Implementing point-to-point communication
- Avoiding deadlock problems
- Collective communication using a broadcast
- Collective communication using the scatter function
- Collective communication using the gather function
- Collective communication using Alltoall
- The reduction operation
- Optimizing communication
- Asynchronous Programming
- Distributed Python
- Cloud Computing
- Heterogeneous Computing
- Understanding heterogeneous computing
- Understanding the GPU architecture
- Understanding GPU programming
- Dealing with PyCUDA
- Heterogeneous programming with PyCUDA
- Implementing memory management with PyCUDA
- Introducing PyOpenCL
- Building applications with PyOpenCL
- Element-wise expressions with PyOpenCL
- Evaluating PyOpenCL applications
- GPU programming with Numba
- Python Debugging and Testing
- Other Books You May Enjoy
The reduction operation
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