ipyparallel
  • Changes in IPython Parallel
    • 5.1
    • 5.0
    • 4.1
    • 4.0
  • Overview and getting started
    • Examples
    • Introduction
    • Architecture overview
    • Getting Started
  • Starting the IPython controller and engines
    • General considerations
    • Using ipcluster
    • Configuring an IPython cluster
    • IPython on EC2 with StarCluster
    • Using the ipcontroller and ipengine commands
  • IPython’s Direct interface
    • Starting the IPython controller and engines
    • Creating a DirectView instance
    • Quick and easy parallelism
    • Calling Python functions
    • Moving Python objects around
    • Other things to look at
  • Parallel Magic Commands
    • The Magics
    • Multiple Active Views
    • Engines as Kernels
  • The IPython task interface
    • Starting the IPython controller and engines
    • Creating a LoadBalancedView instance
    • Quick and easy parallelism
    • Dependencies
    • Retries and Resubmit
    • Schedulers
    • More details
  • The AsyncResult object
    • Beyond multiprocessing’s AsyncResult
    • Metadata
    • Map results are iterable!
  • Using MPI with IPython
    • Additional installation requirements
    • Starting the engines with MPI enabled
    • Actually using MPI
  • IPython’s Task Database
    • Enabling a DB Backend
    • Using the Task Database
    • Example Queries
    • Cost
  • Security details of IPython
    • Process and network topology
    • Application logic
    • Secure network connections
    • Specific security vulnerabilities
    • Other security measures
    • Summary
  • Parallel examples
    • 150 million digits of pi
    • Conclusion
  • DAG Dependencies
    • Why are DAGs good for task dependencies?
    • A Sample DAG
  • Details of Parallel Computing with IPython
    • Caveats
    • Running Code
    • Views
    • Data Movement
    • Results
    • Querying the Hub
    • Controlling the Engines
    • Synchronization
    • Map
    • Decorators and RemoteFunctions
    • Dependencies
  • Transitioning from IPython.kernel to ipyparallel
    • Processes
    • Creating a Client
    • Apply
    • MultiEngine to DirectView
    • Task to LoadBalancedView
  • Messaging for Parallel Computing
    • The Controller
    • The Hub
    • Schedulers
    • Control Messages
    • Implementation
  • Connection Diagrams of The IPython ZMQ Cluster
    • All Connections
  • ipyparallel
    • Classes
    • Decorators
    • Exceptions
 
ipyparallel
  • Docs »
  • Edit on GitHub

© Copyright 2015, The IPython Development Team.

Built with Sphinx using a theme provided by Read the Docs.