parallel graph management and execution in heterogeneous computing
pathos is a framework for heterogenous computing. It provides a consistent
high-level interface for configuring and launching parallel computations
across heterogenous resources. pathos provides configurable launchers for
parallel and distributed computing, where each launcher contains the
syntactic logic to configure and launch jobs in an execution environment.
Examples of launchers that plug into pathos are: a queue-less MPI-based
launcher (in pyina), a ssh-based launcher (in pathos), and a multi-process
launcher (in multiprocess).
pathos provides a consistent interface for parallel and/or distributed
versions of map and apply for each launcher, thus lowering the barrier
for users to extend their code to parallel and/or distributed resources.
The guiding design principle behind pathos is that map and apply
should be drop-in replacements in otherwise serial code, and thus switching
to one or more of the pathos launchers is all that is needed to enable
code to leverage the selected parallel or distributed computing resource.
This not only greatly reduces the time to convert a code to parallel, but it
also enables a single code-base to be maintained instead of requiring
parallel, serial, and distributed versions of a code. pathos maps can be
nested, thus hierarchical heterogenous computing is possible by merely
selecting the desired hierarchy of map and pipe (apply) objects.
The pathos framework is composed of several interoperating packages::
- dill: a utility to serialize all of python
- pox: utilities for filesystem exploration and automated builds
- klepto: persistent caching to memory, disk, or database
- multiprocess: better multiprocessing and multithreading in python
- ppft: distributed and parallel python
- pyina: MPI parallel
mapand cluster scheduling - pathos: graph management and execution in heterogenous computing
The pathos package provides a few basic tools to make parallel and
distributed computing more accessable to the end user. The goal of pathos
is to enable the user to extend their own code to parallel and distributed
computing with minimal refactoring.
pathos provides methods for configuring, launching, monitoring, and
controlling a service on a remote host. One of the most basic features
of pathos is the ability to configure and launch a RPC-based service
on a remote host. pathos seeds the remote host with a small portpicker
script, which allows the remote host to inform the localhost of a port
that is available for communication.
Beyond the ability to establish a RPC service, and then post requests,
is the ability to launch code in parallel. Unlike parallel computing
performed at the node level (typically with MPI), pathos enables the
user to launch jobs in parallel across heterogeneous distributed resources.
pathos provides distributed map and pipe algorithms, where a mix of
local processors and distributed workers can be selected. pathos
also provides a very basic automated load balancing service, as well as
the ability for the user to directly select the resources.
The high-level pool.map interface, yields a map implementation that
hides the RPC internals from the user. With pool.map, the user can launch
their code in parallel, and as a distributed service, using standard python
and without writing a line of server or parallel batch code.
RPC servers and communication in general is known to be insecure. However,
instead of attempting to make the RPC communication itself secure, pathos
provides the ability to automatically wrap any distributes service or
communication in a ssh-tunnel. Ssh is a universally trusted method.
Using ssh-tunnels, pathos has launched several distributed calculations
on national lab clusters, and to date has performed test calculations
that utilize node-to-node communication between several national lab clusters
and a user's laptop. pathos allows the user to configure and launch
at a very atomistic level, through raw access to ssh and scp.
pathos is the core of a python framework for heterogeneous computing.
pathos is in active development, so any user feedback, bug reports, comments,
or suggestions are highly appreciated. A list of known issues is maintained
at http://trac.mystic.cacr.caltech.edu/project/pathos/query, with a public
ticket list at https://github.com/uqfoundation/pathos/issues.
pathos provides a configurable distributed parallel map interface
to launching RPC service calls, with::
- a
mapinterface that meets and extends the pythonmapstandard - the ability to submit service requests to a selection of servers
- the ability to tunnel server communications with ssh
The pathos core is built on low-level communication to remote hosts using
ssh. The interface to ssh, scp, and ssh-tunneled connections can::
- configure and launch remote processes with ssh
- configure and copy file objects with scp
- establish an tear-down a ssh-tunnel
To get up and running quickly, pathos also provides infrastructure to::
- easily establish a ssh-tunneled connection to a RPC server
The latest released version of pathos is available from::
http://trac.mystic.cacr.caltech.edu/project/pathos
pathos is distributed under a 3-clause BSD license.
You can get the latest development version with all the shiny new features at:: https://github.com/uqfoundation
If you have a new contribution, please submit a pull request.
Probably the best way to get started is to look at the tests and
examples provided within pathos. See pathos.examples and pathos.tests
for a set of scripts that demonstrate the configuration and launching of
communications with ssh and scp, and demonstrate the configuration and
execution of jobs in a hierarchical parallel workflow. The source code is
also generally well documented, so further questions may be resolved by
inspecting the code itself. Please also feel free to submit a ticket on
github, or ask a question on stackoverflow (@Mike McKerns).
pathos is an active research tool. There are a growing number of publications
and presentations that discuss real-world examples and new features of pathos
in greater detail than presented in the user's guide. If you would like to
share how you use pathos in your work, please post a link or send an email
(to mmckerns at uqfoundation dot org).
Important classes and functions are found here::
pathos.abstract_launcher[the worker pool API definition]pathos.pools[all of the pathos worker pools]pathos.core[the high-level command interface]pathos.hosts[the hostname registry interface]pathos.serial.SerialPool[the serial python worker pool]pathos.parallel.ParallelPool[the parallelpython worker pool]pathos.multiprocessing.ProcessPool[the multiprocessing worker pool]pathos.threading.ThreadPool[the multithreading worker pool]pathos.connection.Pipe[the launcher base class]pathos.secure.Pipe[the secure launcher base class]pathos.secure.Copier[the secure copier base class]pathos.secure.Tunnel[the secure tunnel base class]pathos.selector.Selector[the selector base class]pathos.server.Server[the server base class]pathos.profile[profiling in threads and processes]
pathos also provides four convience scripts that are used to establish
secure distributed connections. These scripts are installed to a directory
on the user's $PATH, and thus can be run from anywhere::
portpicker.py[get the portnumber of an open port]pathos_tunnel.py[establish a ssh-tunnel connection]pathos_server.py[launch a remote RPC server]tunneled_pathos_server.py[launch a tunneled remote RPC server]
Typing --help as an argument to any of the above scripts will print out an
instructive help message.
If you use pathos to do research that leads to publication, we ask that you
acknowledge use of pathos by citing the following in your publication::
M.M. McKerns, L. Strand, T. Sullivan, A. Fang, M.A.G. Aivazis,
"Building a framework for predictive science", Proceedings of
the 10th Python in Science Conference, 2011;
http://arxiv.org/pdf/1202.1056
Michael McKerns and Michael Aivazis,
"pathos: a framework for heterogeneous computing", 2010- ;
http://trac.mystic.cacr.caltech.edu/project/pathos
Please see http://trac.mystic.cacr.caltech.edu/project/pathos or http://arxiv.org/pdf/1202.1056 for further information.