semvec/pypi-packages huggingface dataset:
cudatree 0.6
Random Forests for the GPU using PyCUDA
License: BSD

CudaTree
========

CudaTree is an implementation of Leo Breiman's Random Forests adapted to run on the GPU. A random forest is an ensemble of randomized decision trees which vote together to predict new labels. CudaTree parallelizes the construction of each individual tree in the ensemble and thus is able to train faster than the latest version of scikits-learn.

Usage
-------------

::

  import numpy as np
  from cudatree import load_data, RandomForestClassifier
  x_train, y_train = load_data("digits")
  forest = RandomForestClassifier(n_estimators = 50, max_features = 6)
  forest.fit(x_train, y_train)
  forest.predict(x_train)

Dependencies
--------------

CudaTree is writen for Python 2.7 and depends on:

* scikit-learn
* NumPy
* PyCUDA
*  Parakeet
marvin-wfms 0.0.1
Pilot-based GWENDIA Workflow Enacter.
License: BSD
Keywords: workflow gwendia pilot

Marvin Workflow Management System
=================================

Introduction
------------

A Pilot-API based Workflow Management System with a brain the size of the universe.

Installation
------------

    $ pip install marvin-wfms
    
Usage
-----
    
    $ python marvin.py <workflow.xml> <input.xml>

      <workflow.xml>: is a GWENDIA based workflow.
      <input.xml>: the values to be used by the corresponding input ports.


Related publications
--------------------


_Exploring Dynamic Enactment of Scientific Workflows using Pilot-Abstractions._
Mark Santcroos, Barbera DC van Schaik, Shayan Shahand, Silvia Delgado Olabarriaga, Andre Luckow, Shantenu Jha
13th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing, 2013.
https://raw.github.com/saga-project/radical.wp/master/publications/pdf/ccgrid-pilotapi_draft.pdf

_P*: A Model of Pilot-Abstractions._
Luckow, A., Santcroos, M., Merzky, A., Weidner, O., Mantha, P., & Jha, S. (2012).
Proceedings of the 8th IEEE International Conference on e-Science 2012.
https://raw.github.com/saga-project/radical.wp/master/publications/pdf/pstar12_draft.pdf

_A data-driven workflow language for grids based on array programming principles._
Montagnat, J., Isnard, B., Glatard, T., Maheshwari, K., & Fornarino, M. (2009).
WORKS '09: Proceedings of the 4th Workshop on Workflows in Support of Large-Scale Science. 
http://dl.acm.org/citation.cfm?id=1645171