You are here:
Work Queue + Python: A Framework For Scalable Scientific Ensemble Applications
Peter Bui, Dinesh Rajan, Badi Abdul-Wahid, Jesus Izaguirre and Douglas Thain
Even with the increase in the number and variety of computer resources available to research scientists today, it is still challenging to construct scalable distributed applications. To address this issue, we developed Work Queue, a flexible master/worker framework for building large scale scientific ensemble applications that span many machines including clusters, grids, and clouds.
A Technical Anatomy Of How OpenMPI Applications Can Inherit Fault-Tolerance Using SPM.Python
Minesh B Amin
SPM.Python is a scalable, parallel fault-tolerant version of the serial Python language, and can be deployed to create parallel capabilities to solve problems in domains divning finance, life sciences, electronic design, IT, visualization, and research.
A New Compilation Path: From Python/NumPy to OpenCL
Xunhao Li, Rahul Garg and Jose Nelson Amaral
Jit4OpenCL is a new compiler that converts scientific applications written in Python/NumPy into OpenCL code.
pandas: a Foundational Python Library for Data Analysis and Statistics
In this paper we will discuss pandas, a Python library of rich data structures and tools for working with relational or "labeled" data sets common to statistics, finance, social sciences, and many other fields.
The Integrated Plasma Simulator: A Flexible Python Framework for Coupled Multiphysics Simulation
Samantha S. Foley, Wael R. Elwasif and David E. Bernholdt
This paper presents the Integrated Plasma Simulator (IPS), a framework designed for loosely coupled simulations of fusion plasmas. The IPS provides users with a simple component architecture into which a wide range of existing plasma physics codes can be inserted as components.
High-Performance Astrophysical Simulations and Analysis with Python
Matthew Turk and Britton Smith
We present yt, an open source, community-developed astrophysical analysis and visualization toolkit for data generated by high-performance computing (HPC) simulations of astrophysical phenomena.
Parallel Computational Methods and Simulation for Coastal and Hydraulic Applications Using the Proteus Toolkit
Chris Kees and Matthew Farthing
The Proteus toolkit evolved to support research on new models for coastal and hydraulic processes and improvements in numerical methods. The models considered include multiphase flow in porous media, shallow water flow, turbulent free surface flow, and flow-driven processes such as sediment and species transport.
Call for Papers
Workshop Python for High Performance and Scientific Computing (SC11)
Submission page (EasyChair)
Birds of a Feather Python for High Performance Computing (SC11)
Facebook event page
Copyright © 2018 German Aerospace Center (DLR). All rights reserved.