Git Product home page Git Product logo

awe's Introduction

AWE

About:

AWE is a workload management system for bioinformatic workflow applications. AWE, together with Shock data management system, can be used to build an integrated platform for efficient data analysis and management which features following functionalities:

  • Explicit task parallelization and convenient application integration
  • Scalable, portable, and fault-tolerant workflow computation
  • Integration of heterogeneous and geographically distributed computing resources
  • Performance-aware, cost-efficient service management and resource management
  • Reusable and reproducible data product management

awe-diagram

AWE is designed as a distributed system that contains a centralized server and multiple distributed clients. The server receives job submissions and parses jobs into tasks, splits tasks into workunits, and manages workunits in a queue. The AWE clients, running on distributed, heterogeneous computing resources, keep checking out workunits from the server queue and dispatching the workunits on the local computing resources.

AWE uses the Shock data management system to handle input and output data (retrieval, storage, splitting, and merge). AWE uses a RESTful API for communication between AWE components and with outside components such as Shock, the job submitter, and the status monitor.

awe-diagram

AWE is actively being developed at github.com/MG-RAST/AWE.

Shock is actively being developed at github.com/MG-RAST/Shock.

Documentation

Documentation can be found on the AWE wiki pages:

https://github.com/MG-RAST/AWE/wiki

Papers to cite

W. Tang, J. Wilkening, N. Desai, W. Gerlach, A. Wilke, F. Meyer, "A scalable data analysis platform for metagenomics," in Proc. of IEEE International Conference on Big Data, 2013.[ieeexplore] [pdf]

W. Gerlach, W. Tang, K. Keegan, T. Harrison, A. Wilke, J. Bischof, M. D'Souza, S. Devoid, D. Murphy-Olson, N. Desai, F. Meyer, "Skyport โ€“ Container-Based Execution Environment Management for Multi-Cloud Scientific Workflows," in Proc. of the 5th International Workshop on Data Intensive Computing in the Clouds, 2014. [pdf]

AWE Discussion Group

For questions, bug reports or feature requests please use the awe-users mailing list:

https://groups.google.com/d/forum/awe-users (Email: [email protected])

awe's People

Contributors

danielolson5 avatar eberroca avatar jaredbischof avatar jaredwilkening avatar sage-service-user avatar teharrison avatar wgerlach avatar wtangiit avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.