Skip to main content

A Skeleton Generator

Project description

<a href=”http://dx.doi.org/10.5281/zenodo.13750”><img src=”https://zenodo.org/badge/doi/10.5281/zenodo.13750.svg” alt=”10.5281/zenodo.13750”></a>

Skeleton

Application Skeleton is a tool to generate skeleton applications — easy-to-program, easy-to-run applications — that mimic a real applications’ parallel or distributed performance at a task (but not process) level.

Application classes that can be represented include: bag of tasks, map reduce, multi-stage workflow, and variations of these with a fixed number of iterations.

Applications are described as one or more stages.

Stages are described as one more more tasks. Stages can also be iterative.

Tasks can be serial or parallel, and have compute and I/O (read and write) elements.


Documentation about Skeletons can be found in the report directory


Contributors are welcome!


A paper about the first version of Application Skeletons is: Z. Zhang and D. S. Katz, “Application Skeletons: Encapsulating MTC Application Task Computation and I/O,” Proceedings of 6th Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS), (in conjunction with SC13), 2013. http://dx.doi.org/10.1145/2503210.2503222

A paper about the current version is: Z. Zhang and D. S. Katz, “Using Application Skeletons to Improve eScience Infrastructure,” Proceedings of 10th IEEE International Conference on eScience, 2014. http://dx.doi.org/10.1109/eScience.2014.9 (paper). http://www.slideshare.net/danielskatz/using-application-skeletons-to-improve-escience-infrastructure (slides).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aimes.skeleton-1.2.0.tar.gz (36.9 kB view details)

Uploaded Source

File details

Details for the file aimes.skeleton-1.2.0.tar.gz.

File metadata

File hashes

Hashes for aimes.skeleton-1.2.0.tar.gz
Algorithm Hash digest
SHA256 9b90f5fdabd3396b3869a909b2907379558bbefa683e8660f3678deecbea122f
MD5 b969e6dac79ffc0565ef61cb9a679a6c
BLAKE2b-256 31c1bead3d27f58b4802eb46113913b5a4ccf4be78912a02316d0bde38700245

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page