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Title

github wiki

Man-hours required

Date

Finalized

Owners

Skills

Description

Raison d'etre / Value Derived

Setting up the Infrastructure

 

 

10/10/2011 - 21/10/2011

 

 

Capture what we need to the collaboration between ICRAR and TW successful

We want a clear understanding of the goal of this collaboration and how to ensure it is successful

GAIA Parameter DB refresh

gaia-pdb

 

10/10/2011

26/10/2011

PHP, MySQL

Rewrite GAIA Parameter database application

Sample project to show how agile methodology, technologies and infrastructure tools work in practice

Turn GAIA PDB into SKA PDB

ska-pdb

 

01/12/2011

 

Ruby on Rails, MySQL

The version of the GAIA PDB delivered by GAIA Parameter DB refresh should be converted into a deployable SKA parameter database

Have a single, accessible repository for technical and natural properties related to the SKA.

NGAS FUSE storage

ngas-fuse

 

01/12/2011

 

Python, FUSE, HTTP

Implement a FUSE based container storage into NGAS

Allow physical packaging of files into single container (user based filesystem)

NGAS FUSE file systemngasfs 08/08/2014 Python, FUSE, sqlite, HTTP, PyFilesystemImplement a NGAS FUSE file system on-top of SQLite and PyFilesystem. Allow for user defined filters, limiting the number of file objects.Allow users to mount NGAS as a part of their standard file system and thus provide posix-like functionality.

VO cone search cube server

vo-data-cube-cone-search

 

01/12/2011

 

client-server, Java or Python

Implement a VO cone search server for multi-res radio data cubes

Alllow Virtual Observatory Tools to retrieve columns of data cubes via standard VO cone search

Moving MAGPHYS to BOINC

boinc-magphys

 

05/12/2011

 

C, Php, Fortran

Port the MAGPHYS project into the BOINC environment

Take advantage of existing BOINC user base for calculating spectral energy density, which can be used to tell the story of how the galaxy evolved.

Moving GalFit to BOINC

boinc-galfit

 

05/12/2011

 

C, Php, Fortran

Port the GalFit project into the BOINC environment

Take advantage of existing BOINC user base for classifying galaxies.

Moving Python Source Finder to BOINC

boinc-source-finder

 

05/12/2011

 

C, Php, Python

Port the MAGPHYS project into the BOINC environment

Take advantage of existing BOINC user base for finding galaxies (sources).

NGAS VOSpace  24/10/2012 Python

Implement a VOSpace interface on-top of NGAS. This is now revived with the implementation of pvospace by Dave Pallot

Provide VOSpace capabilites for ICRAR
NGAS Interface on-top of S3  
 
 PythonImplement an NGAS compliant interface on-top of S3Provides NGAS functionality and easy cross-utilisation of S3 enabled storage.
NGAS Minio gateway

 


Andreas WicenecPython, GoImplement a gateway for NGAS in Minio. Minio is written in Go.This would allow us to expose NGAS as a S3 compliant object store. Essentially the reverse of the above.
NGAS Minio underneath ownCloud/CloudStor

 


Andreas WicenecPython, Go, configurationIntegrate Minio with a NGAS gateway with ownCloudIn this way we would be able to have NGAS exposed directly to the desktop of users. Pretty cool!!!
Integrate BeeGFS with DALiuGE

 


Python, C(?)BeeGFS offers functionality, which closely resembles advanced design features required by DALiuGE. One being storage pools another being beeond (BeeGFS on Demand). This project would implement an integration within DALiuGE to use those BeeGFS features.Enables advanced DALiuGE features in terms of data placement and resilience control
DALiuGE PGT to DASK graph translator

 


PythonTranslating a DALiuGE Physical Graph Template (PGT) into a DASK graph essentially requires translating a JSON file into a Python dictionary. This project aims to implement such a translator.Enable running EAGLE graphs with DASK. Inform us about missing features from DALiuGE or DASK.
Benchmarking and Optimising Radio Astronomy Data I/O

 


Andreas WicenecPython/C/C++Produce a comprehensive and flexible benchmark suite to measure and analyse access to large Measurement Set data sets. Should include highly parallel data access patterns distributed across many processes and nodes in a cluster. Second part is to analyse measurements on various platforms/systems and derive potential optimisations.A dedicated MS benchmarking suite. Optimisation of data distribution and access software for selected platforms/systems.