- High Throughput Computing with Dask
- Collections
Collections in Space High Throughput Computing with Dask
Use collections to bring together multiple datasets and their associated files in an almost unlimited number of ways.
Intelligent High Throughput Computing (2019)
Last year we had a workshop that looked at some possibilities for High Throughput Computing (you can find all the details here). We would like to invite you to a follow-up workshop this year from July 1-5, again hosted in Turin.
The workshop will be 3.5 days long consisting of 1.5 days with three different Python libraries related to Dask:
Dask: https://docs.dask.org/en/latest/
Dask_jobqueue: https://dask-jobqueue.readthedocs.io/en/latest/
jobqueue_features: https://github.com/E-CAM/jobqueue_features
The last library is something that has been developed since last year by E-CAM. It allows the user to create tasks that call out to MPI programs, and easily configure the tasks to run on different types of resources (CPU/GPU/KNL).
The final 2 days will be a hackathon where you can work on your own use case with technical assistance.
- 3 0 993 0
Intelligent High Throughput Computing (2019)
- Last year we had a workshop that looked at some possibilities for High Throughput Computing (you can find all the details here). We would like to invite you to a follow-up workshop this year from July 1-5, again hosted in Turin.
The workshop will be 3.5 days long consisting of 1.5 days with three different Python libraries related to Dask:
Dask: https://docs.dask.org/en/latest/
Dask_jobqueue: https://dask-jobqueue.readthedocs.io/en/latest/
jobqueue_features: https://github.com/E-CAM/jobqueue_features
The last library is something that has been developed since last year by E-CAM. It allows the user to create tasks that call out to MPI programs, and easily configure the tasks to run on different types of resources (CPU/GPU/KNL).
The final 2 days will be a hackathon where you can work on your own use case with technical assistance. - Jul 01, 2019
- 3 0