John Hearns via Beowulf
2018-05-09 06:51:01 UTC
As a fan of the Julia language, I jsut saw this announcement on the Julia
forum.
Sounds mighty interesting!
https://discourse.julialang.org/t/cfp-parallel-applications-workshop-alternatives-to-mpi-supercomputing-2018/10762
http://sourceryinstitute.github.io/PAW/
Higher-level parallel programming models offer rich sets of abstractions
that feel natural in the intended applications. Such languages and tools
include (Fortran, UPC, Julia), systems for large-scale data processing and
analytics (Spark, Tensorflow, Dask), and frameworks and libraries that
extend existing languages (Charm++, Unified Parallel C++ (UPC++), Coarray
C++, HPX, Legion, Global Arrays). While there are tremendous differences
between these approaches, all strive to support better programmer
abstractions for concerns such as data parallelism, task parallelism,
dynamic load balancing, and data placement across the memory hierarchy.
forum.
Sounds mighty interesting!
https://discourse.julialang.org/t/cfp-parallel-applications-workshop-alternatives-to-mpi-supercomputing-2018/10762
http://sourceryinstitute.github.io/PAW/
Higher-level parallel programming models offer rich sets of abstractions
that feel natural in the intended applications. Such languages and tools
include (Fortran, UPC, Julia), systems for large-scale data processing and
analytics (Spark, Tensorflow, Dask), and frameworks and libraries that
extend existing languages (Charm++, Unified Parallel C++ (UPC++), Coarray
C++, HPX, Legion, Global Arrays). While there are tremendous differences
between these approaches, all strive to support better programmer
abstractions for concerns such as data parallelism, task parallelism,
dynamic load balancing, and data placement across the memory hierarchy.