3 ms·

How about dask's distrubted array? Do you know how the architecture and goals compare to Elemental?

• deleted 11y ago
  [deleted]
• math_and_stuff 11y ago
  Distributed [1] is very new and seems to have similar core architectural goals as TensorFlow. But perhaps I'm being too politically correct: both make use of very course-grain parallelism relative to a typical distributed-memory linear algebra library (e.g., the current communication mechanisms of both are likely to be too course-grain to efficiently support distributed dense matrix inversion or eigensolvers; not that this is likely to be a design goal of either). [1] http://matthewrocklin.com/blog/work/2015/06/23/Distributed/ http://matthewrocklin.com/blog/work/2015/06/23/Distributed/
  • Gtifn 11y ago
    I think distributed's scheduler has seen much iteration since then and is now based on tornado. I wonder if that changes your assessment. Also what do you think of Julia's native distributed capabilities and this library here: https://github.com/shashi/ComputeFramework.jl https://github.com/shashi/ComputeFramework.jl