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We use "deep learning made easy" as a slogan for ImJoy, as the project evolves, it becomes more general than deep learning, so it would be nice if we come up with a better slogan.
Here are some exa…
oeway updated
4 years ago
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- Optimize AI algorithms and computational workflows to ensure scalability and efficiency in processing large volumes of user responses.
- Explore techniques such as distributed computing, parallel p…
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Hi Lennart,
Regarding the acknowledgements:
> The authors gratefully acknowledge the computing time provided to them on the high-performance computers [Cluster name/s] at the NHR Center PC2. The…
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In-Memory Computing Essentials for Software Engineers
fundamental capabilities of in-memory computing platforms that are proven to boost application performance and solve scalability problems by st…
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Thanks for your great work on developing Rocket.jl. The documentation is very helpful and is a great introduction to reactive programming. I've read it in its entirety. However, I didn't find any exam…
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I'm trying [this example from the dask-examples repo](https://github.com/dask/dask-examples/blob/main/applications/stencils-with-numba.ipynb). When computing the graph it gives a `PicklingError`
```
…
rsarm updated
3 months ago
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Some terminology is used inconsistently, but this also raises a few other things we need to better align.
The Distributed Worker Proposal uses "Computing Resources" or "Distributed Computing Resour…
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If there are multiple worker processes, will this package take advantage of distributed computing automatically? For example,
``` julia
using Dsitributed
@everywhere using Distances
X = rand(3,10)…
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https://github.com/sanjar-notes/distributed-computing-systems/issues/1
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Hi all,
let us know if you'd like to join this working group on 'Marshaling and Serialization in R'. To join, just add a comment below with a very brief introduction of yourself and your interest i…