LeNetTorch
vectorflow
| LeNetTorch | vectorflow | |
|---|---|---|
| 1 | 12 | |
| 0 | 1,291 | |
| - | 0.3% | |
| 1.8 | 0.0 | |
| about 2 years ago | 15 days ago | |
| Python | D | |
| MIT License | Apache License 2.0 |
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LeNetTorch
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Small Neural networks in Julia 5x faster than PyTorch
The Flux.jl example did this. A PR to the PyTorch example to do this would be welcome: https://github.com/chriselrod/LeNetTorch
vectorflow
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Programming languages endorsed for server-side use at Meta
>> Mozilla (of course)
Mozilla is a c++ and javascript shop. What do they ship in Rust? How much of Firefox is written in rust for example?
>> Microsoft, Meta, Google/Acrobat, Amazon
Large firms have lots of devs and consequently lots of toy projects. Is their usage of rust more significant than their use of D? I mean Meta was churning out projects in D a while back (warp, flint, etc) and looked like it might be going all in at one point (they even hired one of the leads on D lang).
>> That's practically all of FAANG
Who were we missing? Netflix, they’ve dabbled with D too: https://github.com/Netflix/vectorflow
Don’t misunderstand my point - it’s not that D is more popular than rust, it’s that rust is not used for real work in any significant capacity yet.
Where’s the big project written in rust? Servo and the rust compiler are the only two large rust projects on github.
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Cloud TPU VMs are generally available
Thanks Zak, already applied.
Just wondering does TPU VM support Vectorflow?
https://github.com/Netflix/vectorflow
- Vectorflow is a minimalist neural network library optimized for sparse data and single machine environments open sourced by Netflix (r/MachineLearning)
- [P] Vectorflow is a minimalist neural network library optimized for sparse data and single machine environments open sourced by Netflix
- Vectorflow is a minimalist neural network library optimized for sparse data and single machine environments open sourced by Netflix
- Vectorflow: Minimalist neural network library faster than TensorFlow in D
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Small Neural networks in Julia 5x faster than PyTorch
A library I designed a few years ago (https://github.com/Netflix/vectorflow) is also much faster than pytorch/tensorflow in these cases.
In "small" or "very sparse" setups, you're memory bound, not compute bound. TF and Pytorch are bad at that because they assume memory movements are worth it and do very little in-place operations.
Different tools for different jobs.
What are some alternatives?
tiny-cuda-nn - Lightning fast C++/CUDA neural network framework