Jack Clayton jackos

## Arch-Mojo.md

      
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                Sharktheone
                / Arch-Mojo.md
            
            
              Last active
              December 7, 2023 15:44
            
              
                Install the new mojo programming language on Arch. This will be obsolete when mojo adds official Arch support.
              
          
    The installation script has moved to this repository


## mojo_radiative_transfer.md

      
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                Nicholaswogan
                / mojo_radiative_transfer.md
            
            
              Last active
              May 26, 2023 23:21
            
              
                Benchmark of a common radiative transfer algorithm with the Mojo programming language
              
          
    Radiative transfer with Mojo

Lots of scientific codes need to estimate how light passes through an atmosphere. For example, to quantify the greenhouse effect, climate models need to know how an atmosphere absorbs and scatters sunlight and how efficiently infrared radiation emitted by the atmosphere escapes to space. Also, researchers need models of radiative transfer to interpret telescope observations of atmospheres on planets orbiting distant stars. By simulating what the telescope should see under different atmospheric compositions, a researcher can ultimately back out the composition that best agrees with the telescope observations.
A problem is that many scientific codes are bottlenecked by doing radiative transfer. Lots of computation is required because gases (e.g., H2O) absorb in very complicated ways as a function of the wavelength of light, so many radiative transfer calculations are required to revolve this structure.
I was excited to see initial release of the Mojo programming language, becau

  
## tensorflow_cpu_m1_darwin_arm64_rust.md

      
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                lnshi
                / tensorflow_cpu_m1_darwin_arm64_rust.md
            
            
              Created
              March 26, 2022 04:59
            
              
                Build TensorFlow C library on Apple M1 (darwin_arm64) and use it with TensorFlow rust bindings
              
          
    Background

Currently if you try to use the TensorFlow rust bindings crate: tensorflow = "0.17.0", this crate's sub-crate: tensorflow-sys will try to build the underlying TensorFlow C library from the source as Google hasn't provided an official release for Apple M1, but unfortunately the building will fail.
This gist provides a full working instructions for you to build the TensorFlow C library on Apple M1 (darwin_arm64), and eventually use it with the TensorFlow rust bindings crate: tensorflow = "0.17.0".
This gist was tested on TensorFlow v2.8.0, the other versions should work in the same way.
Steps


## audit.yml
name: Security audit
on:
  schedule:
    - cron: '0 0 * * *'
  push:
    paths:
      - '**/Cargo.toml'
      - '**/Cargo.lock'
jobs:
  security_audit:
	name: Security audit
	on:
	schedule:
	- cron: '0 0 * * *'
	push:
	paths:
	- '**/Cargo.toml'
	- '**/Cargo.lock'
	jobs:
	security_audit: