Merge pull request #26 from ICHEC/rt

updated

lecture-08/instructions/instructions.md

@@ -6,7 +6,10 @@ The link to install annaconda and installation instruction can be found [here](h
 
 ---
 
-# Instructions for installing Julia for YAO
+## Instructions for installing Julia for YAO
+
+### Using Conda 
+
 1. Create an environment in conda each for julia
     ```bash
     conda create -n julia-env python=3 notebook
@@ -25,27 +28,45 @@ The link to install annaconda and installation instruction can be found [here](h
     conda install -c conda-forge julia
     ```
 
-    If you want a separate julia installation other than conda, you can download from official julia download pare [here](https://julialang.org/downloads/).
+
+If you want a separate julia installation other than conda, you can download from official julia download pare [here](https://julialang.org/downloads/), or use your operating system's package manager as bellow.
+
+### system level installation
+
+Since Julia has it's own package management, one may also just want to install at system level. 
+
+On linux, most package managers have julia included, such as on Ubuntu you can install it by following terminal command -
+
+```bash
+sudo apt install julia
+```
+
+On MacOS one can install via `Homebrew`
+```zsh
+brew install julia
+```
 
 ---
-4. Now we need to install julia kernel to be able to use them in python notebook. Julia does it's own package management, so we need to install the kernel through julia. Let's first launch julia by simply typing following in the terminal -
-    ```bash
-    julia
-    ```
-    This will run julia, and you will see julia prompt similar to python/ipython prompt. Within the prompt, now we run the following in sequence-
-    ```julia
-    using Pkg; Pkg.add("IJulia")
-    ```
-    This will install IJulia which provides ability to use julia kernel.
-    
-    We further configure the kernel by following command -
-    ```julia
-    using IJulia
-    installkernel("[Julia 4 cpu]", env=Dict("JULIA_NUM_THREADS"=>"4"))
-    ```
-    The *installkernel* command is taking two arguments, first is a string, that is name of the kernel (visible when choosing a kernel in vscode/jupyter notebook) and next one defines a variable JULIA_NUM_THREADS which tells julia kernel how many cpu threads it can use. We choose 4, but it can be any positive number ≤ total number of cpu threads on your machine (laptop/desktop).
+
+Once we have julia installed, we need to install julia kernel to be able to use them in python notebook. Julia does it's own package management, so we need to install the kernel through julia. Let's first launch julia by simply typing following in the terminal -
+```bash
+julia
+```
+This will run julia, and you will see julia prompt similar to python/ipython prompt. Within the prompt, now we run the following in sequence-
+```julia
+using Pkg; Pkg.add("IJulia")
+```
+This will install IJulia which provides ability to use julia kernel.
+
+We further configure the kernel by following command -
+```julia
+using IJulia
+installkernel("[Julia 4 cpu]", env=Dict("JULIA_NUM_THREADS"=>"4"))
+```
+The *installkernel* command is taking two arguments, first is a string, that is name of the kernel (visible when choosing a kernel in vscode/jupyter notebook) and next one defines a variable JULIA_NUM_THREADS which tells julia kernel how many cpu threads it can use. We choose 4, but it can be any positive number ≤ total number of cpu threads on your machine (laptop/desktop).
+
 ---
-5. We just setup a functioning julia kernel. When you open any notebook, it shows an option in top right corner to *select a kernel*. So now you can go ahead and open a julia notebook in vscode. You should be able to see "Julia 4 cpu" (or whichever name you chose) as a julia kernel from the list of jupyter kernels. Select it, and run any julia code in the cell. Happy coding!
+We just setup a functioning julia kernel. When you open any notebook, it shows an option in top right corner to *select a kernel*. So now you can go ahead and open a julia notebook in vscode. You should be able to see "Julia 4 cpu" (or whichever name you chose) as a julia kernel from the list of jupyter kernels. Select it, and run any julia code in the cell. Happy coding!
 
 ![Julia Kernel](./julia-kernel.png)
 

lecture-08/landscape-of-sdks-tools.md

@@ -322,3 +322,8 @@ Lets take a look at the specific quantum software components used. First we have
 :align: center
 ```
 
+```{admonition} Julia instructions
+:class: tip
+
+Instructions for using Julia and Julia Yao can be found [here](./instructions/instructions.md)
+```