From 161d957423f5886c89c835fdd11d06f0448daccd Mon Sep 17 00:00:00 2001
From: gruczela <gruczela@msu.edu>
Date: Mon, 20 Mar 2023 18:44:02 -0400
Subject: [PATCH] added software abstract

---
 Numba Examples/README.md | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)

diff --git a/Numba Examples/README.md b/Numba Examples/README.md
index 8b13789..8803459 100644
--- a/Numba Examples/README.md	
+++ b/Numba Examples/README.md	
@@ -1 +1,21 @@
+### Software Abstract
+The software I chose to evaluate in my project is Python Numba. It is a compiler aiming to speed up applications. Numba is designed for Python arrays and numerical functions; specifically, it works best on code that uses loops, Numpy arrays and functions. Without having to switch languages, it increases optimization for code written in Python that is particularly math-heavy, utilizing functions with high performance. In order to call on Numba to compile functions, a selection of decorators are available to be applied. The option to parallelize functions automatically is available in the Numba decorators as well.
+### Installation
+In order to install Python Numba on the HPCC, here are provided step-by-step instructions:
+
+1. Log onto the HPCC
+
+2. Log onto a development node
+
+3. Run this command: `pip install numba`
+
+4. To check if installation was successful, run these commands:
+```
+python
+
+import numba
+
+numba.__version__
+```
+This should output the version of Numba you have installed.
 
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