design document

Author: Brett VanderHaar

README.md

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 # floyds-algorithm
 
-start
+## Abstract
+An OpenMP and non-OpenMP version of a C++ implementation of Floyd's algorithm was tested and compared.  Results indicate dramatic speedup using OpenMP.
+
+## High Level Design
+The single threaded version goes row-by-row through the matrix and calculates the score.  The multi-threaded version using parallel OpenMP for loops.
+
+## Implementation
+C++14 standard library with GCC 5.2 was chosen due to ease of implementing OpenMP.  The OMP_NUM_THREADS environment variable was used to control the number of OpenMP threads. Level 2 optimizations were also compared in the tests due to anecdotal evidence resulting in reduced processing time.
+
+## Testing Methodology
+A Macbook Pro, Early 2015 with a 2.7GHz Core i5 processor with 8GB of DDR3 RAM was used for compilation and test runs.  A Linux VM with Arch Linux and GCC 5.2 were used.
+
+## Discussion
+Here is the raw data of the test runs.
+![Raw Data](https://raw.githubusercontent.com/bvanderhaar/floyds-algorithm/master/docs/raw-data.png)
+
+Here is the comparison of the data, graphed.  
+![Comparison](https://raw.githubusercontent.com/bvanderhaar/floyds-algorithm/master/docs/runtime-graph.png)
+
+Both L2 optimizations and OpenMP have profound effect on processing time.
+
+## Conclusion
+OpenMP reduced the processing time in all cases.  L2 optimizations are also tuned to help in the case of nested for loops.