Updated method section.

latex/sections/methods.tex

@@ -292,17 +292,21 @@ results from \ref{subsec:statistical_mechanics}. In addition, we set a tolerance
 verify convergence, and a maximum number of Monte Carlo cycles to avoid longer 
 runtimes during implementation.
 
-We avoid the overhead of if-tests, and take advantage of the parallelization, by 
-defining a pattern to access all neighboring spins. Using a $L \times 2$ matrix, 
-containing all indices to the neighbors, and pre-defined constants, we find the 
-indices of the neighboring spins. The first column contains the indics for neighbors 
-to the left and up, and the second column right and down. 
+We used a pattern to access all neighboring spins, where all indices of the neighboring 
+spins are put in an $L \times 2$ matrix. The indices are accessed using pre-defined 
+constants, where the first column contain the indices for neighbors to the left 
+and up, and the second column right and down. This method avoids the use of if-tests,
+and takes advantage of the parallel optimization. 
 
 We parallelize our code using both a message passing interface (OpenMPI) and 
 multi-threading (OpenMP). First, we divide the temperatures into smaller ranges, 
 and each MPI process receives a set of temperatures. Every MPI process spawn a 
 set of threads, which initialize an Ising model and performs the Metropolis-Hastings 
-algorithm.
+algorithm. We limit the number of times threads are spawned and joined, by using 
+single parallel regions, reducing parallel overhead. We used Fox \footnote{Technical 
+specifications for Fox can be found at \url{https://www.uio.no/english/services/it/research/platforms/edu-research/help/fox/system-overview.md}}, 
+a high-performance computing cluster, to run our program. 
+
 
 
 \subsection{Tools}\label{subsec:tools}