diff --git a/README.md b/README.md
index a65de42..1da5537 100644
--- a/README.md
+++ b/README.md
@@ -2,3 +2,21 @@ Parallel MCMC On GPU
 ===========================
 
 This project compares the performance of MCMC on a single threaded CPU, and a multicore, multithreaded GPU (using CUDA).
+
+
+## Sequential
+
+#### Dependencies
+* gcc 5.4.0 or newer
+
+#### How to compile
+```
+cd ./sequential
+g++ -std=c++11 gibbs_metropolis.cpp -o gibbs_metropolis
+```
+
+##### Run
+**Small Example**
+``
+./gibbs_metropolis smallData.txt
+```
diff --git a/sequential/gibbs_metropolis.cpp b/sequential/gibbs_metropolis.cpp
index f10279c..ebd3ce8 100755
--- a/sequential/gibbs_metropolis.cpp
+++ b/sequential/gibbs_metropolis.cpp
@@ -46,7 +46,7 @@ specifically http://docs.nvidia.com/cuda/curand/index.html#topic_1_2_1
 #include <stdio.h>
 #include <stdlib.h>
 #include <math.h>
-// #include <curand_kernel.h>
+#include <random>
 
 #define PI 3.14159265359f
 
@@ -272,11 +272,13 @@ void sample_theta(float *theta, float *log_theta, int *y, float *n,
                              float a, float b, int K){
 
   float hyperA, hyperB;
+  std::default_random_engine generator;
 
   for ( int i = 0; i < K; i++ ){
     hyperA = a + y[i];
     hyperB = b + n[i];
-    theta[i] = rgamma(hyperA, hyperB);
+    std::gamma_distribution<double> distribution(hyperA, hyperB);
+    theta[i] = distribution(generator);
     log_theta[i] = log(theta[i]);
   }
 }