diff --git a/performance/SIMD/roessler.cpp b/performance/SIMD/roessler.cpp
new file mode 100644
index 0000000..4e6cc42
--- /dev/null
+++ b/performance/SIMD/roessler.cpp
@@ -0,0 +1,125 @@
+/*
+ * Simulation of an ensemble of Roessler attractors
+ *
+ * Copyright 2014 Mario Mulansky
+ *
+ * Distributed under the Boost Software License, Version 1.0.
+ * (See accompanying file LICENSE_1_0.txt or
+ * copy at http://www.boost.org/LICENSE_1_0.txt)
+ *
+ */
+
+
+#include <iostream>
+#include <vector>
+#include <random>
+
+#include <boost/timer.hpp>
+#include <boost/array.hpp>
+
+#include <boost/numeric/odeint.hpp>
+
+namespace odeint = boost::numeric::odeint;
+
+typedef boost::timer timer_type;
+
+typedef double fp_type;
+//typedef float fp_type;
+
+typedef boost::array<fp_type, 3> state_type;
+typedef std::vector<state_type> state_vec;
+
+//---------------------------------------------------------------------------
+struct roessler_system {
+    const fp_type m_a, m_b, m_c;
+
+    roessler_system(const fp_type a, const fp_type b, const fp_type c)
+        : m_a(a), m_b(b), m_c(c)
+    {}
+
+    void operator()(const state_type &x, state_type &dxdt, const fp_type t) const
+    {
+        dxdt[0] = -x[1] - x[2];
+        dxdt[1] = x[0] + m_a * x[1];
+        dxdt[2] = m_b + x[2] * (x[0] - m_c);
+    }
+};
+
+//---------------------------------------------------------------------------
+int main(int argc, char *argv[]) {
+if(argc<3)
+{
+    std::cerr << "Expected size and steps as parameter" << std::endl;
+    exit(1);
+}
+const size_t n = atoi(argv[1]);
+const size_t steps = atoi(argv[2]);
+//const size_t steps = 50;
+
+const fp_type dt = 0.01;
+
+const fp_type a = 0.2;
+const fp_type b = 1.0;
+const fp_type c = 9.0;
+
+// random initial conditions on the device
+std::vector<fp_type> x(n), y(n), z(n);
+std::default_random_engine generator;
+std::uniform_real_distribution<fp_type> distribution_xy(-8.0, 8.0);
+std::uniform_real_distribution<fp_type> distribution_z(0.0, 20.0);
+auto rand_xy = std::bind(distribution_xy, std::ref(generator));
+auto rand_z = std::bind(distribution_z, std::ref(generator));
+std::generate(x.begin(), x.end(), rand_xy);
+std::generate(y.begin(), y.end(), rand_xy);
+std::generate(z.begin(), z.end(), rand_z);
+
+state_vec state(n);
+for(size_t i=0; i<n; ++i)
+{
+    state[i][0] = x[i];
+    state[i][1] = y[i];
+    state[i][2] = z[i];
+}
+
+std::cout.precision(16);
+
+std::cout << "# n: " << n << std::endl;
+
+std::cout << x[0] << std::endl;
+
+
+// Stepper type - use never_resizer for slight performance improvement
+odeint::runge_kutta4_classic<state_type, fp_type, state_type, fp_type,
+                             odeint::array_algebra,
+                             odeint::default_operations,
+                             odeint::never_resizer> stepper;
+
+roessler_system sys(a, b, c);
+
+timer_type timer;
+
+fp_type t = 0.0;
+
+for (int step = 0; step < steps; step++)
+{
+    for(size_t i=0; i<n; ++i)
+    {
+        stepper.do_step(sys, state[i], t, dt);
+    }
+    t += dt;
+}
+
+std::cout << "Integration finished, runtime for " << steps << " steps: ";
+std::cout << timer.elapsed() << " s" << std::endl;
+
+// compute some accumulation to make sure all results have been computed
+fp_type s = 0.0;
+for(size_t i = 0; i < n; ++i)
+{
+    s += state[i][0];
+}
+
+std::cout << state[0][0] << std::endl;
+std::cout << s/n << std::endl;
+
+}