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diff --git a/src/boost/libs/compute/example/batched_determinant.cpp b/src/boost/libs/compute/example/batched_determinant.cpp
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+++ b/src/boost/libs/compute/example/batched_determinant.cpp
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+//---------------------------------------------------------------------------//
+// Copyright (c) 2013-2014 Kyle Lutz <kyle.r.lutz@gmail.com>
+//
+// 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
+//
+// See http://boostorg.github.com/compute for more information.
+//---------------------------------------------------------------------------//
+
+#include <iostream>
+
+#include <Eigen/Core>
+#include <Eigen/LU>
+
+#include <boost/compute/function.hpp>
+#include <boost/compute/system.hpp>
+#include <boost/compute/algorithm/transform.hpp>
+#include <boost/compute/container/vector.hpp>
+#include <boost/compute/types/fundamental.hpp>
+
+namespace compute = boost::compute;
+
+// this example shows how to compute the determinant of many 4x4 matrices
+// using a determinant function and the transform() algorithm. in OpenCL the
+// float16 type can be used to store a 4x4 matrix and the components are laid
+// out in the following order:
+//
+// M = [ s0 s4 s8 sc ]
+//     [ s1 s5 s9 sd ]
+//     [ s2 s6 sa se ]
+//     [ s3 s7 sb sf ]
+//
+// the input matrices are created using eigen's random matrix and then
+// used again at the end to verify the results of the determinant function.
+int main()
+{
+    // get default device and setup context
+    compute::device gpu = compute::system::default_device();
+    compute::context context(gpu);
+    compute::command_queue queue(context, gpu);
+    std::cout << "device: " << gpu.name() << std::endl;
+
+    size_t n = 1000;
+
+    // create random 4x4 matrices on the host
+    std::vector<Eigen::Matrix4f> matrices(n);
+    for(size_t i = 0; i < n; i++){
+        matrices[i] = Eigen::Matrix4f::Random();
+    }
+
+    // copy matrices to the device
+    using compute::float16_;
+    compute::vector<float16_> input(n, context);
+    compute::copy(
+        matrices.begin(), matrices.end(), input.begin(), queue
+    );
+
+    // function returning the determinant of a 4x4 matrix.
+    BOOST_COMPUTE_FUNCTION(float, determinant4x4, (const float16_ m),
+    {
+        return m.s0*m.s5*m.sa*m.sf + m.s0*m.s6*m.sb*m.sd + m.s0*m.s7*m.s9*m.se +
+               m.s1*m.s4*m.sb*m.se + m.s1*m.s6*m.s8*m.sf + m.s1*m.s7*m.sa*m.sc +
+               m.s2*m.s4*m.s9*m.sf + m.s2*m.s5*m.sb*m.sc + m.s2*m.s7*m.s8*m.sd +
+               m.s3*m.s4*m.sa*m.sd + m.s3*m.s5*m.s8*m.se + m.s3*m.s6*m.s9*m.sc -
+               m.s0*m.s5*m.sb*m.se - m.s0*m.s6*m.s9*m.sf - m.s0*m.s7*m.sa*m.sd -
+               m.s1*m.s4*m.sa*m.sf - m.s1*m.s6*m.sb*m.sc - m.s1*m.s7*m.s8*m.se -
+               m.s2*m.s4*m.sb*m.sd - m.s2*m.s5*m.s8*m.sf - m.s2*m.s7*m.s9*m.sc -
+               m.s3*m.s4*m.s9*m.se - m.s3*m.s5*m.sa*m.sc - m.s3*m.s6*m.s8*m.sd;
+    });
+
+    // calculate determinants on the gpu
+    compute::vector<float> determinants(n, context);
+    compute::transform(
+        input.begin(), input.end(), determinants.begin(), determinant4x4, queue
+    );
+
+    // check determinants
+    std::vector<float> host_determinants(n);
+    compute::copy(
+        determinants.begin(), determinants.end(), host_determinants.begin(), queue
+    );
+
+    for(size_t i = 0; i < n; i++){
+        float det = matrices[i].determinant();
+
+        if(std::abs(det - host_determinants[i]) > 1e-6){
+          std::cerr << "error: wrong determinant at " << i << " ("
+                    << host_determinants[i] << " != " << det << ")"
+                    << std::endl;
+            return -1;
+        }
+    }
+
+    return 0;
+}