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<div id="projectname">ViennaCL - The Vienna Computing Library
 <span id="projectnumber">1.7.1</span>
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<div id="projectbrief">Free open-source GPU-accelerated linear algebra and solver library.</div>
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<div class="title">multithreaded_cg.cpp</div> </div>
</div><!--header-->
<div class="contents">
<p>This tutorial shows how to run multiple instances of a conjugate gradient solver, one instance per GPU.</p>
<p>We start with including the necessary headers: </p>
<div class="fragment"><div class="line"><span class="preprocessor">#ifndef VIENNACL_WITH_OPENCL</span></div>
<div class="line"><span class="preprocessor"> #define VIENNACL_WITH_OPENCL</span></div>
<div class="line"><span class="preprocessor">#endif</span></div>
<div class="line"></div>
<div class="line"><span class="comment">// include necessary system headers</span></div>
<div class="line"><span class="preprocessor">#include <iostream></span></div>
<div class="line"></div>
<div class="line"><span class="comment">//</span></div>
<div class="line"><span class="comment">// ublas includes</span></div>
<div class="line"><span class="comment">//</span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/io.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/triangular.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/matrix_sparse.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/matrix.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/matrix_proxy.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/operation.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/operation_sparse.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/io.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/lu.hpp></span></div>
<div class="line"></div>
<div class="line"><span class="comment">// Must be set if you want to use ViennaCL algorithms on ublas objects</span></div>
<div class="line"><span class="preprocessor">#define VIENNACL_WITH_UBLAS 1</span></div>
<div class="line"></div>
<div class="line"></div>
<div class="line"><span class="comment">//include basic scalar and vector types of ViennaCL</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="scalar_8hpp.html">viennacl/scalar.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="vector_8hpp.html">viennacl/vector.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="compressed__matrix_8hpp.html">viennacl/compressed_matrix.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="matrix__market_8hpp.html">viennacl/io/matrix_market.hpp</a>"</span></div>
<div class="line"></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="device_8hpp.html">viennacl/ocl/device.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="platform_8hpp.html">viennacl/ocl/platform.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="backend_8hpp.html">viennacl/ocl/backend.hpp</a>"</span></div>
<div class="line"></div>
<div class="line"><span class="comment">//include the generic inner product functions of ViennaCL</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="norm__2_8hpp.html">viennacl/linalg/norm_2.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="cg_8hpp.html">viennacl/linalg/cg.hpp</a>"</span></div>
<div class="line"></div>
<div class="line"><span class="comment">// Some helper functions for this tutorial:</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="vector-io_8hpp.html">vector-io.hpp</a>"</span></div>
<div class="line"></div>
<div class="line"><span class="keyword">using namespace </span>boost::numeric;</div>
</div><!-- fragment --><p> This tutorial uses Boost.Thread for threading. Other threading approaches (e.g. pthreads) also work. </p>
<div class="fragment"><div class="line"><span class="preprocessor">#include <boost/thread.hpp></span></div>
</div><!-- fragment --><p> This functor represents the work carried out in each thread. It creates the necessary objects, loads the data, and executes the CG solver. </p>
<div class="fragment"><div class="line"><span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><span class="keyword">class </span>worker</div>
<div class="line">{</div>
<div class="line"><span class="keyword">public</span>:</div>
<div class="line"> worker(std::size_t tid) : thread_id_(tid) {}</div>
</div><!-- fragment --><p> The functor interface, entry point for each thread. </p>
<div class="fragment"><div class="line"><span class="keywordtype">void</span> operator()()</div>
<div class="line">{</div>
</div><!-- fragment --><p> Set up some ublas objects </p>
<div class="fragment"><div class="line">ublas::vector<NumericT> rhs;</div>
<div class="line">ublas::vector<NumericT> ref_result;</div>
<div class="line">ublas::compressed_matrix<NumericT> ublas_matrix;</div>
</div><!-- fragment --><p> Read system from file. You may also assemble everything on the fly here. </p>
<div class="fragment"><div class="line"><span class="keywordflow">if</span> (!<a name="a0"></a><a class="code" href="namespaceviennacl_1_1io.html#ad934125ed3dbe661e264bcd7d62b1048">viennacl::io::read_matrix_market_file</a>(ublas_matrix, <span class="stringliteral">"../examples/testdata/mat65k.mtx"</span>))</div>
<div class="line">{</div>
<div class="line"> std::cout << <span class="stringliteral">"Error reading Matrix file"</span> << std::endl;</div>
<div class="line"> <span class="keywordflow">return</span>;</div>
<div class="line">}</div>
<div class="line"></div>
<div class="line"><span class="keywordflow">if</span> (!<a name="a1"></a><a class="code" href="vector-io_8hpp.html#a303954a45833b84192a6dcf3065f85e3">readVectorFromFile</a>(<span class="stringliteral">"../examples/testdata/rhs65025.txt"</span>, rhs))</div>
<div class="line">{</div>
<div class="line"> std::cout << <span class="stringliteral">"Error reading RHS file"</span> << std::endl;</div>
<div class="line"> <span class="keywordflow">return</span>;</div>
<div class="line">}</div>
<div class="line"></div>
<div class="line"><span class="keywordflow">if</span> (!<a class="code" href="vector-io_8hpp.html#a303954a45833b84192a6dcf3065f85e3">readVectorFromFile</a>(<span class="stringliteral">"../examples/testdata/result65025.txt"</span>, ref_result))</div>
<div class="line">{</div>
<div class="line"> std::cout << <span class="stringliteral">"Error reading Result file"</span> << std::endl;</div>
<div class="line"> <span class="keywordflow">return</span>;</div>
<div class="line">}</div>
</div><!-- fragment --><p> Set up some ViennaCL objects in the respective context. It is important to place the objects in the correct context (associated with each thread) </p>
<div class="fragment"><div class="line"><a name="_a2"></a><a class="code" href="classviennacl_1_1context.html">viennacl::context</a> ctx(<a name="a3"></a><a class="code" href="namespaceviennacl_1_1ocl.html#a82c1aba632a7ee0991eee480d5340966">viennacl::ocl::get_context</a>(static_cast<long>(thread_id_)));</div>
<div class="line"></div>
<div class="line">std::size_t vcl_size = rhs.size();</div>
<div class="line"><a name="_a4"></a><a class="code" href="classviennacl_1_1compressed__matrix.html">viennacl::compressed_matrix<NumericT></a> vcl_compressed_matrix(ctx);</div>
<div class="line"><a name="_a5"></a><a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> vcl_rhs(vcl_size, ctx);</div>
<div class="line"><a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> vcl_ref_result(vcl_size, ctx);</div>
<div class="line"></div>
<div class="line"><a name="a6"></a><a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(rhs.begin(), rhs.end(), vcl_rhs.begin());</div>
<div class="line"><a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(ref_result.begin(), ref_result.end(), vcl_ref_result.begin());</div>
</div><!-- fragment --><p> Transfer ublas-matrix to ViennaCL objects sitting on the GPU: </p>
<div class="fragment"><div class="line"> <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(ublas_matrix, vcl_compressed_matrix);</div>
<div class="line"></div>
<div class="line"> <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> vcl_result = <a name="a7"></a><a class="code" href="namespaceviennacl_1_1linalg.html#a6e9b329b64ac782e6a5687ad2fc47a2a">viennacl::linalg::solve</a>(vcl_compressed_matrix, vcl_rhs, <a name="_a8"></a><a class="code" href="classviennacl_1_1linalg_1_1cg__tag.html">viennacl::linalg::cg_tag</a>());</div>
<div class="line"></div>
<div class="line"> std::stringstream ss;</div>
<div class="line"> ss << <span class="stringliteral">"Result of thread "</span> << thread_id_ << <span class="stringliteral">" on device "</span> << <a class="code" href="namespaceviennacl_1_1ocl.html#a82c1aba632a7ee0991eee480d5340966">viennacl::ocl::get_context</a>(static_cast<long>(thread_id_)).<a name="a9"></a><a class="code" href="classviennacl_1_1ocl_1_1context.html#a122abd131e682733ff44bdf480365ba2">devices</a>()[0].name() << <span class="stringliteral">": "</span> << vcl_result[0] << <span class="stringliteral">", should: "</span> << ref_result[0] << std::endl;</div>
<div class="line"> message_ = ss.str();</div>
<div class="line"> }</div>
<div class="line"></div>
<div class="line"> std::string message()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> message_; }</div>
<div class="line"></div>
<div class="line"><span class="keyword">private</span>:</div>
<div class="line"> std::string message_;</div>
<div class="line"> std::size_t thread_id_;</div>
<div class="line">};</div>
</div><!-- fragment --><p> In the main routine we create two OpenCL contexts and then use one thread per context to run the CG solver in the functor defined above. </p>
<div class="fragment"><div class="line"><span class="keywordtype">int</span> <a name="a10"></a><a class="code" href="tests_2src_2bisect_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a>()</div>
<div class="line">{</div>
<div class="line"> <span class="comment">//Change this type definition to double if your gpu supports that</span></div>
<div class="line"> <span class="keyword">typedef</span> <span class="keywordtype">float</span> <a name="a11"></a><a class="code" href="fft__1d_8cpp.html#ad5c19ca4f47d3f8ec21232a5af2624e5">ScalarType</a>;</div>
<div class="line"></div>
<div class="line"> <span class="keywordflow">if</span> (<a name="a12"></a><a class="code" href="namespaceviennacl_1_1ocl.html#ae1e931f6efd155240b33ca440dfcfef5">viennacl::ocl::get_platforms</a>().<a name="a13"></a><a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>() == 0)</div>
<div class="line"> {</div>
<div class="line"> std::cerr << <span class="stringliteral">"Error: No platform found!"</span> << std::endl;</div>
<div class="line"> <span class="keywordflow">return</span> EXIT_FAILURE;</div>
<div class="line"> }</div>
</div><!-- fragment --><p> Part 1: Setup first device for first context, second device for second context: </p>
<div class="fragment"><div class="line"><a name="_a14"></a><a class="code" href="classviennacl_1_1ocl_1_1platform.html">viennacl::ocl::platform</a> pf = <a class="code" href="namespaceviennacl_1_1ocl.html#ae1e931f6efd155240b33ca440dfcfef5">viennacl::ocl::get_platforms</a>()[0];</div>
<div class="line">std::vector<viennacl::ocl::device> <span class="keyword">const</span> & devices = pf.<a name="a15"></a><a class="code" href="classviennacl_1_1ocl_1_1platform.html#afaa563522ebe9ce7b80ef02c40e7fe31">devices</a>();</div>
<div class="line"></div>
<div class="line"><span class="comment">// Set first device to first context:</span></div>
<div class="line"><a name="a16"></a><a class="code" href="namespaceviennacl_1_1ocl.html#add1725d48cfd159ce187e287369d1cdb">viennacl::ocl::setup_context</a>(0, devices[0]);</div>
<div class="line"></div>
<div class="line"><span class="comment">// Set second device for second context (use the same device for the second context if only one device available):</span></div>
<div class="line"><span class="keywordflow">if</span> (devices.size() > 1)</div>
<div class="line"> <a class="code" href="namespaceviennacl_1_1ocl.html#add1725d48cfd159ce187e287369d1cdb">viennacl::ocl::setup_context</a>(1, devices[1]);</div>
<div class="line"><span class="keywordflow">else</span></div>
<div class="line"> <a class="code" href="namespaceviennacl_1_1ocl.html#add1725d48cfd159ce187e287369d1cdb">viennacl::ocl::setup_context</a>(1, devices[0]);</div>
</div><!-- fragment --><p> Part 2: Now let two threads operate on two GPUs in parallel, each running a CG solver </p>
<div class="fragment"><div class="line">worker<ScalarType> work_functor0(0);</div>
<div class="line">worker<ScalarType> work_functor1(1);</div>
<div class="line">boost::thread worker_thread_0(boost::ref(work_functor0));</div>
<div class="line">boost::thread worker_thread_1(boost::ref(work_functor1));</div>
<div class="line"></div>
<div class="line">worker_thread_0.join();</div>
<div class="line">worker_thread_1.join();</div>
<div class="line"></div>
<div class="line">std::cout << work_functor0.message() << std::endl;</div>
<div class="line">std::cout << work_functor1.message() << std::endl;</div>
</div><!-- fragment --><p> That's it. Print a success message and exit. </p>
<div class="fragment"><div class="line"> std::cout << <span class="stringliteral">"!!!! TUTORIAL COMPLETED SUCCESSFULLY !!!!"</span> << std::endl;</div>
<div class="line"></div>
<div class="line"> <span class="keywordflow">return</span> EXIT_SUCCESS;</div>
<div class="line">}</div>
</div><!-- fragment --> <h2>Full Example Code</h2>
<div class="fragment"><div class="line"><span class="comment">/* =========================================================================</span></div>
<div class="line"><span class="comment"> Copyright (c) 2010-2016, Institute for Microelectronics,</span></div>
<div class="line"><span class="comment"> Institute for Analysis and Scientific Computing,</span></div>
<div class="line"><span class="comment"> TU Wien.</span></div>
<div class="line"><span class="comment"> Portions of this software are copyright by UChicago Argonne, LLC.</span></div>
<div class="line"><span class="comment"></span></div>
<div class="line"><span class="comment"> -----------------</span></div>
<div class="line"><span class="comment"> ViennaCL - The Vienna Computing Library</span></div>
<div class="line"><span class="comment"> -----------------</span></div>
<div class="line"><span class="comment"></span></div>
<div class="line"><span class="comment"> Project Head: Karl Rupp rupp@iue.tuwien.ac.at</span></div>
<div class="line"><span class="comment"></span></div>
<div class="line"><span class="comment"> (A list of authors and contributors can be found in the PDF manual)</span></div>
<div class="line"><span class="comment"></span></div>
<div class="line"><span class="comment"> License: MIT (X11), see file LICENSE in the base directory</span></div>
<div class="line"><span class="comment">============================================================================= */</span></div>
<div class="line"></div>
<div class="line"><span class="preprocessor">#ifndef VIENNACL_WITH_OPENCL</span></div>
<div class="line"><span class="preprocessor"> #define VIENNACL_WITH_OPENCL</span></div>
<div class="line"><span class="preprocessor">#endif</span></div>
<div class="line"></div>
<div class="line"><span class="comment">// include necessary system headers</span></div>
<div class="line"><span class="preprocessor">#include <iostream></span></div>
<div class="line"></div>
<div class="line"><span class="comment">//</span></div>
<div class="line"><span class="comment">// ublas includes</span></div>
<div class="line"><span class="comment">//</span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/io.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/triangular.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/matrix_sparse.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/matrix.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/matrix_proxy.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/operation.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/operation_sparse.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/io.hpp></span></div>
<div class="line"><span class="preprocessor">#include <boost/numeric/ublas/lu.hpp></span></div>
<div class="line"></div>
<div class="line"><span class="comment">// Must be set if you want to use ViennaCL algorithms on ublas objects</span></div>
<div class="line"><span class="preprocessor">#define VIENNACL_WITH_UBLAS 1</span></div>
<div class="line"></div>
<div class="line"></div>
<div class="line"><span class="comment">//include basic scalar and vector types of ViennaCL</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="scalar_8hpp.html">viennacl/scalar.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="vector_8hpp.html">viennacl/vector.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="compressed__matrix_8hpp.html">viennacl/compressed_matrix.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="matrix__market_8hpp.html">viennacl/io/matrix_market.hpp</a>"</span></div>
<div class="line"></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="device_8hpp.html">viennacl/ocl/device.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="platform_8hpp.html">viennacl/ocl/platform.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="backend_8hpp.html">viennacl/ocl/backend.hpp</a>"</span></div>
<div class="line"></div>
<div class="line"><span class="comment">//include the generic inner product functions of ViennaCL</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="norm__2_8hpp.html">viennacl/linalg/norm_2.hpp</a>"</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="cg_8hpp.html">viennacl/linalg/cg.hpp</a>"</span></div>
<div class="line"></div>
<div class="line"><span class="comment">// Some helper functions for this tutorial:</span></div>
<div class="line"><span class="preprocessor">#include "<a class="code" href="vector-io_8hpp.html">vector-io.hpp</a>"</span></div>
<div class="line"></div>
<div class="line"><span class="keyword">using namespace </span>boost::numeric;</div>
<div class="line"></div>
<div class="line"><span class="preprocessor">#include <boost/thread.hpp></span></div>
<div class="line"></div>
<div class="line"><span class="keyword">template</span><<span class="keyword">typename</span> NumericT></div>
<div class="line"><span class="keyword">class </span>worker</div>
<div class="line">{</div>
<div class="line"><span class="keyword">public</span>:</div>
<div class="line"> worker(std::size_t tid) : thread_id_(tid) {}</div>
<div class="line"></div>
<div class="line"> <span class="keywordtype">void</span> operator()()</div>
<div class="line"> {</div>
<div class="line"> ublas::vector<NumericT> rhs;</div>
<div class="line"> ublas::vector<NumericT> ref_result;</div>
<div class="line"> ublas::compressed_matrix<NumericT> ublas_matrix;</div>
<div class="line"></div>
<div class="line"> <span class="keywordflow">if</span> (!<a class="code" href="namespaceviennacl_1_1io.html#ad934125ed3dbe661e264bcd7d62b1048">viennacl::io::read_matrix_market_file</a>(ublas_matrix, <span class="stringliteral">"../examples/testdata/mat65k.mtx"</span>))</div>
<div class="line"> {</div>
<div class="line"> std::cout << <span class="stringliteral">"Error reading Matrix file"</span> << std::endl;</div>
<div class="line"> <span class="keywordflow">return</span>;</div>
<div class="line"> }</div>
<div class="line"></div>
<div class="line"> <span class="keywordflow">if</span> (!<a class="code" href="vector-io_8hpp.html#a303954a45833b84192a6dcf3065f85e3">readVectorFromFile</a>(<span class="stringliteral">"../examples/testdata/rhs65025.txt"</span>, rhs))</div>
<div class="line"> {</div>
<div class="line"> std::cout << <span class="stringliteral">"Error reading RHS file"</span> << std::endl;</div>
<div class="line"> <span class="keywordflow">return</span>;</div>
<div class="line"> }</div>
<div class="line"></div>
<div class="line"> <span class="keywordflow">if</span> (!<a class="code" href="vector-io_8hpp.html#a303954a45833b84192a6dcf3065f85e3">readVectorFromFile</a>(<span class="stringliteral">"../examples/testdata/result65025.txt"</span>, ref_result))</div>
<div class="line"> {</div>
<div class="line"> std::cout << <span class="stringliteral">"Error reading Result file"</span> << std::endl;</div>
<div class="line"> <span class="keywordflow">return</span>;</div>
<div class="line"> }</div>
<div class="line"></div>
<div class="line"> <a class="code" href="classviennacl_1_1context.html">viennacl::context</a> ctx(<a class="code" href="namespaceviennacl_1_1ocl.html#a82c1aba632a7ee0991eee480d5340966">viennacl::ocl::get_context</a>(static_cast<long>(thread_id_)));</div>
<div class="line"></div>
<div class="line"> std::size_t vcl_size = rhs.size();</div>
<div class="line"> <a class="code" href="classviennacl_1_1compressed__matrix.html">viennacl::compressed_matrix<NumericT></a> vcl_compressed_matrix(ctx);</div>
<div class="line"> <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> vcl_rhs(vcl_size, ctx);</div>
<div class="line"> <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> vcl_ref_result(vcl_size, ctx);</div>
<div class="line"></div>
<div class="line"> <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(rhs.begin(), rhs.end(), vcl_rhs.<a name="a17"></a><a class="code" href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">begin</a>());</div>
<div class="line"> <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(ref_result.begin(), ref_result.end(), vcl_ref_result.<a class="code" href="classviennacl_1_1vector__base.html#a762d98e2f912fc534951f25555b6077f">begin</a>());</div>
<div class="line"></div>
<div class="line"></div>
<div class="line"> <a class="code" href="namespaceviennacl.html#a10b7f8cf6b8864a7aa196d670481a453">viennacl::copy</a>(ublas_matrix, vcl_compressed_matrix);</div>
<div class="line"></div>
<div class="line"> <a class="code" href="classviennacl_1_1vector.html">viennacl::vector<NumericT></a> vcl_result = <a class="code" href="namespaceviennacl_1_1linalg.html#a6e9b329b64ac782e6a5687ad2fc47a2a">viennacl::linalg::solve</a>(vcl_compressed_matrix, vcl_rhs, <a class="code" href="classviennacl_1_1linalg_1_1cg__tag.html">viennacl::linalg::cg_tag</a>());</div>
<div class="line"></div>
<div class="line"> std::stringstream ss;</div>
<div class="line"> ss << <span class="stringliteral">"Result of thread "</span> << thread_id_ << <span class="stringliteral">" on device "</span> << <a class="code" href="namespaceviennacl_1_1ocl.html#a82c1aba632a7ee0991eee480d5340966">viennacl::ocl::get_context</a>(static_cast<long>(thread_id_)).<a class="code" href="classviennacl_1_1ocl_1_1context.html#a122abd131e682733ff44bdf480365ba2">devices</a>()[0].name() << <span class="stringliteral">": "</span> << vcl_result[0] << <span class="stringliteral">", should: "</span> << ref_result[0] << std::endl;</div>
<div class="line"> message_ = ss.str();</div>
<div class="line"> }</div>
<div class="line"></div>
<div class="line"> std::string message()<span class="keyword"> const </span>{ <span class="keywordflow">return</span> message_; }</div>
<div class="line"></div>
<div class="line"><span class="keyword">private</span>:</div>
<div class="line"> std::string message_;</div>
<div class="line"> std::size_t thread_id_;</div>
<div class="line">};</div>
<div class="line"></div>
<div class="line"><span class="keywordtype">int</span> <a class="code" href="tests_2src_2bisect_8cpp.html#ae66f6b31b5ad750f1fe042a706a4e3d4">main</a>()</div>
<div class="line">{</div>
<div class="line"> <span class="comment">//Change this type definition to double if your gpu supports that</span></div>
<div class="line"> <span class="keyword">typedef</span> <span class="keywordtype">float</span> <a class="code" href="fft__1d_8cpp.html#ad5c19ca4f47d3f8ec21232a5af2624e5">ScalarType</a>;</div>
<div class="line"></div>
<div class="line"> <span class="keywordflow">if</span> (<a class="code" href="namespaceviennacl_1_1ocl.html#ae1e931f6efd155240b33ca440dfcfef5">viennacl::ocl::get_platforms</a>().<a class="code" href="namespaceviennacl_1_1traits.html#aa2344ea20469f55fbc15a8e9526494d0">size</a>() == 0)</div>
<div class="line"> {</div>
<div class="line"> std::cerr << <span class="stringliteral">"Error: No platform found!"</span> << std::endl;</div>
<div class="line"> <span class="keywordflow">return</span> EXIT_FAILURE;</div>
<div class="line"> }</div>
<div class="line"></div>
<div class="line"> <a class="code" href="classviennacl_1_1ocl_1_1platform.html">viennacl::ocl::platform</a> pf = <a class="code" href="namespaceviennacl_1_1ocl.html#ae1e931f6efd155240b33ca440dfcfef5">viennacl::ocl::get_platforms</a>()[0];</div>
<div class="line"> std::vector<viennacl::ocl::device> <span class="keyword">const</span> & devices = pf.<a class="code" href="classviennacl_1_1ocl_1_1platform.html#afaa563522ebe9ce7b80ef02c40e7fe31">devices</a>();</div>
<div class="line"></div>
<div class="line"> <span class="comment">// Set first device to first context:</span></div>
<div class="line"> <a class="code" href="namespaceviennacl_1_1ocl.html#add1725d48cfd159ce187e287369d1cdb">viennacl::ocl::setup_context</a>(0, devices[0]);</div>
<div class="line"></div>
<div class="line"> <span class="comment">// Set second device for second context (use the same device for the second context if only one device available):</span></div>
<div class="line"> <span class="keywordflow">if</span> (devices.size() > 1)</div>
<div class="line"> <a class="code" href="namespaceviennacl_1_1ocl.html#add1725d48cfd159ce187e287369d1cdb">viennacl::ocl::setup_context</a>(1, devices[1]);</div>
<div class="line"> <span class="keywordflow">else</span></div>
<div class="line"> <a class="code" href="namespaceviennacl_1_1ocl.html#add1725d48cfd159ce187e287369d1cdb">viennacl::ocl::setup_context</a>(1, devices[0]);</div>
<div class="line"></div>
<div class="line"> worker<ScalarType> work_functor0(0);</div>
<div class="line"> worker<ScalarType> work_functor1(1);</div>
<div class="line"> boost::thread worker_thread_0(boost::ref(work_functor0));</div>
<div class="line"> boost::thread worker_thread_1(boost::ref(work_functor1));</div>
<div class="line"></div>
<div class="line"> worker_thread_0.join();</div>
<div class="line"> worker_thread_1.join();</div>
<div class="line"></div>
<div class="line"> std::cout << work_functor0.message() << std::endl;</div>
<div class="line"> std::cout << work_functor1.message() << std::endl;</div>
<div class="line"></div>
<div class="line"> std::cout << <span class="stringliteral">"!!!! TUTORIAL COMPLETED SUCCESSFULLY !!!!"</span> << std::endl;</div>
<div class="line"></div>
<div class="line"> <span class="keywordflow">return</span> EXIT_SUCCESS;</div>
<div class="line">}</div>
<div class="line"></div>
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