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https://github.com/OPM/opm-simulators.git
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Tweak ILU opencl kernel launch params
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842a9a9317
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@ -274,7 +274,7 @@ bool BILU0<block_size>::create_preconditioner(BlockedMatrix *mat, BlockedMatrix
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if (verbosity >= 5) {
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out << "color " << color << ": " << firstRow << " - " << lastRow << " = " << lastRow - firstRow << "\n";
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}
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OpenclKernels::ILU_decomp(firstRow, lastRow, s.LUvals, s.LUcols, s.LUrows, s.diagIndex, s.invDiagVals, Nb, block_size);
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OpenclKernels::ILU_decomp(firstRow, lastRow, s.LUvals, s.LUcols, s.LUrows, s.diagIndex, s.invDiagVals, rowsPerColor[color], block_size);
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}
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if (verbosity >= 3) {
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@ -299,17 +299,17 @@ void BILU0<block_size>::apply(const cl::Buffer& y, cl::Buffer& x)
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for (int color = 0; color < numColors; ++color) {
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#if CHOW_PATEL
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OpenclKernels::ILU_apply1(s.Lvals, s.Lcols, s.Lrows, s.diagIndex, y, x, s.rowsPerColor, color, Nb, block_size);
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OpenclKernels::ILU_apply1(s.Lvals, s.Lcols, s.Lrows, s.diagIndex, y, x, s.rowsPerColor, color, rowsPerColor[color], block_size);
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#else
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OpenclKernels::ILU_apply1(s.LUvals, s.LUcols, s.LUrows, s.diagIndex, y, x, s.rowsPerColor, color, Nb, block_size);
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OpenclKernels::ILU_apply1(s.LUvals, s.LUcols, s.LUrows, s.diagIndex, y, x, s.rowsPerColor, color, rowsPerColor[color], block_size);
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#endif
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}
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for (int color = numColors - 1; color >= 0; --color) {
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#if CHOW_PATEL
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OpenclKernels::ILU_apply2(s.Uvals, s.Ucols, s.Urows, s.diagIndex, s.invDiagVals, x, s.rowsPerColor, color, Nb, block_size);
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OpenclKernels::ILU_apply2(s.Uvals, s.Ucols, s.Urows, s.diagIndex, s.invDiagVals, x, s.rowsPerColor, color, rowsPerColor[color], block_size);
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#else
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OpenclKernels::ILU_apply2(s.LUvals, s.LUcols, s.LUrows, s.diagIndex, s.invDiagVals, x, s.rowsPerColor, color, Nb, block_size);
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OpenclKernels::ILU_apply2(s.LUvals, s.LUcols, s.LUrows, s.diagIndex, s.invDiagVals, x, s.rowsPerColor, color, rowsPerColor[color], block_size);
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#endif
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}
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@ -14,7 +14,7 @@ __kernel void ILU_apply1(
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const unsigned int block_size,
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__local double *tmp)
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{
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const unsigned int warpsize = 32;
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const unsigned int warpsize = get_local_size(0);
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const unsigned int bs = block_size;
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const unsigned int idx_t = get_local_id(0);
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const unsigned int num_active_threads = (warpsize/bs/bs)*bs*bs;
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@ -14,7 +14,7 @@ __kernel void ILU_apply2(
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const unsigned int block_size,
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__local double *tmp)
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{
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const unsigned int warpsize = 32;
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const unsigned int warpsize = get_local_size(0);
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const unsigned int bs = block_size;
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const unsigned int idx_t = get_local_id(0);
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const unsigned int num_active_threads = (warpsize/bs/bs)*bs*bs;
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@ -41,6 +41,7 @@ int OpenclKernels::verbosity;
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cl::CommandQueue *OpenclKernels::queue;
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std::vector<double> OpenclKernels::tmp;
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bool OpenclKernels::initialized = false;
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size_t OpenclKernels::preferred_workgroup_size = 0;
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std::unique_ptr<cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, cl::LocalSpaceArg> > OpenclKernels::dot_k;
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std::unique_ptr<cl::KernelFunctor<cl::Buffer&, cl::Buffer&, const unsigned int, cl::LocalSpaceArg> > OpenclKernels::norm_k;
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@ -140,6 +141,11 @@ void OpenclKernels::init(cl::Context *context, cl::CommandQueue *queue_, std::ve
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isaiL_k.reset(new isaiL_kernel_type(cl::Kernel(program, "isaiL")));
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isaiU_k.reset(new isaiU_kernel_type(cl::Kernel(program, "isaiU")));
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// testing shows all kernels have the same preferred_workgroup_size_multiple
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// 32 for NVIDIA
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// 64 for AMD
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cl::Kernel(program, "ILU_apply1").getWorkGroupInfo(devices[0], CL_KERNEL_PREFERRED_WORK_GROUP_SIZE_MULTIPLE, &preferred_workgroup_size_multiple);
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initialized = true;
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} // end get_opencl_kernels()
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@ -388,10 +394,10 @@ void OpenclKernels::ILU_apply1(cl::Buffer& vals, cl::Buffer& cols,
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cl::Buffer& rows, cl::Buffer& diagIndex,
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const cl::Buffer& y, cl::Buffer& x,
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cl::Buffer& rowsPerColor, int color,
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int Nb, unsigned int block_size)
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int rowsThisColor, unsigned int block_size)
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{
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const unsigned int work_group_size = 32;
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const unsigned int num_work_groups = ceilDivision(Nb, work_group_size);
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const unsigned int work_group_size = preferred_workgroup_size_multiple;
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const unsigned int num_work_groups = rowsThisColor;
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const unsigned int total_work_items = num_work_groups * work_group_size;
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const unsigned int lmem_per_work_group = sizeof(double) * work_group_size;
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Timer t_ilu_apply1;
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@ -413,10 +419,10 @@ void OpenclKernels::ILU_apply2(cl::Buffer& vals, cl::Buffer& cols,
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cl::Buffer& rows, cl::Buffer& diagIndex,
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cl::Buffer& invDiagVals, cl::Buffer& x,
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cl::Buffer& rowsPerColor, int color,
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int Nb, unsigned int block_size)
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int rowsThisColor, unsigned int block_size)
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{
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const unsigned int work_group_size = 32;
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const unsigned int num_work_groups = ceilDivision(Nb, work_group_size);
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const unsigned int work_group_size = preferred_workgroup_size_multiple;
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const unsigned int num_work_groups = rowsThisColor;
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const unsigned int total_work_items = num_work_groups * work_group_size;
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const unsigned int lmem_per_work_group = sizeof(double) * work_group_size;
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Timer t_ilu_apply2;
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@ -437,19 +443,19 @@ void OpenclKernels::ILU_apply2(cl::Buffer& vals, cl::Buffer& cols,
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void OpenclKernels::ILU_decomp(int firstRow, int lastRow,
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cl::Buffer& vals, cl::Buffer& cols, cl::Buffer& rows,
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cl::Buffer& diagIndex, cl::Buffer& invDiagVals,
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int Nb, unsigned int block_size)
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int rowsThisColor, unsigned int block_size)
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{
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const unsigned int work_group_size2 = 128;
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const unsigned int num_work_groups2 = 1024;
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const unsigned int total_work_items2 = num_work_groups2 * work_group_size2;
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const unsigned int num_hwarps_per_group = work_group_size2 / 16;
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const unsigned int lmem_per_work_group2 = num_hwarps_per_group * block_size * block_size * sizeof(double); // each block needs a pivot
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const unsigned int work_group_size = 128;
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const unsigned int num_work_groups = rowsThisColor;
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const unsigned int total_work_items = num_work_groups * work_group_size;
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const unsigned int num_hwarps_per_group = work_group_size / 16;
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const unsigned int lmem_per_work_group = num_hwarps_per_group * block_size * block_size * sizeof(double); // each block needs a pivot
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Timer t_ilu_decomp;
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cl::Event event = (*ilu_decomp_k)(cl::EnqueueArgs(*queue, cl::NDRange(total_work_items2), cl::NDRange(work_group_size2)),
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cl::Event event = (*ilu_decomp_k)(cl::EnqueueArgs(*queue, cl::NDRange(total_work_items), cl::NDRange(work_group_size)),
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firstRow, lastRow, vals, cols, rows,
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invDiagVals, diagIndex, Nb,
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cl::Local(lmem_per_work_group2));
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invDiagVals, diagIndex, rowsThisColor,
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cl::Local(lmem_per_work_group));
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if (verbosity >= 4) {
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event.wait();
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@ -64,6 +64,7 @@ private:
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static cl::CommandQueue *queue;
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static std::vector<double> tmp; // used as tmp CPU buffer for dot() and norm()
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static bool initialized;
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static size_t preferred_workgroup_size; // stores CL_KERNEL_PREFERRED_WORK_GROUP_SIZE_MULTIPLE
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static std::unique_ptr<cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, cl::LocalSpaceArg> > dot_k;
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static std::unique_ptr<cl::KernelFunctor<cl::Buffer&, cl::Buffer&, const unsigned int, cl::LocalSpaceArg> > norm_k;
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