#include #include #include "isaac/kernels/stream.h" #include "isaac/kernels/keywords.h" #include "isaac/kernels/templates/gemv.h" #include "tools/arguments.hpp" #include "tools/loop.hpp" #include "tools/reductions.hpp" #include "tools/vector_types.hpp" #include namespace isaac { namespace templates { gemv_parameters::gemv_parameters(unsigned int _simd_width, unsigned int _local_size_0, unsigned int _local_size_1, unsigned int _num_groups_0, unsigned int _num_groups_1, fetching_policy_type _fetch_policy): base::parameters_type(_simd_width, _local_size_0, _local_size_1, 1), num_groups_0(_num_groups_0), num_groups_1(_num_groups_1), fetch_policy(_fetch_policy) { } int gemv::is_invalid_impl(driver::Device const &, expressions_tuple const &) const { if (p_.fetch_policy==FETCH_FROM_LOCAL) return TEMPLATE_INVALID_FETCHING_POLICY_TYPE; return TEMPLATE_VALID; } unsigned int gemv::lmem_usage(const expressions_tuple &) const { return (p_.local_size_0+1)*p_.local_size_1; } std::string gemv::generate_impl(std::string const & suffix, expressions_tuple const & expressions, driver::Device const & device, std::vector const & mappings) const { using tools::to_string; std::vector dots; expressions_tuple::data_type::const_iterator sit; std::vector::const_iterator mit; for (mit = mappings.begin(), sit = expressions.data().begin(); mit != mappings.end(); ++mit, ++sit) { array_expression const & first_expression = *expressions.data().front(); std::vector idx = filter_nodes(&is_dot, first_expression, false); for (auto & elem : idx) dots.push_back((mapped_gemv*)(mit->at(mapping_key(elem, PARENT_NODE_TYPE)).get())); } kernel_generation_stream stream; driver::backend_type backend = device.backend(); std::string _size_t = size_type(device); std::string name[2] = {"prod", "reduce"}; name[0] += suffix; name[1] += suffix; std::string arguments = _size_t + " M, " + _size_t + " N, " ; for (const auto & e : dots) { std::string numeric_type = to_string(lhs_most(e->array_expression().tree(), e->array_expression().root()).lhs.dtype); if (e->is_index_dot()) { arguments += e->process(Global(backend).get() + " unsigned int* #name_temp, "); arguments += e->process(Global(backend).get() + " " + numeric_type + "* #name_temp_value,"); } else arguments += e->process(Global(backend).get() + " " + numeric_type + "* #name_temp, "); } int col_simd_width = (dot_type_ == REDUCE_COLUMNS) ? 1 : p_.simd_width; switch(backend) { #ifdef ISAAC_WITH_CUDA case driver::CUDA: stream << "#include \"helper_math.h\"" << std::endl; break; #endif case driver::OPENCL: stream << " __attribute__((reqd_work_group_size(" << p_.local_size_0 << "," << p_.local_size_1 << ",1)))" << std::endl; break; } stream << KernelPrefix(backend) << " void " << name[0] << "(" << arguments << generate_arguments("#scalartype", device, mappings, expressions) << ")" << std::endl; stream << "{" << std::endl; stream.inc_tab(); process(stream, PARENT_NODE_TYPE, {{"array0", "#scalartype #namereg = #pointer[#start];"}, {"array1", "#pointer += #start;"}, {"array2", "#pointer += #start;"}}, expressions, mappings); unsigned int local_size_0_ld = p_.local_size_0; std::string local_size_0_ld_str = to_string(local_size_0_ld); for (const auto & e : dots) stream << e->process(Local(backend).get() + " " + append_width("#scalartype", col_simd_width) + " #name_buf[" + to_string(p_.local_size_1*local_size_0_ld) + "];") << std::endl; stream << "for(" << _size_t << " r = " << GlobalIdx1(backend) << "*" << col_simd_width << "; r < (M +" << p_.local_size_1 - 1 << ")/" << p_.local_size_1 << "*" << p_.local_size_1*col_simd_width << "; r += " << GlobalSize1(backend) << "*" << col_simd_width << ")" << std::endl; stream << "{" << std::endl; stream.inc_tab(); stream << "" << _size_t << " lidx = " << LocalIdx0(backend) << ";" << std::endl; stream << "" << _size_t << " lidy = " << LocalIdx1(backend) <<";" << std::endl; for (const auto & e : dots){ std::string data_type = append_width("#scalartype",col_simd_width); stream << e->process(data_type + " #name_acc = " + neutral_element((e)->root_op(), backend, "#scalartype") + ";") << std::endl; } stream << "if (r < M)" << std::endl; stream << "{" << std::endl; stream.inc_tab(); element_wise_loop_1D(stream, p_.fetch_policy, (dot_type_==REDUCE_COLUMNS)?p_.simd_width:1, "c", "N", GlobalIdx0(backend).get(), GlobalSize0(backend).get(), device, [&](unsigned int row_simd_width) { for (const auto & e : dots) { std::map accessors; if(dot_type_==REDUCE_COLUMNS) { std::string data_type = append_width("#scalartype",row_simd_width); accessors["array2"] = data_type + " #namereg = " + vload(row_simd_width, "#scalartype", "c*#stride", "#pointer + r*#ld", backend)+";"; accessors["repeat"] = data_type + " #namereg = " + vload(row_simd_width, "#scalartype", "(c%#tuplearg0)*#stride", "#pointer + (r%#tuplearg1)*#stride ", backend)+";"; } else { std::string data_type = append_width("#scalartype",col_simd_width); accessors["array2"] = data_type + " #namereg = " + vload(col_simd_width, "#scalartype", "0", "#pointer + r*#stride + c*#ld", backend) + ";"; accessors["repeat"] = "#scalartype #namereg = $VALUE{(r%#tuplearg0)*#stride, (c%#tuplearg1)*#stride};"; } e->process_recursive(stream, PARENT_NODE_TYPE, accessors); } //Update accumulators std::vector str(row_simd_width); if (row_simd_width==1) str[0] = "#namereg"; else for (unsigned int a = 0; a < row_simd_width; ++a) str[a] = access_vector_type("#namereg",a); for (auto & elem : dots) for (unsigned int a = 0; a < row_simd_width; ++a) { std::string value = elem->evaluate_recursive(LHS_NODE_TYPE, {{"array2", str[a]}, {"repeat", str[a]}, {"array0", "#namereg"}}); if (elem->is_index_dot()) compute_index_dot(stream, elem->process("#name_acc"), "c*"+to_string(row_simd_width) + to_string(a), elem->process("#name_acc_value"), value, elem->root_op()); else compute_dot(stream, elem->process("#name_acc"), value,elem->root_op()); } }); stream.dec_tab(); stream << "}" << std::endl; for (auto & expr : dots) stream << expr->process("#name_buf[lidy*" + local_size_0_ld_str + "+ lidx] = #name_acc;") << std::endl; stream << "#pragma unroll" << std::endl; stream << "for(" << _size_t << " stride = " << p_.local_size_0/2 << "; stride >0; stride /=2)" << std::endl; stream << "{" << std::endl; stream.inc_tab(); stream << LocalBarrier(backend) << ";" << std::endl; stream << "if (lidx < stride)" << std::endl; stream << "{" << std::endl; stream.inc_tab(); for (auto & e : dots) if (e->is_index_dot()) compute_index_dot(stream, e->process("#name_buf[lidy*" + local_size_0_ld_str + " + lidx]"), e->process("#name_buf[lidy*" + local_size_0_ld_str + " + lidx + stride]") , e->process("#name_buf_value[lidy*" + local_size_0_ld_str + " + lidx]"), e->process("#name_buf_value[lidy*" + local_size_0_ld_str + " + lidx + stride]") , e->root_op()); else compute_dot(stream,e->process("#name_buf[lidy*" + local_size_0_ld_str + " + lidx]"), e->process("#name_buf[lidy*" + local_size_0_ld_str + " + lidx + stride]"), e->root_op()); stream.dec_tab(); stream << "}" << std::endl; stream.dec_tab(); stream << "}" << std::endl; stream << "if (lidx == 0 && r < M)" << std::endl; stream << "{" << std::endl; stream.inc_tab(); if(p_.num_groups_0==1) { std::map accessors; for(int s = 0 ; s < col_simd_width ; ++s) { accessors["gemv"] = "#name_buf[lidy*" + local_size_0_ld_str + "]"; if(col_simd_width > 1) accessors["gemv"] = access_vector_type(accessors["gemv"], s); accessors["array1"] = "#pointer[(r +" + to_string(s) + ")*#stride]"; evaluate(stream, PARENT_NODE_TYPE, accessors, expressions, mappings); } } else { for (mapped_dot const * e : dots) { if(col_simd_width > 1) stream << "if(M - r > " << col_simd_width << "){" << std::endl; if (e->is_index_dot()) stream << e->process(vstore(col_simd_width,"uint", "#name_buf_value[lidy*" + local_size_0_ld_str + "]", "0", "#name_temp_value + r + M*" + GroupIdx0(backend).get(),backend)) << ";" << std::endl; stream << e->process(vstore(col_simd_width,"#scalartype", "#name_buf[lidy*" + local_size_0_ld_str + "]", "0", "#name_temp + r + M*" + GroupIdx0(backend).get(),backend)) << ";" << std::endl; if(col_simd_width > 1) { stream << "}" << std::endl; stream << "else{" << std::endl; stream.inc_tab(); for(int s = 0 ; s < col_simd_width ; ++s){ if (e->is_index_dot()) stream << "if(r + " << s << "< M) " << e->process("#name_temp_value[r + " + to_string(s) + " + M*" + GroupIdx0(backend).get() + "] = " + access_vector_type("#name_buf_value[lidy*" + local_size_0_ld_str + "]", s)) << ";" << std::endl; stream << "if(r + " << s << "< M) " << e->process("#name_temp[r + " + to_string(s) + " + M*" + GroupIdx0(backend).get() + "] = " + access_vector_type("#name_buf[lidy*" + local_size_0_ld_str + "]", s)) << ";" << std::endl; } stream.dec_tab(); stream << "}" << std::endl; } } } stream.dec_tab(); stream << "}" << std::endl; stream.dec_tab(); stream << "}" << std::endl; stream.dec_tab(); stream << "}" << std::endl; // std::cout << stream.str() << std::endl; if(p_.num_groups_0>1) { ///////////////////////////////////////// ////////////// Kernel 2 //////////////////////////////////////// if(backend==driver::OPENCL) stream << " __attribute__((reqd_work_group_size(" << p_.local_size_0 << "," << p_.local_size_1 << ",1)))" << std::endl; stream << KernelPrefix(backend) << " void " << name[1] << "(" << arguments << generate_arguments("#scalartype", device, mappings, expressions) << ")" << std::endl; stream << "{" << std::endl; stream.inc_tab(); process(stream, PARENT_NODE_TYPE, {{"array0", "#scalartype #namereg = #pointer[#start];"}, {"array1", "#pointer += #start;"}, {"array2", "#pointer += #start; "}}, expressions, mappings); for (const auto & e : dots) stream << e->process(Local(backend).get() + " #scalartype #name_buf[" + to_string(p_.local_size_1*local_size_0_ld) + "];") << std::endl; stream << "for(" << _size_t << " r = " << GlobalIdx1(backend) << "; r < (M +" << p_.local_size_1 - 1 << ")/" << p_.local_size_1 << "*" << p_.local_size_1 << "; r += " << GlobalSize1(backend) << "){" << std::endl; stream.inc_tab(); stream << _size_t << " lidx = " << LocalIdx0(backend) << ";" << std::endl; stream << _size_t << " lidy = " << LocalIdx1(backend) <<";" << std::endl; for (const auto & e : dots) stream << e->process("#scalartype #name_acc = " + neutral_element((e)->root_op(), backend, "#scalartype") + ";") << std::endl; stream << "if (r < M)" << std::endl; stream << "{" << std::endl; stream.inc_tab(); stream << "for(" << _size_t << " c = lidx; c < " << p_.num_groups_0 << "; c += " << LocalSize0(backend) << "){" << std::endl; stream.inc_tab(); for (mapped_dot* e: dots) compute_dot(stream, e->process("#name_acc"), e->process("#name_temp[r + M*c]"), e->root_op()); stream.dec_tab(); stream << "}" << std::endl; stream.dec_tab(); stream << "}" << std::endl; for (auto & expr : dots) stream << expr->process("#name_buf[lidy*" + local_size_0_ld_str + "+ lidx] = #name_acc;") << std::endl; stream << "#pragma unroll" << std::endl; stream << "for(" << _size_t << " stride = " << p_.local_size_0/2 << "; stride >0; stride /=2)" << std::endl; stream << "{" << std::endl; stream.inc_tab(); stream << LocalBarrier(backend) << ";" << std::endl; stream << "if (lidx < stride)" << std::endl; stream << "{" << std::endl; stream.inc_tab(); for (auto & e : dots) if (e->is_index_dot()) compute_index_dot(stream, e->process("#name_buf[lidy*" + local_size_0_ld_str + " + lidx]"), e->process("#name_buf[lidy*" + local_size_0_ld_str + " + lidx + stride]") , e->process("#name_buf_value[lidy*" + local_size_0_ld_str + " + lidx]"), e->process("#name_buf_value[lidy*" + local_size_0_ld_str + " + lidx + stride]") , e->root_op()); else compute_dot(stream,e->process("#name_buf[lidy*" + local_size_0_ld_str + " + lidx]"), e->process("#name_buf[lidy*" + local_size_0_ld_str + " + lidx + stride]"), e->root_op()); stream.dec_tab(); stream << "}" << std::endl; stream.dec_tab(); stream << "}" << std::endl; stream << "if (lidx == 0 && r < M)"; stream << "{" << std::endl; stream.inc_tab(); std::map accessors; accessors["gemv"] = "#name_buf[lidy*" + local_size_0_ld_str + "]"; accessors["array1"] = "#pointer[r*#stride]"; evaluate(stream, PARENT_NODE_TYPE, accessors, expressions, mappings); stream.dec_tab(); stream << "}" << std::endl; stream.dec_tab(); stream << "}" << std::endl; stream.dec_tab(); stream << "}" << std::endl; } return stream.str(); } gemv::gemv(gemv::parameters_type const & parameters, gemv::dot_type rtype, binding_policy_t binding_policy) : base_impl(parameters, binding_policy), dot_type_(rtype){ } std::vector gemv::input_sizes(expressions_tuple const & expressions) const { array_expression const & first_expression = *expressions.data().front(); std::vector idx = filter_nodes(&is_dot, first_expression, false); std::pair MN = matrix_size(lhs_most(first_expression.tree(), idx[0])); if(dot_type_==REDUCE_COLUMNS) std::swap(MN.first,MN.second); return {MN.first, MN.second}; } void gemv::enqueue(driver::CommandQueue & queue, driver::Program const & program, std::string const & suffix, base & fallback, controller const & controller) { expressions_tuple const & expressions = controller.x(); driver::Context const & context = expressions.context(); std::vector MN = input_sizes(expressions); std::vector dots; for (const auto & e : expressions.data()) { std::vector dots_idx = filter_nodes(&is_dot, *e, false); for (auto & r : dots_idx) dots.push_back(&(e)->tree()[r]); } //Fallback if(p_.simd_width>1 && requires_fallback(expressions)) { fallback.enqueue(queue, program, "fallback", fallback, controller); return; } //Kernel std::vector< driver::Buffer > tmp; std::vector< driver::Buffer > tmpidx; unsigned int dtype_size = size_of(lhs_most(expressions.data().front()->tree(), expressions.data().front()->root()).lhs.dtype); std::string name[2] = {"prod", "reduce"}; name[0] += suffix; name[1] += suffix; unsigned int nk = (p_.num_groups_0==1)?1:2; std::vector kernels; for(unsigned int k = 0 ; k < nk ; ++k) kernels.push_back(driver::Kernel(program, name[k].c_str())); for(unsigned int k = 0 ; k < nk ; ++k) { driver::Kernel & kernel = kernels[k]; unsigned int n_arg = 0; int_t M = MN[0]; int_t N = MN[1]; kernel.setSizeArg(n_arg++, M); kernel.setSizeArg(n_arg++, N); //Temporary buffers unsigned int i = 0; unsigned int j = 0; for (auto const & r : dots) { if (is_index_dot(r->op)) { if (tmpidx.size() <= j) tmpidx.push_back(driver::Buffer(context, p_.num_groups_0*M*4)); kernel.setArg(n_arg++, tmpidx[j]); j++; } if (tmp.size() <= i) tmp.push_back(driver::Buffer(context, p_.num_groups_0*M*dtype_size)); kernel.setArg(n_arg++, tmp[i]); i++; } set_arguments(expressions, kernel, n_arg, binding_policy_); } //NDRange driver::NDRange global[2] = { driver::NDRange(p_.local_size_0*p_.num_groups_0, p_.local_size_1*p_.num_groups_1), driver::NDRange(p_.local_size_0, p_.local_size_1*p_.num_groups_1) }; driver::NDRange local[2] = { driver::NDRange(p_.local_size_0, p_.local_size_1), driver::NDRange(p_.local_size_0, p_.local_size_1) }; for(unsigned int i = 0 ; i < nk ; ++i) controller.execution_options().enqueue(program.context(), kernels[i], global[i], local[i]); } gemv_n::gemv_n(gemv_parameters const & parameters, binding_policy_t binding_policy): gemv(parameters, REDUCE_ROWS, binding_policy){} gemv_n::gemv_n(unsigned int simd, unsigned int ls1, unsigned int ls2, unsigned int ng1, unsigned int ng2, fetching_policy_type fetch, binding_policy_t bind): gemv(gemv_parameters(simd, ls1, ls2, ng1, ng2, fetch), REDUCE_ROWS, bind) {} gemv_t::gemv_t(gemv::parameters_type const & parameters, binding_policy_t binding_policy): gemv(parameters, REDUCE_COLUMNS, binding_policy){} gemv_t::gemv_t(unsigned int simd, unsigned int ls1, unsigned int ls2, unsigned int ng1, unsigned int ng2, fetching_policy_type fetch, binding_policy_t bind): gemv(gemv_parameters(simd, ls1, ls2, ng1, ng2, fetch), REDUCE_COLUMNS, bind) {} } }