More efficient access pattern in the GEMV kernel
This commit is contained in:
@@ -10,8 +10,8 @@ namespace atidlas
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mreduction_parameters::mreduction_parameters(unsigned int _simd_width,
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unsigned int _local_size_0, unsigned int _local_size_1,
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unsigned int _num_groups_0, fetching_policy_type _fetch_policy): base::parameters_type(_simd_width, _local_size_0, _local_size_1, 1),
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num_groups_0(_num_groups_0), num_groups_1(2), fetch_policy(_fetch_policy) { }
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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),
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num_groups_0(_num_groups_0), num_groups_1(_num_groups_1), fetch_policy(_fetch_policy) { }
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int mreduction::check_invalid_impl(cl::Device const &, expressions_tuple const &) const
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@@ -29,8 +29,7 @@ unsigned int mreduction::lmem_usage() const
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std::string mreduction::generate_impl(unsigned int label, expressions_tuple const & expressions, std::vector<mapping_type> const & mappings, unsigned int simd_width, std::vector<mapped_mreduction*> const & exprs) const
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{
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using tools::to_string;
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unsigned int local_size_1_ld = p_.local_size_1+1;
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std::string local_size_1_ld_str = to_string(local_size_1_ld);
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kernel_generation_stream stream;
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@@ -61,13 +60,16 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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{"array2", "#pointer += #start1 + #start2*#ld; "
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"#ld *= #nldstride; "}}, expressions, mappings);
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unsigned int local_size_0_ld = p_.local_size_0+1;
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std::string local_size_0_ld_str = to_string(local_size_0_ld);
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for (const auto & e : exprs)
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stream << e->process("__local #scalartype #name_buf[" + to_string(p_.local_size_0*local_size_1_ld) + "];") << std::endl;
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stream << e->process("__local #scalartype #name_buf[" + to_string(p_.local_size_1*local_size_0_ld) + "];") << std::endl;
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stream << "unsigned int lid0 = get_local_id(0);" << std::endl;
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stream << "unsigned int lid1 = get_local_id(1);" << std::endl;
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stream << "unsigned int upper_bound_0 = ( M +" << p_.local_size_0 - 1 << ")/" << p_.local_size_0 << "*" << p_.local_size_0 << ";" << std::endl;
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stream << "for(unsigned int r = get_global_id(0); r < upper_bound_0; r += get_global_size(0)){" << std::endl;
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stream << "unsigned int upper_bound_1 = ( M +" << p_.local_size_1 - 1 << ")/" << p_.local_size_1 << "*" << p_.local_size_1 << ";" << std::endl;
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stream << "for(unsigned int r = get_global_id(1); r < upper_bound_1; r += get_global_size(1)){" << std::endl;
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stream.inc_tab();
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for (const auto & e : exprs)
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@@ -77,7 +79,7 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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stream << "{" << std::endl;
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stream.inc_tab();
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element_wise_loop_1D(stream, p_.fetch_policy, simd_width, "c", "N", "get_global_id(1)", "get_global_size(1)", [&](unsigned int simd_width)
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element_wise_loop_1D(stream, p_.fetch_policy, simd_width, "c", "N", "get_global_id(0)", "get_global_size(0)", [&](unsigned int simd_width)
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{
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std::string data_type = append_width("#scalartype",simd_width);
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@@ -121,25 +123,25 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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stream << "}" << std::endl;
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for (auto & expr : exprs)
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stream << expr->process("#name_buf[lid0*" + local_size_1_ld_str + "+ lid1] = #name_acc;") << std::endl;
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stream << expr->process("#name_buf[lid1*" + local_size_0_ld_str + "+ lid0] = #name_acc;") << std::endl;
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stream << "#pragma unroll" << std::endl;
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stream << "for(unsigned int stride = " << p_.local_size_1/2 << "; stride >0; stride /=2)" << std::endl;
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stream << "for(unsigned int stride = " << p_.local_size_0/2 << "; stride >0; stride /=2)" << std::endl;
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stream << "{" << std::endl;
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stream.inc_tab();
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stream << "barrier(CLK_LOCAL_MEM_FENCE); " << std::endl;
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stream << "if (lid1 < stride)" << std::endl;
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stream << "if (lid0 < stride)" << std::endl;
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stream << "{" << std::endl;
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stream.inc_tab();
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for (auto & e : exprs)
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if (e->is_index_reduction())
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compute_index_reduction(stream, e->process("#name_buf[lid0*" + local_size_1_ld_str + " + lid1]"), e->process("#name_buf[lid0*" + local_size_1_ld_str + " + lid1 + stride]")
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, e->process("#name_buf_value[lid0*" + local_size_1_ld_str + " + lid1]"), e->process("#name_buf_value[lid0*" + local_size_1_ld_str + " + lid1 + stride]")
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compute_index_reduction(stream, e->process("#name_buf[lid1*" + local_size_0_ld_str + " + lid0]"), e->process("#name_buf[lid1*" + local_size_0_ld_str + " + lid0 + stride]")
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, e->process("#name_buf_value[lid1*" + local_size_0_ld_str + " + lid0]"), e->process("#name_buf_value[lid1*" + local_size_0_ld_str + " + lid0 + stride]")
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, e->root_op());
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else
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compute_reduction(stream,e->process("#name_buf[lid0*" + local_size_1_ld_str + " + lid1]"), e->process("#name_buf[lid0*" + local_size_1_ld_str + " + lid1 + stride]"), e->root_op());
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compute_reduction(stream,e->process("#name_buf[lid1*" + local_size_0_ld_str + " + lid0]"), e->process("#name_buf[lid1*" + local_size_0_ld_str + " + lid0 + stride]"), e->root_op());
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stream.dec_tab();
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stream << "}" << std::endl;
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@@ -148,16 +150,25 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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stream << "}" << std::endl;
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stream << "if (lid1 == 0 && r < M)";
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stream << "if (lid0 == 0 && r < M)";
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stream << "{" << std::endl;
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stream.inc_tab();
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if(p_.num_groups_0==1)
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{
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std::map<std::string, std::string> accessors;
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accessors["mreduction"] = "#name_buf[lid1*" + local_size_0_ld_str + "]";
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accessors["array1"] = "#pointer[r*#stride]";
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evaluate(stream, PARENT_NODE_TYPE, accessors, expressions, mappings);
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}
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else
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{
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for (mapped_reduction const * e : exprs)
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{
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if (e->is_index_reduction())
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stream << e->process("#name_temp_value[r + M*get_group_id(1)] = #name_buf_value[lid0*" + local_size_1_ld_str + "];") << std::endl;
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stream << e->process("#name_temp[r + M*get_group_id(1)] = #name_buf[lid0*" + local_size_1_ld_str + "];") << std::endl;
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stream << e->process("#name_temp_value[r + M*get_group_id(0)] = #name_buf_value[lid1*" + local_size_0_ld_str + "];") << std::endl;
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stream << e->process("#name_temp[r + M*get_group_id(0)] = #name_buf[lid1*" + local_size_0_ld_str + "];") << std::endl;
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}
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}
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stream.dec_tab();
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stream << "}" << std::endl;
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@@ -168,6 +179,8 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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stream.dec_tab();
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stream << "}" << std::endl;
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if(p_.num_groups_0>1)
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{
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/////////////////////////////////////////
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////////////// Kernel 2
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////////////////////////////////////////
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@@ -184,12 +197,12 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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"#ld *= #nldstride; "}}, expressions, mappings);
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for (const auto & e : exprs)
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stream << e->process("__local #scalartype #name_buf[" + to_string(p_.local_size_0*local_size_1_ld) + "];") << std::endl;
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stream << e->process("__local #scalartype #name_buf[" + to_string(p_.local_size_1*local_size_0_ld) + "];") << std::endl;
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stream << "unsigned int lid0 = get_local_id(0);" << std::endl;
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stream << "unsigned int lid1 = get_local_id(1);" << std::endl;
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stream << "unsigned int upper_bound_0 = ( M +" << p_.local_size_0 - 1 << ")/" << p_.local_size_0 << "*" << p_.local_size_0 << ";" << std::endl;
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stream << "for(unsigned int r = get_global_id(0); r < upper_bound_0; r += get_global_size(0)){" << std::endl;
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stream << "unsigned int upper_bound_1 = ( M +" << p_.local_size_1 - 1 << ")/" << p_.local_size_1 << "*" << p_.local_size_1 << ";" << std::endl;
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stream << "for(unsigned int r = get_global_id(1); r < upper_bound_1; r += get_global_size(1)){" << std::endl;
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stream.inc_tab();
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for (const auto & e : exprs)
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@@ -199,7 +212,7 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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stream << "{" << std::endl;
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stream.inc_tab();
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stream << "for(unsigned int c = get_local_id(1); c < " << p_.num_groups_1 << "; c += get_local_size(1)){" << std::endl;
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stream << "for(unsigned int c = get_local_id(0); c < " << p_.num_groups_0 << "; c += get_local_size(0)){" << std::endl;
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stream.inc_tab();
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for (mapped_reduction* e: exprs)
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@@ -213,25 +226,25 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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stream << "}" << std::endl;
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for (auto & expr : exprs)
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stream << expr->process("#name_buf[lid0*" + local_size_1_ld_str + "+ lid1] = #name_acc;") << std::endl;
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stream << expr->process("#name_buf[lid1*" + local_size_0_ld_str + "+ lid0] = #name_acc;") << std::endl;
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stream << "#pragma unroll" << std::endl;
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stream << "for(unsigned int stride = " << p_.local_size_1/2 << "; stride >0; stride /=2)" << std::endl;
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stream << "for(unsigned int stride = " << p_.local_size_0/2 << "; stride >0; stride /=2)" << std::endl;
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stream << "{" << std::endl;
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stream.inc_tab();
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stream << "barrier(CLK_LOCAL_MEM_FENCE); " << std::endl;
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stream << "if (lid1 < stride)" << std::endl;
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stream << "if (lid0 < stride)" << std::endl;
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stream << "{" << std::endl;
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stream.inc_tab();
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for (auto & e : exprs)
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if (e->is_index_reduction())
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compute_index_reduction(stream, e->process("#name_buf[lid0*" + local_size_1_ld_str + " + lid1]"), e->process("#name_buf[lid0*" + local_size_1_ld_str + " + lid1 + stride]")
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, e->process("#name_buf_value[lid0*" + local_size_1_ld_str + " + lid1]"), e->process("#name_buf_value[lid0*" + local_size_1_ld_str + " + lid1 + stride]")
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compute_index_reduction(stream, e->process("#name_buf[lid1*" + local_size_0_ld_str + " + lid0]"), e->process("#name_buf[lid1*" + local_size_0_ld_str + " + lid0 + stride]")
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, e->process("#name_buf_value[lid1*" + local_size_0_ld_str + " + lid0]"), e->process("#name_buf_value[lid1*" + local_size_0_ld_str + " + lid0 + stride]")
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, e->root_op());
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else
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compute_reduction(stream,e->process("#name_buf[lid0*" + local_size_1_ld_str + " + lid1]"), e->process("#name_buf[lid0*" + local_size_1_ld_str + " + lid1 + stride]"), e->root_op());
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compute_reduction(stream,e->process("#name_buf[lid1*" + local_size_0_ld_str + " + lid0]"), e->process("#name_buf[lid1*" + local_size_0_ld_str + " + lid0 + stride]"), e->root_op());
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stream.dec_tab();
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stream << "}" << std::endl;
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@@ -240,12 +253,12 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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stream << "}" << std::endl;
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stream << "if (lid1 == 0 && r < M)";
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stream << "if (lid0 == 0 && r < M)";
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stream << "{" << std::endl;
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stream.inc_tab();
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std::map<std::string, std::string> accessors;
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accessors["mreduction"] = "#name_buf[lid0*" + local_size_1_ld_str + "]";
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accessors["mreduction"] = "#name_buf[lid1*" + local_size_0_ld_str + "]";
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accessors["array1"] = "#pointer[r*#stride]";
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evaluate(stream, PARENT_NODE_TYPE, accessors, expressions, mappings);
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@@ -258,7 +271,7 @@ std::string mreduction::generate_impl(unsigned int label, expressions_tuple cons
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stream.dec_tab();
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stream << "}" << std::endl;
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}
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// std::cout << stream.str() << std::endl;
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return stream.str();
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@@ -309,11 +322,6 @@ void mreduction::enqueue(cl::CommandQueue & queue, std::vector<cl_ext::lazy_comp
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expressions_tuple const & expressions = controller.x();
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cl::Context const & context = expressions.context();
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char k0[10];
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char k1[10];
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fill_kernel_name(k0, label, "d0");
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fill_kernel_name(k1, label, "d1");
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std::vector<int_t> MN = input_sizes(expressions);
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std::vector<array_expression::node const *> reductions;
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for (const auto & e : expressions.data())
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@@ -330,21 +338,28 @@ void mreduction::enqueue(cl::CommandQueue & queue, std::vector<cl_ext::lazy_comp
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idx = 1;
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cl::Program & program = programs[idx].program();
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//NDRange
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cl::Kernel kernels[2] = { cl::Kernel(program, k0), cl::Kernel(program, k1)};
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cl::NDRange global[2] = { cl::NDRange(p_.local_size_0*p_.num_groups_0, p_.local_size_1*p_.num_groups_1), cl::NDRange(p_.local_size_0*p_.num_groups_0, p_.local_size_1) };
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cl::NDRange local[2] = { cl::NDRange(p_.local_size_0, p_.local_size_1), cl::NDRange(p_.local_size_0, p_.local_size_1) };
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std::vector< cl::Buffer > tmp;
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std::vector< cl::Buffer > tmpidx;
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unsigned int dtype_size = size_of(lhs_most(expressions.data().front()->tree(), expressions.data().front()->root()).lhs.dtype);
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for (auto & k : kernels)
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char kname[2][10];
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fill_kernel_name(kname[0], label, "d0");
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fill_kernel_name(kname[1], label, "d1");
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unsigned int nk = (p_.num_groups_0==1)?1:2;
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std::vector<cl::Kernel> kernels;
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for(unsigned int k = 0 ; k < nk ; ++k)
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kernels.push_back(cl::Kernel(program, kname[k]));
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for(unsigned int k = 0 ; k < nk ; ++k)
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{
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cl::Kernel & kernel = kernels[k];
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unsigned int n_arg = 0;
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int_t M = MN[0];
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int_t N = MN[1];
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k.setArg(n_arg++, cl_uint(M));
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k.setArg(n_arg++, cl_uint(N));
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kernel.setArg(n_arg++, cl_uint(M));
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kernel.setArg(n_arg++, cl_uint(N));
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//Temporary buffers
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unsigned int i = 0;
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@@ -354,19 +369,22 @@ void mreduction::enqueue(cl::CommandQueue & queue, std::vector<cl_ext::lazy_comp
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if (is_index_reduction(r->op))
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{
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if (tmpidx.size() <= j)
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tmpidx.push_back(cl::Buffer(context, CL_MEM_READ_WRITE, p_.num_groups_1*M*4));
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k.setArg(n_arg++, tmpidx[j]);
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tmpidx.push_back(cl::Buffer(context, CL_MEM_READ_WRITE, p_.num_groups_0*M*4));
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kernel.setArg(n_arg++, tmpidx[j]);
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j++;
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}
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if (tmp.size() <= i)
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tmp.push_back(cl::Buffer(context, CL_MEM_READ_WRITE, p_.num_groups_1*M*dtype_size));
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k.setArg(n_arg++, tmp[i]);
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tmp.push_back(cl::Buffer(context, CL_MEM_READ_WRITE, p_.num_groups_0*M*dtype_size));
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kernel.setArg(n_arg++, tmp[i]);
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i++;
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}
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set_arguments(expressions, k, n_arg);
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set_arguments(expressions, kernel, n_arg);
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}
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for(unsigned int i = 0 ; i < 2 ; ++i)
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//NDRange
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cl::NDRange global[2] = { cl::NDRange(p_.local_size_0*p_.num_groups_0, p_.local_size_1*p_.num_groups_1), cl::NDRange(p_.local_size_0, p_.local_size_1*p_.num_groups_1) };
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cl::NDRange local[2] = { cl::NDRange(p_.local_size_0, p_.local_size_1), cl::NDRange(p_.local_size_0, p_.local_size_1) };
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for(unsigned int i = 0 ; i < nk ; ++i)
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controller.execution_options().enqueue_cache(queue, kernels[i], cl::NullRange, global[i], local[i]);
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}
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@@ -375,8 +393,8 @@ mreduction_rows::mreduction_rows(mreduction_parameters const & parameters,
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mreduction(parameters, REDUCE_ROWS, binding_policy){}
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mreduction_rows::mreduction_rows(unsigned int simd, unsigned int ls1, unsigned int ls2,
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unsigned int ng, fetching_policy_type fetch, binding_policy_t bind):
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mreduction(mreduction_parameters(simd, ls1, ls2, ng, fetch), REDUCE_ROWS, bind)
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unsigned int ng1, unsigned int ng2, fetching_policy_type fetch, binding_policy_t bind):
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mreduction(mreduction_parameters(simd, ls1, ls2, ng1, ng2, fetch), REDUCE_ROWS, bind)
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{}
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@@ -385,8 +403,8 @@ mreduction_cols::mreduction_cols(mreduction::parameters_type const & parameters
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mreduction(parameters, REDUCE_COLUMNS, binding_policy){}
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mreduction_cols::mreduction_cols(unsigned int simd, unsigned int ls1, unsigned int ls2,
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unsigned int ng, fetching_policy_type fetch, binding_policy_t bind):
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mreduction(mreduction_parameters(simd, ls1, ls2, ng, fetch), REDUCE_COLUMNS, bind)
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unsigned int ng1, unsigned int ng2, fetching_policy_type fetch, binding_policy_t bind):
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mreduction(mreduction_parameters(simd, ls1, ls2, ng1, ng2, fetch), REDUCE_COLUMNS, bind)
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{}
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template class base_impl<mreduction, mreduction_parameters>;
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