├── .gitignore
├── image
    ├── logo.png
    ├── meta.png
    ├── cpp-task.png
    ├── demo_dag.png
    ├── demo_meta.png
    ├── dispatch.png
    ├── demo_meta_a.png
    ├── demo_meta_b.png
    └── demo_thread_data.png
├── .vscode
    ├── settings.json
    └── launch.json
├── test
    ├── main.cpp
    ├── test_find_index.cpp
    ├── test_type_id.cpp
    ├── test_executor.cpp
    ├── test_node.cpp
    ├── test_register_node.cpp
    ├── test_invoke_ex.cpp
    └── test_data_meta.cpp
├── .gitmodules
├── include
    ├── gparallel.h
    ├── executor.h
    ├── meta.h
    ├── util.h
    ├── glist.h
    ├── node_deduce.h
    ├── type_id.h
    ├── invoke_ex.h
    ├── node_schema.h
    ├── meta_decorator.h
    └── dag_schema.h
├── src
    ├── util.cpp
    ├── debug.cpp
    └── dag_schema.cpp
├── .travis.yml
├── CMakeLists.txt
├── demo
    └── advprocess.cpp
├── README.md
└── LICENSE


/.gitignore:
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1 | build
2 | 


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/image/logo.png:
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https://raw.githubusercontent.com/galois-advertising/gparallel/HEAD/image/logo.png


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/image/meta.png:
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https://raw.githubusercontent.com/galois-advertising/gparallel/HEAD/image/meta.png


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/image/cpp-task.png:
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https://raw.githubusercontent.com/galois-advertising/gparallel/HEAD/image/cpp-task.png


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/image/demo_dag.png:
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https://raw.githubusercontent.com/galois-advertising/gparallel/HEAD/image/demo_dag.png


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/image/demo_meta.png:
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https://raw.githubusercontent.com/galois-advertising/gparallel/HEAD/image/demo_meta.png


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/image/dispatch.png:
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https://raw.githubusercontent.com/galois-advertising/gparallel/HEAD/image/dispatch.png


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/.vscode/settings.json:
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1 | {
2 |     "C_Cpp.default.configurationProvider": "vector-of-bool.cmake-tools"
3 | }


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/image/demo_meta_a.png:
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https://raw.githubusercontent.com/galois-advertising/gparallel/HEAD/image/demo_meta_a.png


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/image/demo_meta_b.png:
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https://raw.githubusercontent.com/galois-advertising/gparallel/HEAD/image/demo_meta_b.png


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/image/demo_thread_data.png:
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https://raw.githubusercontent.com/galois-advertising/gparallel/HEAD/image/demo_thread_data.png


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/test/main.cpp:
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1 | #include <iostream>
2 | #include <gtest/gtest.h>
3 | 
4 | 
5 | int main(int argc, char **argv)
6 | {
7 |     ::testing::InitGoogleTest(&argc, argv);
8 |      return RUN_ALL_TESTS();
9 | }


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/.gitmodules:
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1 | [submodule "common"]
2 | 	path = common
3 | 	url = https://github.com/galois-advertising/common
4 | 	branch = master
5 | [submodule "gtest"]
6 | 	path = gtest
7 | 	url = https://github.com/google/googletest.git


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/include/gparallel.h:
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 1 | #pragma once
 2 | #include "dag_schema.h"
 3 | #include "glist.h"
 4 | #include "invoke_ex.h"
 5 | #include "meta.h"
 6 | #include "meta_decorator.h"
 7 | #include "node_deduce.h"
 8 | #include "executor.h"
 9 | #include "node_schema.h"
10 | #include "type_id.h"
11 | #include "util.h"
12 | #include "gparallel.h"
13 | #include "log.h"


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/.vscode/launch.json:
--------------------------------------------------------------------------------
 1 | {
 2 |     "version": "0.2.0",
 3 |     "configurations": [
 4 |         {
 5 |             "name": "(lldb) gparalled",
 6 |             "type": "cppdbg",
 7 |             "request": "launch",
 8 |             "program": "${workspaceRoot}/build/gparallel",
 9 |             "args": [""],
10 |             "stopAtEntry": false,
11 |             "cwd": "${workspaceRoot}",
12 |             "environment": [],
13 |             "externalConsole": true,
14 |             "MIMode": "lldb"
15 |         }
16 |     ]
17 | }


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/test/test_find_index.cpp:
--------------------------------------------------------------------------------
 1 | 
 2 | #include <iostream>
 3 | #include <string>
 4 | #include <gtest/gtest.h>
 5 | #include "gparallel.h"
 6 | #include "log.h"
 7 | 
 8 | struct AA {
 9 |     std::string* data;
10 |     AA(std::string* a) : data(a) {}
11 | };
12 | 
13 | TEST(Test, find_index) {
14 |     using namespace galois::gparallel;
15 |     ASSERT_EQ((find_index<int, 0, double, float, std::string, int>::index), 0);
16 |     ASSERT_EQ((find_index<std::string, 0, double, float, std::string, int>::index), 2);
17 |     ASSERT_EQ((find_index<AA, 0, double, float, std::string*, int>::index), 2);
18 | }


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/test/test_type_id.cpp:
--------------------------------------------------------------------------------
 1 | #include <iostream>
 2 | #include <gtest/gtest.h>
 3 | #include "type_id.h"
 4 | struct test_tag_1 {};
 5 | struct test_tag_2 {};
 6 | TEST(Test, typeid) {
 7 |     using namespace galois::gparallel;
 8 |     std::cout<<type_id<int, test_tag_1>::instance().id()<<std::endl;
 9 |     std::cout<<type_id<int, test_tag_1>::instance().name()<<std::endl;
10 |     std::cout<<type_id<double, test_tag_1>::instance().id()<<std::endl;
11 |     std::cout<<type_id<double, test_tag_1>::instance().name()<<std::endl;
12 |     std::cout<<type_id<double, test_tag_2>::instance().id()<<std::endl;
13 |     std::cout<<type_id<double, test_tag_2>::instance().name()<<std::endl;
14 | }


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/include/executor.h:
--------------------------------------------------------------------------------
 1 | // solopointer1202@gmail.com
 2 | #pragma once
 3 | #include <functional>
 4 | #include "invoke_ex.h"
 5 | 
 6 | namespace galois::gparallel {
 7 | template<class meta_storage_t>
 8 | using executable_t = std::function<void(meta_storage_t*)>;
 9 | 
10 | template<class meta_storage_t, class process_t>
11 | class executor {
12 | private:
13 |     static bool invoke(process_t fn, meta_storage_t* storage) {
14 |         invoke_ex(fn, storage);
15 |         return true;
16 |     }
17 | public:
18 |     static executable_t<meta_storage_t> create(process_t process) {
19 |         return std::bind(&invoke, process, std::placeholders::_1);
20 |     }
21 | };
22 | 
23 | 
24 | };


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/test/test_executor.cpp:
--------------------------------------------------------------------------------
 1 | #include <iostream>
 2 | #include <gtest/gtest.h>
 3 | #include <stdio.h>
 4 | #include "gparallel.h"
 5 | using namespace galois::gparallel;
 6 | 
 7 | struct base {};
 8 | 
 9 | DECL_META(A, base) {
10 | };
11 | 
12 | DECL_META(B, base, A) {
13 | };
14 | 
15 | DECL_META(C, base) {
16 | };
17 | 
18 | struct Process
19 | {
20 |     static void process(input<A> a, input<B> b, output<C> c) {
21 |         TRACE("[gparallel] process succeed", "");
22 |     };
23 | };
24 | 
25 | TEST(Test, executor) {
26 |     using namespace galois::gparallel;
27 |     base b;
28 |     auto exe = executor<base, decltype(Process::process)>::create(Process::process);
29 |     exe(&b);
30 | 
31 | }


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/src/util.cpp:
--------------------------------------------------------------------------------
 1 | // solopointer1202@gmail.com
 2 | #include <map>
 3 | #include <vector>
 4 | #include <string>
 5 | #include <algorithm>
 6 | #include <memory>
 7 | #include "util.h"
 8 | #include "type_id.h"
 9 | 
10 | namespace galois::gparallel {
11 | #ifdef __GNUG__
12 | #include <cstdlib>
13 | #include <cxxabi.h>
14 | // see https://stackoverflow.com/questions/281818/unmangling-the-result-of-stdtype-infoname
15 | std::string demangle(const char* name) {
16 |     int status = -4; // some arbitrary value to eliminate the compiler warning
17 |     // enable c++11 by passing the flag -std=c++11 to g++
18 |     std::unique_ptr<char, void(*)(void*)> res {
19 |         abi::__cxa_demangle(name, NULL, NULL, &status),
20 |         std::free
21 |     };
22 |     return (status==0) ? res.get() : name ;
23 | }
24 | #else
25 | // does nothing if not g++
26 | std::string demangle(const char* name) {
27 |     return name;
28 | }
29 | #endif
30 | 
31 | }


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/include/meta.h:
--------------------------------------------------------------------------------
 1 | // solopointer1202@gmail.com
 2 | #pragma once
 3 | #include "util.h"
 4 | #include "log.h"
 5 | 
 6 | namespace galois::gparallel {
 7 | 
 8 | template <class T, class _meta_storage_t, 
 9 |     template <class> class _meta_name, 
10 |     template <class> class... _super_meta_names>
11 | struct meta_traits : public T {
12 |     typedef meta_info_t<_meta_storage_t, _meta_name, _super_meta_names...> meta_info;
13 |     typedef _meta_storage_t meta_storage_t;
14 | };
15 | #define DECL_META(meta_name, meta_storage_t, super_meta_names...) template <class T> \
16 | struct meta_name : public meta_traits<T, meta_storage_t, meta_name, ##super_meta_names>
17 | // DECL_MEAT(MetaName, MetaType, OtherMetaName...)
18 | // MetaName<auto_type>[getters, setters] -> meta_traits[meta_info, meta_storage_t] -> auto_type    
19 | // `data_meta_name` is essentially a T.
20 | // Between `data_meta_name` and T, there a meta_traits 
21 | // for describe: 
22 | // 1. Other data_meta_names which it depends.
23 | // 2. Type of this data_meta 
24 | }


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/test/test_node.cpp:
--------------------------------------------------------------------------------
 1 | #include <iostream>
 2 | #include <gtest/gtest.h>
 3 | #include <stdio.h>
 4 | #include "gparallel.h"
 5 | using namespace galois::gparallel;
 6 | 
 7 | struct base {};
 8 | 
 9 | DECL_META(A, base) {
10 | };
11 | 
12 | DECL_META(B, base, A) {
13 | };
14 | 
15 | DECL_META(C, base, B) {
16 | };
17 | 
18 | DECL_META(D, base, A, B, C) {
19 | };
20 | 
21 | struct Process
22 | {
23 |     int process(input<A> a, input<B> b, output<C> c, output<D> d)
24 |     {
25 |         return 0;
26 |     };
27 | };
28 | 
29 | #define SHOW(_name) \
30 | printf(#_name"\n");\
31 | for (auto & a : _name) {\
32 |     printf("\tkey:[%d] id:[%d] type:[%d] name:[%s]\n", \
33 |         a.first, a.second.id, a.second.type, \
34 |         typeid_manager<none_type>::instance().name(a.second.id).c_str());\
35 | }\
36 | 
37 | TEST(Test, deduce_depends) {
38 |     using namespace galois::gparallel;
39 |     io_description vec;
40 |     deduce_depends<Process>::deduce(vec);
41 |     SHOW(vec.input);
42 |     SHOW(vec.output);
43 |     ASSERT_EQ(vec.input.size(), 3);
44 |     ASSERT_EQ(vec.output.size(), 2);
45 | }


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/test/test_register_node.cpp:
--------------------------------------------------------------------------------
 1 | #include <iostream>
 2 | #include <gtest/gtest.h>
 3 | #include <stdio.h>
 4 | #include <algorithm>
 5 | #include "gparallel.h"
 6 | using namespace galois::gparallel;
 7 | 
 8 | struct base {};
 9 | DECL_META(MetaB, base) {};
10 | 
11 | DECL_META(MetaC, base) {};
12 | 
13 | DECL_META(MetaA, base, MetaC) {};
14 | 
15 | DECL_META(MetaD, base) {};
16 | 
17 | DECL_META(MetaE, base, MetaD) {};
18 | 
19 | struct NodeA
20 | {
21 |     static int process(input<MetaA> b) { return 0; }
22 | };
23 | 
24 | struct NodeB
25 | {
26 |     static int process(input<MetaA> a, output<MetaB> b) { return 0; }
27 | };
28 | 
29 | struct NodeC
30 | {
31 |     static int process(output<MetaC> c) { return 0; }
32 | };
33 | 
34 | struct NodeD
35 | {
36 |     static int process(input<MetaB> b, input<MetaC> c, output<MetaD> d) { return 0; }
37 | };
38 | 
39 | struct NodeE
40 | {
41 |     static int process(output<MetaE> e) { return 0; }
42 | };
43 | 
44 | TEST(Test, register_node) {
45 |     using namespace galois::gparallel;
46 |     dag_schema<base> nodes;
47 |     register_node<base, NodeA, NodeB, NodeC, NodeD, NodeE>::reg(nodes);
48 |     ASSERT_EQ(setup_dag_schema<base>(nodes), true);
49 | }
50 | 


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/test/test_invoke_ex.cpp:
--------------------------------------------------------------------------------
 1 | #include <iostream>
 2 | #include "invoke_ex.h"
 3 | #include <gtest/gtest.h>
 4 | 
 5 | struct A{int value=1;};
 6 | struct B{int value=2;};
 7 | struct C{int value=3;};
 8 | struct D{int value=4;};
 9 | struct E{int value=5;};
10 | 
11 | int fn(A a, B b, C c, D d)
12 | {
13 |     std::cout<<a.value<<b.value<<c.value<<d.value<<std::endl;
14 |     return 1;
15 | }
16 | 
17 | TEST(Test, invoke_ex) {
18 |     //using namespace galois::gparallel;
19 |     //A a;
20 |     //B b;
21 |     //C c;
22 |     //D d;
23 |     //// any order of a,b,c,d is ok
24 |     //ASSERT_EQ(invoke_ex(fn, a, b, c, d), 1);
25 |     //ASSERT_EQ(invoke_ex(fn, d, b, c, a), 1);
26 |     //ASSERT_EQ(invoke_ex(fn, d, c, b, a), 1);
27 |     //ASSERT_EQ(invoke_ex(fn, d, c, b, a), 1);
28 | }
29 | 
30 | struct AA {
31 |     float data;
32 |     AA(float a) : data(a) {}
33 | };
34 | 
35 | struct BB {
36 |     int data;
37 |     BB(int a) : data(a) {}
38 | };
39 | 
40 | struct CC {
41 |     float data;
42 |     CC(float a) : data(a) {}
43 | };
44 | 
45 | struct DD {
46 |     int data;
47 |     DD(int a) : data(a) {}
48 | };
49 | 
50 | int fn2(AA a, BB b, CC c, DD d) {
51 |     std::cout<<a.data<<b.data<<c.data<<d.data<<std::endl;
52 |     return 1;
53 | }
54 | 
55 | TEST(Test, invoke_ex2) {
56 |     using namespace galois::gparallel;
57 |     // any order of a,b,c,d is ok
58 |     //ASSERT_EQ(invoke_ex(fn2, 1, 1.1), 1);
59 | }


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/test/test_data_meta.cpp:
--------------------------------------------------------------------------------
 1 | #include <string>
 2 | #include <iostream>
 3 | #include <cxxabi.h>
 4 | #include <gtest/gtest.h>
 5 | #include "gparallel.h"
 6 | using namespace galois::gparallel;
 7 | struct thread_data {
 8 |     int AAA_storage = 0;
 9 |     int AAB_storage = 0;
10 |     int AAC_storage = 0;
11 | 
12 |     int ABA_storage = 0;
13 |     int ABB_storage = 0;
14 |     int ABC_storage = 0;
15 | 
16 |     int ACA_storage = 0;
17 |     int ACB_storage = 0;
18 |     int ACC_storage = 0;
19 | 
20 |     int AA_storage = 0;
21 |     int AB_storage = 0;
22 |     int AC_storage = 0;
23 | 
24 |     int A_storage = 0;
25 |     thread_data(int a) {}
26 | };
27 | 
28 | DECL_META(m_aaa, thread_data){
29 |     const int & AAA_storage() const { return this->data->AAA_storage;}
30 | };
31 | 
32 | DECL_META(m_aab, thread_data){};
33 | DECL_META(m_aac, thread_data){};
34 | DECL_META(m_aa, thread_data, m_aaa, m_aab, m_aac){};
35 | 
36 | DECL_META(m_aba, thread_data){};
37 | DECL_META(m_abb, thread_data){};
38 | DECL_META(m_abc, thread_data){};
39 | DECL_META(m_ab, thread_data, m_aba, m_abb, m_abc){};
40 | 
41 | DECL_META(m_aca, thread_data){};
42 | DECL_META(m_acb, thread_data){};
43 | DECL_META(m_acc, thread_data){};
44 | DECL_META(m_ac, thread_data, m_aca, m_acb, m_acc){};
45 | 
46 | DECL_META(m_a, thread_data, m_aa, m_ab, m_ac){};
47 | 
48 | TEST(Test, meta_deduce) {
49 |     using namespace galois::gparallel;
50 |     io_description deps;
51 |     input<m_a>::meta_imp_t::deduce<none_type>(deps);
52 |     thread_data td(1);
53 |     input<m_a> input_a(&td);
54 | }


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/include/util.h:
--------------------------------------------------------------------------------
 1 | // solopointer1202@gmail.com
 2 | #pragma once
 3 | #include <map>
 4 | #include <vector>
 5 | #include <string>
 6 | #include <memory>
 7 | #include <typeinfo>
 8 | #include <iostream>
 9 | #include <cxxabi.h>
10 | #include "type_id.h"
11 | 
12 | namespace galois::gparallel {
13 | 
14 | struct none_type {};
15 | struct auto_type {};
16 | 
17 | 
18 | std::string demangle(const char* name);
19 | 
20 | enum class parameter_type {
21 |     NONE = 0, INPUT, OUTPUT
22 | };
23 | 
24 | enum class meta_level_t {
25 |     NONE = 0, ITEM, QUERY
26 | };
27 | 
28 | struct io_item {
29 |     int id;
30 |     meta_level_t meta_level;
31 |     parameter_type type;
32 | };
33 | 
34 | typedef std::map<int, io_item> node_io_map;
35 | typedef std::vector<io_item> node_io_vec;
36 | struct io_description {
37 |     node_io_map input;
38 |     node_io_map output;
39 | };
40 | template <class D, template <class> class... MS> struct meta_info_t {};
41 | template <template <class> class... TMPS> struct template_list {};
42 | template <class... TS> struct type_list {};
43 | 
44 | template <class T>
45 | std::string type(const T& t) {
46 |     return demangle(typeid(t).name());
47 | }
48 | 
49 | template <class T>
50 | class storage_reference {
51 | public:
52 |     typedef T data_type;
53 |     void reset(T * data) {
54 |         _data = data;
55 |     }
56 |     template <class P>
57 |     static void deduce(io_description&) {/*End of deduce recurs, do nothing.*/}
58 |     const T * data() const {
59 |         return _data;
60 |     }
61 |     T * mutable_data() {
62 |         return _data;
63 |     }
64 | private:
65 |     T * _data;
66 | };
67 | 
68 | 
69 | }


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/.travis.yml:
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 1 | sudo: required
 2 | dist: xenial
 3 | language: cpp
 4 | matrix:
 5 |   include:
 6 |     
 7 |     # Linux g++-7
 8 |     - os: linux
 9 |       compiler: g++
10 |       addons:
11 |         apt:
12 |           update: true
13 |           sources:
14 |             - sourceline: 'ppa:mhier/libboost-latest'
15 |             - ubuntu-toolchain-r-test
16 |           packages:
17 |             - g++-7
18 |             - boost1.67
19 |       env:
20 |         - MATRIX_EVAL="CC=gcc-7 && CXX=g++-7"
21 |     
22 |     # Linux g++-8
23 |     - os: linux
24 |       compiler: g++
25 |       addons:
26 |         apt:
27 |           update: true
28 |           sources:
29 |             - sourceline: 'ppa:mhier/libboost-latest'
30 |             - ubuntu-toolchain-r-test
31 |           packages:
32 |             - g++-8
33 |             - boost1.67
34 |       env:
35 |         - MATRIX_EVAL="CC=gcc-8 && CXX=g++-8"
36 | 
37 |     # Linux g++-9
38 |     - os: linux
39 |       compiler: g++
40 |       addons:
41 |         apt:
42 |           update: true
43 |           sources:
44 |             - sourceline: 'ppa:mhier/libboost-latest'
45 |             - ubuntu-toolchain-r-test
46 |           packages:
47 |             - g++-9
48 |             - boost1.67
49 |       env:
50 |         - MATRIX_EVAL="CC=gcc-9 CXX=g++-9"
51 | 
52 | # install cmake 3.10
53 | before_install:
54 |   - eval "${MATRIX_EVAL}"
55 |   - wget -O cmake.sh https://cmake.org/files/v3.10/cmake-3.10.0-rc1-Linux-x86_64.sh 
56 |   - sudo sh cmake.sh --skip-license --exclude-subdir --prefix=/usr/local
57 | 
58 | # Build steps
59 | script:
60 |   - mkdir build
61 |   - cd build
62 |   - cmake ../
63 |   - make 


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/include/glist.h:
--------------------------------------------------------------------------------
 1 | // solopointer1202@gmail.com
 2 | #pragma once
 3 | #include <type_traits>
 4 | 
 5 | namespace galois::gparallel
 6 | {
 7 | 
 8 | template <class... TT>
 9 | struct grow {};
10 | 
11 | template <class T>
12 | struct grow<T> : public T {
13 | };
14 | 
15 | template <class T, class... TT>
16 | struct grow<T, TT...> : public grow<TT...> {
17 |     operator T() {
18 |         return T(this->data());
19 |     }
20 | };
21 | 
22 | template <class... columns>
23 | class glist{};
24 | 
25 | template <class first_column, class... rest_columns>
26 | class glist<first_column, rest_columns...> {
27 | public:
28 |     typedef typename first_column::data_type data_type;
29 |     class _data_container {
30 |     public:
31 |         auto data() {
32 |             return _data;
33 |         }
34 |     //private:
35 |         data_type * _data;
36 |     };
37 | 
38 |     class iterator : public grow<first_column, rest_columns..., _data_container> {
39 |     public:
40 |         iterator(data_type * item) {
41 |             this->_data = item;
42 |         }
43 | 
44 |         bool operator!=(const iterator & other) {
45 |             return this->_data != other._data;
46 |         }
47 | 
48 |         iterator & operator++() {
49 |             this->_data += 1;
50 |             return *this;
51 |         }
52 | 
53 |         iterator & operator*() {
54 |             return *this;
55 |         }
56 |     };
57 | 
58 |     iterator begin() {
59 |         return iterator(_items);
60 |     }
61 | 
62 |     iterator end() {
63 |         return iterator(_items + _count);
64 |     }
65 | 
66 |     glist(data_type * items, int count) : _items(items), _count(count) {}
67 | 
68 | private:
69 |     data_type * _items;
70 |     int _count;
71 | };
72 | 
73 | }
74 | 


--------------------------------------------------------------------------------
/src/debug.cpp:
--------------------------------------------------------------------------------
 1 | // solopointer1202@gmail.com
 2 | #include <algorithm>
 3 | #include <iostream>
 4 | #include <map>
 5 | #include <set>
 6 | #include <sstream>
 7 | #include <regex>
 8 | #include "dag_schema.h"
 9 | #include "type_id.h"
10 | #include "util.h"
11 | #include "log.h"
12 | 
13 | 
14 | namespace galois::gparallel {
15 | void show_meta_depends_graphviz(topology_t & meta_transitive_closure, std::string tag) {
16 |     std::stringstream meta_depends_log;
17 |     meta_depends_log<<"\ndigraph "<<tag<<"{\n";
18 |     meta_depends_log<<"rankdir=BT;\n";
19 |     meta_depends_log<<"size=\"8,5\";\n";
20 |     for (auto & p : meta_transitive_closure) {
21 |         std::cout<<typeid_manager<none_type>::instance().name(p.first)<<std::endl;;
22 |         for (auto id : p.second) {
23 |                 meta_depends_log<<"\""<<typeid_manager<none_type>::instance().name(p.first)
24 |                 <<"\" -> \""<<typeid_manager<none_type>::instance().name(id)<<"\""<<";"<<std::endl;
25 |         }
26 |     }
27 |     meta_depends_log<<"}";
28 |     auto log_str = meta_depends_log.str();
29 |     std::regex re("galois::gparallel::none_type, |galois::gparallel::meta_info_t");
30 |     INFO("%s\nhttp://graphviz.it/#", tag.c_str());
31 |     INFO("%s", std::regex_replace(log_str, re, "").c_str());
32 | 
33 | }
34 | 
35 | bool graphviz(topology_t& target, std::stringstream & ss, std::string tag) {
36 |     ss<<"digraph "<<tag<<"{"<<std::endl;
37 |     ss<<"rankdir=BT;"<<std::endl;
38 |     ss<<"size=\"8,5\";"<<std::endl;
39 |     for (auto& [output, input_set] : target) {
40 |         for (auto input : input_set) {
41 |                 ss<<"\""<<output<<"\" -> \""<<input<<"\""<<";"<<std::endl;
42 |         }
43 |     }
44 |     ss<<"}";
45 |     return true;
46 | }
47 | }


--------------------------------------------------------------------------------
/CMakeLists.txt:
--------------------------------------------------------------------------------
 1 | PROJECT(gparallel)
 2 | CMAKE_MINIMUM_REQUIRED(VERSION 2.8)
 3 | SET(CMAKE_C_FLAGS "${CMAKE_C_FLAGS} -g")
 4 | SET(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -g")
 5 | SET(CMAKE_CXX_FLAGS_DEBUG "$ENV{CXXFLAGS} -O0 -Wall -g -ggdb -std=c++2a -fno-strict-aliasing -Wno-register -Wno-pessimizing-move")
 6 | SET(CMAKE_CXX_FLAGS_RELEASE "$ENV{CXXFLAGS} -O3 -Wall -std=c++2a -fno-strict-aliasing -Wno-register -Wno-pessimizing-move")
 7 | SET(CMAKE_BUILD_TYPE "Release")
 8 | 
 9 | # boost
10 | FIND_PACKAGE(Boost REQUIRED COMPONENTS log)
11 | IF(NOT Boost_FOUND)
12 |     MESSAGE("Can not find Boost")
13 | ENDIF()
14 | 
15 | ADD_DEFINITIONS(-DBOOST_SPIRIT_THREADSAFE)
16 | ADD_DEFINITIONS(-DBOOST_ALL_DYN_LINK)
17 | ADD_DEFINITIONS(-D_DEBUG)
18 | 
19 | INCLUDE_DIRECTORIES(${Boost_INCLUDE_DIRS})
20 | LINK_DIRECTORIES(${Boost_LIBRARY_DIRS})
21 | 
22 | # gtest
23 | IF (NOT TARGET gtest)
24 |     ADD_SUBDIRECTORY(gtest)
25 |     ENABLE_TESTING()
26 |     INCLUDE_DIRECTORIES(SYSTEM
27 |         ${gtest_SOURCE_DIR}
28 |         ${gtest_SOURCE_DIR}/include)
29 | ENDIF()
30 | 
31 | # common
32 | IF (NOT TARGET common)
33 |     ADD_SUBDIRECTORY(common)
34 | ENDIF()
35 | 
36 | INCLUDE_DIRECTORIES("${PROJECT_SOURCE_DIR}/include")
37 | INCLUDE_DIRECTORIES("${PROJECT_SOURCE_DIR}/src")
38 | INCLUDE_DIRECTORIES("${CMAKE_SOURCE_DIR}/common/util/include")
39 | 
40 | # libgparallel.a
41 | file(GLOB gparallel_srcs "${PROJECT_SOURCE_DIR}/src/*.cpp")
42 | ADD_LIBRARY(gparallel STATIC ${gparallel_srcs})
43 | 
44 | # gparallel_test
45 | file(GLOB test_srcs "${PROJECT_SOURCE_DIR}/test/*.cpp")
46 | ADD_EXECUTABLE(test ${test_srcs})
47 | TARGET_LINK_LIBRARIES(test gtest common gparallel)
48 | 
49 | # demo
50 | file(GLOB demo_srcs "${PROJECT_SOURCE_DIR}/demo/*.cpp")
51 | ADD_EXECUTABLE(demo ${demo_srcs})
52 | TARGET_LINK_LIBRARIES(demo gtest common gparallel)
53 | 


--------------------------------------------------------------------------------
/include/node_deduce.h:
--------------------------------------------------------------------------------
 1 | // solopointer1202@gmail.com
 2 | #pragma once
 3 | #include <type_traits>
 4 | #include <map>
 5 | #include <vector>
 6 | #include <string>
 7 | #include <memory>
 8 | #include <iostream>
 9 | #include "util.h"
10 | #include "meta_decorator.h"
11 | 
12 | namespace galois::gparallel
13 | {
14 | // NT: node type
15 | // R: return type
16 | // A: arg type
17 | // AS: args type
18 | // 1. simple deduce_arg detail
19 | template <class A, class NT>
20 | struct deduce_op {
21 |     static void deduce(io_description & iodes) {
22 |         record_input_output<A, NT>(iodes);
23 |         depth_first_search_of_meta<typename parameter_traits<A>::meta_info>::template deduce<NT>(iodes);
24 |     }
25 | };
26 | 
27 | // 2.last deduce_arg in the recursion 
28 | template <class NT, class...AS>
29 | struct deduce_arg {
30 |     static void deduce(io_description &) {
31 |         // do nothing
32 |         // the stop template in the recursion
33 |     }
34 | };
35 | 
36 | template <class NT, class A, class...AS>
37 | struct deduce_arg<NT, A, AS...> {
38 |     static void deduce(io_description & iodes) {
39 |         deduce_op<A, NT>::deduce(iodes);
40 |         deduce_arg<NT, AS...>::deduce(iodes);
41 |     }
42 | };
43 | 
44 | // depends deduce
45 | // default template
46 | template <class...AS>
47 | struct deduce_fn {};
48 | // for normal function
49 | template <class NT, class R, class...AS>
50 | struct deduce_fn<NT, R(*)(AS...)> : 
51 |     public deduce_arg<NT, AS...> {};
52 | // for nember function
53 | template <class NT, class R, class...AS>
54 | struct deduce_fn<NT, R(NT::*)(AS...)> : 
55 |     public deduce_arg<NT, AS...> {};
56 | 
57 | // start from here
58 | template <class NT>
59 | struct deduce_depends {
60 |     static void deduce(io_description & vec) {
61 |         deduce_fn<NT, decltype(&NT::process)>::deduce(vec);
62 |     }
63 | };
64 | 
65 | };


--------------------------------------------------------------------------------
/include/type_id.h:
--------------------------------------------------------------------------------
 1 | // solopointer1202@gmail.com
 2 | #pragma once
 3 | #include <map>
 4 | #include <set>
 5 | #include <vector>
 6 | #include <string>
 7 | #include <memory>
 8 | 
 9 | namespace galois::gparallel
10 | {
11 | typedef int id_t;
12 | typedef std::set<id_t> id_set_t;
13 | typedef std::map<id_t, id_set_t> topology_t;
14 | std::string demangle(const char* name);
15 | 
16 | // For every tag, the id is global unique
17 | template <class tag>
18 | class typeid_manager {
19 | public:
20 |     static auto & instance() {
21 |         static typeid_manager<tag> singleton;
22 |         return singleton;
23 |     }
24 |     template <class type>
25 |     int typeid_register() {
26 |         _id2name[_typeid] = demangle(typeid(type).name());
27 |         return _typeid++;
28 |     }
29 |     const std::string & name(int id) const {
30 |         auto pos = _id2name.find(id);
31 |         if (pos != _id2name.cend())
32 |             return pos->second;
33 |         static std::string error_id("ErrorId");
34 |         return error_id;
35 |     }
36 |     auto begin() {
37 |         return _id2name.begin();
38 |     }
39 |     auto end() {
40 |         return _id2name.end();
41 |     }
42 | private:
43 |     typeid_manager() : _typeid(0) {}
44 |     std::map<int, std::string> _id2name;
45 |     int _typeid;
46 | };
47 | 
48 | // for every <T, tag>, assign a class type_id<T, tag> to keep an id. 
49 | template <class type, class tag>
50 | class type_id{
51 | public:
52 |     type_id() {
53 |         _id = typeid_manager<tag>::instance().template typeid_register<type>();
54 |     }
55 |     static type_id<type, tag> & instance() {
56 |         static type_id<type, tag> singleton;
57 |         return singleton;
58 |     }
59 |     uint32_t id() const {
60 |         return _id;
61 |     }
62 |     const std::string & name() const {
63 |         return typeid_manager<tag>::instance().name(_id);
64 |     }
65 | private:
66 |     uint32_t _id;
67 | };
68 | }


--------------------------------------------------------------------------------
/src/dag_schema.cpp:
--------------------------------------------------------------------------------
 1 | 
 2 | // solopointer1202@gmail.com
 3 | #include <map>
 4 | #include <vector>
 5 | #include <string>
 6 | #include <algorithm>
 7 | #include <memory>
 8 | #include "util.h"
 9 | #include "type_id.h"
10 | 
11 | namespace galois::gparallel {
12 | 
13 | void operator += (id_set_t & i, const id_set_t & other) {
14 |     std::transform(other.cbegin(), other.cend(),std::inserter(i, i.end()), 
15 |         [](auto o){return o;});
16 | }
17 | 
18 | bool operator -= (id_set_t & i, const id_set_t & other) {
19 |     id_set_t diff; 
20 |     if (i.size() < other.size()) {
21 |         for (auto id : i) {
22 |             if (other.find(id) != other.end()) {
23 |                 diff.insert(id);
24 |             }
25 |         }
26 |     } else {
27 |         for (auto id : other) {
28 |             if (i.find(id) != i.end()) {
29 |                 diff.insert(id);
30 |             }
31 |         }
32 |     }
33 |     for (auto id : diff) {
34 |         i.erase(id);
35 |     }
36 |     return diff.size() != 0;
37 | }
38 | 
39 | void operator += (id_set_t & i, const node_io_vec & other) {
40 | 
41 |     std::transform(other.cbegin(), other.cend(),std::inserter(i, i.end()), 
42 |         [](auto o){return o.id;});
43 | }
44 | 
45 | void operator += (node_io_vec & i, const node_io_vec & other) {
46 |     i.insert(i.end(), other.begin(), other.end());
47 | }
48 | 
49 | node_io_vec operator + (node_io_vec & a, const node_io_vec & b) {
50 |     node_io_vec res;
51 |     res += a;
52 |     res += b;
53 |     return std::move(res);
54 | }
55 | bool transitive_closure(topology_t& implies) {
56 |     bool has_change = true;
57 |     while (has_change) {
58 |         has_change = false;
59 |         // for every output
60 |         for (auto & [output, input_set] : implies) {
61 |             id_set_t sub;
62 |             // See every input<> as output<> of other nodes,
63 |             // and we find the input<> or 'other nodes',
64 |             // these input<> were also 
65 |             for (auto input_id : input_set) {
66 |                 sub += implies[input_id];
67 |             }
68 |             size_t prev_size = input_set.size();
69 |             input_set += sub;
70 |             if (input_set.size() > prev_size) {
71 |                 has_change = true;
72 |             }
73 |         }
74 |     }
75 |     return true;
76 | }
77 | }


--------------------------------------------------------------------------------
/include/invoke_ex.h:
--------------------------------------------------------------------------------
  1 | // solopointer1202@gmail.com
  2 | #pragma once
  3 | #include <type_traits>
  4 | #include "util.h"
  5 | /***************************************************************************
  6 | *  An extended version of std::invoke, support pass parameters in any order.
  7 | *  solopointer1202@gmail.com
  8 | *  2019.11.09 14:55:41
  9 | ****************************************************************************/
 10 | // R: Type of return value
 11 | // F: Type of function
 12 | // T: Type
 13 | // I: One int 
 14 | // IS: Multiple int
 15 | // A: One argument's type
 16 | // AS: Type of multiple arguments
 17 | // CS: Type of multiple value candidates
 18 | // MS: Type of matched types
 19 | 
 20 | namespace galois::gparallel {
 21 | 
 22 | //template <class... type> struct type_list {};
 23 | template <class T, int I, class... AS>
 24 | struct find_index {
 25 |     typedef char type[I];
 26 | };
 27 | template <class T, int I, class A, class... AS>
 28 | struct find_index<T, I, A, AS...> {
 29 |     typedef char VT[I];
 30 |     static VT& test(T);
 31 |     static typename find_index<T, I + 1, AS...>::type& test(...);
 32 |     typedef decltype(test(A())) type;
 33 |     static const int index = sizeof(type);
 34 | };
 35 | 
 36 | template <int I, class T, class... TS>
 37 | struct n_th {
 38 |     typedef typename n_th<I - 1, TS...>::type type;
 39 | 
 40 |     static type value(T, TS ... ts) {
 41 |         return n_th<I - 1, TS...>::value(ts...);
 42 |     }
 43 | };
 44 | 
 45 | template <class T, class... TS>
 46 | struct n_th<0, T, TS...> {
 47 |     typedef T type;
 48 |     static type value(T t, ...) {
 49 |         return t;
 50 |     }
 51 | };
 52 | 
 53 | 
 54 | // followings handle parameter
 55 | 
 56 | template <class R, class F, class CS, class MS, int... IS>
 57 | struct parameter_match_invoke {};
 58 | 
 59 | template <class R, class F, class... CS, class... MS, int I, int... IS>
 60 | struct parameter_match_invoke<R, F, type_list<CS...>, type_list<MS...>, I, IS...> {
 61 |     typedef typename n_th<I, CS...>::type Match;
 62 |     static R process(F fn, CS... cs, MS ... ms) {
 63 |         return parameter_match_invoke<R, F, type_list<CS...>, type_list<MS..., Match>, IS...>::process(fn, 
 64 |             cs..., ms..., n_th<I, CS...>::value(cs...));
 65 |     }
 66 | };
 67 | 
 68 | template <class R, class... CS, class... MS, class... AS>
 69 | struct parameter_match_invoke<R, R(*)(AS...), type_list<CS...>, type_list<MS...>> {
 70 |     static R process(R(*fn)(AS...), CS ... , MS ... ms) {
 71 |         return fn(ms...);
 72 |     }
 73 | };
 74 | 
 75 | // parameter_match
 76 | template <class R, class F, class AS, class CS, int... IS>
 77 | struct parameter_match {};
 78 | 
 79 | template <class R, class F, class A, class... AS, class... CS, int... IS>
 80 | struct parameter_match<R, F, type_list<A, AS...>, type_list<CS...>, IS...> {
 81 |     static const int index = find_index<A, 0, CS...>::index;
 82 |     static_assert(index != sizeof...(CS), "not match!");
 83 |     static R process(F fn, CS... cs) {
 84 |         return parameter_match<R, F, type_list<AS...>, type_list<CS...>, IS..., index>::process(fn, cs...);
 85 |     }
 86 | };
 87 | 
 88 | template <class R, class F, class... CS, int... IS>
 89 | struct parameter_match<R, F, type_list<>, type_list<CS...>, IS...> {
 90 |     static R process(F fn, CS... cs) {
 91 |         return parameter_match_invoke<R, F, type_list<CS...>, type_list<>, IS...>::process(fn, cs...);
 92 |     }
 93 | };
 94 | 
 95 | // invoke_ex
 96 | template <class R, class... AS, class... CS>
 97 | R invoke_ex(R(*fn)(AS...), CS... cs) {
 98 |     return parameter_match<R, R(*)(AS...), type_list<AS...>, type_list<CS...>>::process(fn, cs...);
 99 | };
100 | 
101 | }
102 | 


--------------------------------------------------------------------------------
/include/node_schema.h:
--------------------------------------------------------------------------------
  1 | // solopointer1202@gmail.com
  2 | #pragma once
  3 | #include <memory>
  4 | #include <sstream>
  5 | #include "executor.h"
  6 | #include "util.h"
  7 | namespace galois::gparallel {
  8 | 
  9 | inline void data_link_map_to_vec(const node_io_map & map, node_io_vec & vec) {
 10 |     for (auto && it : map) {
 11 |         vec.push_back(it.second);
 12 |     }
 13 | }
 14 | void operator += (node_io_vec & i, const node_io_vec & other);
 15 | node_io_vec operator + (node_io_vec & a, const node_io_vec & b);
 16 | typedef int id_t;
 17 | class node;
 18 | template<class meta_storage_t>
 19 | class node_schema;
 20 | template<class meta_storage_t>
 21 | using node_schema_ptr = std::shared_ptr<node_schema<meta_storage_t>>;
 22 | template<class meta_storage_t>
 23 | using node_schema_cptr = std::shared_ptr<const node_schema<meta_storage_t>>;
 24 | 
 25 | // This class holds all the information of a physical node, 
 26 | // including node name, node ID, upstream nodes, downstream nodes, 
 27 | // input and output metas.
 28 | 
 29 | template<class meta_storage_t>
 30 | class node_schema {
 31 | public:
 32 |     using node_schema_ptr_t = node_schema_ptr<meta_storage_t>;
 33 |     using executor_t = executable_t<meta_storage_t>;
 34 |     node_schema() {
 35 |         static int g_node_id = 0;
 36 |         _node_id = g_node_id++;
 37 |         _executor = nullptr;
 38 |         _deps_count = 0;
 39 |     }
 40 | 
 41 |     void initialize(std::string name, executor_t query_fn, const io_description & io) {
 42 |         _name = name;
 43 |         _executor = query_fn;
 44 | 
 45 |         auto fill_meta = [](const node_io_map & s, node_io_vec & d) {
 46 |             d.reserve(s.size());
 47 |             for (auto & node : s) {
 48 |                 d.push_back(node.second);
 49 |             }
 50 |         };
 51 |         fill_meta(io.input, _input_metas);
 52 |         fill_meta(io.output, _output_metas);
 53 |     }
 54 | 
 55 | public: 
 56 |     bool delete_input_nodes(node_schema_ptr_t node) {
 57 |         return mutable_input_nodes().erase(node) > 0;
 58 |     }
 59 | 
 60 | public:
 61 |     // getter
 62 |     executor_t& mutable_executor() {
 63 |         return _executor;
 64 |     }
 65 | 
 66 |     node_io_vec& mutable_input_metas() {
 67 |         return _input_metas;
 68 | 
 69 |     }
 70 | 
 71 |     node_io_vec& mutable_output_metas() {
 72 |         return _output_metas;
 73 | 
 74 |     }
 75 |     const std::set<node_schema_ptr_t> & input_nodes() const {
 76 |         return _input_nodes;
 77 |     }
 78 | 
 79 |     std::set<node_schema_ptr_t> & mutable_input_nodes() {
 80 |         return _input_nodes;
 81 |     }
 82 | 
 83 |     const std::set<node_schema_ptr_t> & output_nodes() const {
 84 |         return _output_nodes;
 85 |     }
 86 | 
 87 |     std::set<node_schema_ptr_t> & mutable_output_nodes() {
 88 |         return _output_nodes;
 89 |     }
 90 | 
 91 |     std::string name() const {
 92 |         return _name;
 93 |     }
 94 | 
 95 |     int deps_count() const {
 96 |         return _deps_count;
 97 |     }
 98 | 
 99 |     int& mutable_deps_count() {
100 |         return _deps_count;
101 |     }
102 | 
103 |     int node_id() const {
104 |         return _node_id;
105 |     }
106 | 
107 |     void describe() const {
108 |     }
109 | 
110 |     void graphviz(std::stringstream& out) const {
111 |         for (auto node : _input_nodes) {
112 |             out<<"\""<<name()<<"\" -> \""<<node->name()<<"\";"<<std::endl;
113 |         }
114 |     }
115 |     executor_t _executor;
116 |     id_t _node_id;
117 |     int _deps_count;
118 |     std::string _name;
119 |     // All input and output metas
120 |     node_io_vec _input_metas;
121 |     node_io_vec _output_metas;
122 |     // gParallel can infer upstream and downstream nodes 
123 |     // through input and output meta which were staraged here
124 |     std::set<node_schema_ptr_t> _input_nodes;
125 |     std::set<node_schema_ptr_t> _output_nodes;
126 | };
127 | }


--------------------------------------------------------------------------------
/demo/advprocess.cpp:
--------------------------------------------------------------------------------
  1 | #include <iostream>
  2 | #include <vector>
  3 | #include <algorithm>
  4 | #include "gparallel.h"
  5 | using namespace galois::gparallel;
  6 | 
  7 | class advertisement {
  8 | public:
  9 |     advertisement(uint64_t _id) : id(_id) {}
 10 |     uint64_t id;
 11 |     double ctr;
 12 |     double cpm;
 13 | };
 14 | 
 15 | using advlist_t = std::vector<advertisement>;
 16 | using ctr_response_t = std::vector<double>;
 17 | using cpm_response_t = std::vector<double>;
 18 | 
 19 | class thread_data {
 20 | public:
 21 |     advlist_t advs_original;
 22 |     advlist_t advs_ctr_ordered;
 23 |     advlist_t advs_cpm_ordered;
 24 |     ctr_response_t ctr_data;
 25 |     cpm_response_t cpm_data;
 26 | };
 27 | 
 28 | DECL_META(original, thread_data) {
 29 |     advlist_t & mutable_advs_original() {
 30 |         return this->mutable_data()->advs_original;
 31 |     }
 32 | };
 33 | 
 34 | DECL_META(ctr, thread_data) {
 35 |     ctr_response_t & mutable_ctr_data() {
 36 |         return this->mutable_data()->ctr_data;
 37 |     }
 38 | };
 39 | 
 40 | DECL_META(cpm, thread_data) {
 41 |     cpm_response_t & mutable_cpm_data() {
 42 |         return this->mutable_data()->cpm_data;
 43 |     }
 44 | };
 45 | 
 46 | DECL_META(original_with_ctr_cpm, thread_data, original) {};
 47 | 
 48 | DECL_META(ctr_ordered_advlist, thread_data) {
 49 |     advlist_t & mutable_advs_ctr_ordered() {
 50 |         return this->mutable_data()->advs_ctr_ordered;
 51 |     }
 52 | };
 53 | 
 54 | DECL_META(cpm_ordered_advlist, thread_data) {
 55 |     advlist_t & mutable_advs_cpm_ordered() {
 56 |         return this->mutable_data()->advs_cpm_ordered;
 57 |     }
 58 | };
 59 | 
 60 | 
 61 | struct get_ctr_node {
 62 |     static void process(input<original> ori, output<ctr> ctr) {
 63 |         INFO("[gparallel] get_ctr_node", "");
 64 |         ctr->mutable_ctr_data().resize(ori->mutable_advs_original().size());
 65 |         for (int pos = 0; pos < ori->mutable_advs_original().size(); pos++) {
 66 |             auto & adv = ori->mutable_advs_original()[pos];
 67 |             ctr->mutable_ctr_data()[pos] = 0.1 * static_cast<double>(adv.id);
 68 |         }
 69 |     }
 70 | };
 71 | 
 72 | struct get_cpm_node {
 73 |     static void process(input<original> ori, output<cpm> cpm) {
 74 |         INFO("[gparallel] get_cpm_node", "");
 75 |         cpm->mutable_cpm_data().resize(ori->mutable_advs_original().size());
 76 |         for (int pos = 0; pos < ori->mutable_advs_original().size(); pos++) {
 77 |             auto & adv = ori->mutable_advs_original()[pos];
 78 |             cpm->mutable_cpm_data()[pos] = 100.2 * static_cast<double>(adv.id);
 79 |         }
 80 | 
 81 |     }
 82 | };
 83 | 
 84 | struct fill_node {
 85 |     static void process(input<ctr> ctr, input<cpm> cpm, input<original> ori, 
 86 |         output<original_with_ctr_cpm> ori_ctr_cpm) {
 87 |         INFO("[gparallel] fill_node", "");
 88 |         for (int pos = 0; pos < ori->mutable_advs_original().size(); pos++) {
 89 |             auto & adv = ori_ctr_cpm->mutable_advs_original()[pos];
 90 |             adv.ctr = ctr->mutable_ctr_data()[pos];
 91 |             adv.cpm = cpm->mutable_cpm_data()[pos];
 92 |             INFO("[gparallel] ori_ctr_cpm adv:[%d] ctr:[%lf] cpm:[%lf]", adv.id, adv.ctr, adv.cpm);
 93 |         }
 94 |     }
 95 | };
 96 | 
 97 | struct gen_ctr_node {
 98 |     static void process(input<original_with_ctr_cpm> ori_ctr_cpm, 
 99 |         output<ctr_ordered_advlist> ctr_ordered) {
100 |         INFO("[gparallel] gen_ctr_node", "");
101 |         ctr_ordered->mutable_advs_ctr_ordered() = ori_ctr_cpm->mutable_advs_original();
102 |         std::sort(ctr_ordered->mutable_advs_ctr_ordered().begin(),
103 |             ctr_ordered->mutable_advs_ctr_ordered().end(), 
104 |             [](const auto& a, const auto& b)->bool{return a.ctr > b.ctr;});
105 | 
106 |     }
107 | };
108 | 
109 | struct gen_cpm_node {
110 |     static void process(input<original_with_ctr_cpm> ori_ctr_cpm, 
111 |         output<cpm_ordered_advlist> cpm_ordered) {
112 |         INFO("[gparallel] gen_cpm_node", "");
113 |         cpm_ordered->mutable_advs_cpm_ordered() = ori_ctr_cpm->mutable_advs_original();
114 |         std::sort(cpm_ordered->mutable_advs_cpm_ordered().begin(),
115 |             cpm_ordered->mutable_advs_cpm_ordered().end(),
116 |             [](const auto& a, const auto& b)->bool{return a.cpm > b.cpm;});
117 |     }
118 | };
119 | 
120 | struct end_node {
121 |     static void process(input<ctr_ordered_advlist> ctr, input<cpm_ordered_advlist> cpm) {
122 |         INFO("[gparallel] end_node", "");
123 |         for (auto& adv : cpm->mutable_advs_cpm_ordered()) {
124 |             INFO("CPM ordered:[%d]", adv.id);
125 |         }
126 |         for (auto& adv : ctr->mutable_advs_ctr_ordered()) {
127 |             INFO("CTR ordered:[%d]", adv.id);
128 |         }
129 |     }
130 | };
131 | 
132 | int main() {
133 |     thread_data td{{advertisement(1), advertisement(2), advertisement(3)}, {},{},{},{}};
134 |     dag_schema<thread_data> nodes;
135 |     register_node<thread_data, get_ctr_node, get_cpm_node>::reg(nodes);
136 |     register_node<thread_data, fill_node>::reg(nodes);
137 |     register_node<thread_data, gen_ctr_node, gen_cpm_node, end_node>::reg(nodes);
138 |     setup_dag_schema<thread_data>(nodes);
139 |     if (auto tasks = topological_sort<thread_data>(nodes); tasks) {
140 |         for (auto task : tasks.value()) {
141 |             INFO("Execute[%s]", task->name().c_str());
142 |             task->mutable_executor()(&td);
143 |         }
144 |     }
145 |     return 0;
146 | }


--------------------------------------------------------------------------------
/include/meta_decorator.h:
--------------------------------------------------------------------------------
  1 | // solopointer1202@gmail.com
  2 | #pragma once
  3 | #include "log.h"
  4 | 
  5 | namespace galois::gparallel {
  6 | 
  7 | std::string demangle(const char* name);
  8 | 
  9 | template <template<class> class M> class input; 
 10 | template <template<class> class M> class output;
 11 | template <class M>
 12 | struct parameter_traits {
 13 | };
 14 | 
 15 | template < template <class> class M>
 16 | struct parameter_traits< input<M> > {
 17 |     typedef type_id<typename M<none_type>::meta_info, none_type> node_meta_id;
 18 |     typedef typename M<none_type>::meta_info meta_info;
 19 |     static const parameter_type ptype = parameter_type::INPUT;
 20 |     static int id() {
 21 |         return node_meta_id::instance().id();
 22 |     }
 23 |     static const char * name() {
 24 |         return node_meta_id::instance().name();
 25 |     }
 26 | };
 27 | 
 28 | template <template <class> class M>
 29 | struct parameter_traits< output<M> > {
 30 |     typedef type_id<typename M<none_type>::meta_info, none_type> node_meta_id;
 31 |     typedef typename M<none_type>::meta_info meta_info;
 32 |     static const parameter_type ptype = parameter_type::OUTPUT;
 33 |     static int id() {
 34 |         return node_meta_id::instance().id();
 35 |     }
 36 |     static const char* name() {
 37 |         return node_meta_id::instance().name();
 38 |     }
 39 | };
 40 | 
 41 | template <class A, class NT>
 42 | void record_input_output(io_description & iodes) {
 43 |     if (parameter_traits<A>::ptype == parameter_type::NONE) {
 44 |         return;
 45 |     }
 46 |     bool is_item = true;
 47 |     io_item link;
 48 |     link.id = parameter_traits<A>::id();
 49 |     link.type = parameter_traits<A>::ptype;
 50 |     link.meta_level = is_item ? meta_level_t::ITEM : meta_level_t::QUERY;
 51 | 
 52 |     if (link.type == parameter_type::INPUT) {
 53 |         iodes.input[link.id] = link;
 54 |     } else {
 55 |         iodes.output[link.id] = link;
 56 |     }
 57 | };
 58 | 
 59 | template <class STACK, class... MS> struct pop_and_process_M {};
 60 | template <class STACK, class... MS> struct push_next_M {};
 61 | 
 62 | 
 63 | // STACK: An abstract stack type, which story some info for Depth-First-Search
 64 | // D: Data type
 65 | // M: Data meta type
 66 | // MS_dep: The data meta types which depends it
 67 | // template_list: a list of any template
 68 | // meta_info_t: a special list for store <D, M, MS_dep ...>
 69 | //
 70 | // deducer<STACK, meta_info_t>
 71 | template <class STACK, class D, template <class> class M, template <class> class... MS_dep>
 72 | struct push_next_M<STACK, meta_info_t<D, M, MS_dep ...>> 
 73 |     : public pop_and_process_M<STACK, template_list<MS_dep...>> {
 74 |     template <class P>
 75 |     static void deduce(io_description & deps) {
 76 | #ifdef _DEBUG
 77 |         DEBUG("%s::deduce[normal]", demangle(typeid(push_next_M<STACK, meta_info_t<D, M, MS_dep ...>>).name()).c_str());
 78 | #endif
 79 |         pop_and_process_M<STACK, template_list<MS_dep...>>::template deduce<P>(deps);
 80 |     }
 81 | };
 82 | 
 83 | // end case
 84 | template <class STACK>
 85 | struct pop_and_process_M<STACK, template_list<>> : public STACK {
 86 |     template <class P>
 87 |     static void deduce(io_description & deps) {
 88 | #ifdef _DEBUG
 89 |         DEBUG("%s::deduce[call stack::deduce]", 
 90 |             demangle(typeid(pop_and_process_M<STACK, template_list<>>).name()).c_str());
 91 | #endif
 92 |         STACK::template deduce<P>(deps);
 93 |     }
 94 | };
 95 | 
 96 | // deducer<STACK, template_list>
 97 | template <class STACK, template <class> class meta_name, template <class> class...super_meta_names>
 98 | struct pop_and_process_M<STACK, template_list<meta_name, super_meta_names...>> 
 99 |     : public meta_name<push_next_M<pop_and_process_M<STACK, template_list<super_meta_names...>>, typename meta_name<none_type>::meta_info>> {
100 |     template <class P>
101 |     static void deduce(io_description & deps) {
102 | #ifdef _DEBUG
103 |         DEBUG("%s::deduce[record_input_output(%s)]", 
104 |             demangle(typeid(pop_and_process_M<STACK, template_list<meta_name, super_meta_names...>>).name()).c_str(),
105 |             demangle(typeid(meta_name<none_type>).name()).c_str()
106 |         );
107 | #endif
108 |         record_input_output<input<meta_name>, P>(deps);
109 |         push_next_M<pop_and_process_M<STACK, template_list<super_meta_names...>>, typename meta_name<none_type>::meta_info>::template deduce<P>(deps);
110 |     }
111 | };
112 | 
113 | // start
114 | template <class T> struct depth_first_search_of_meta {};
115 | template <class meta_storage_t, template <class> class meta_name, template <class> class... super_meta_names>
116 | struct depth_first_search_of_meta< meta_info_t<meta_storage_t, meta_name, super_meta_names...> > 
117 |     : public meta_name<pop_and_process_M<storage_reference<meta_storage_t>, template_list<super_meta_names...>>> {
118 |     depth_first_search_of_meta(meta_storage_t* data) {
119 |         this->reset(data); 
120 |     }
121 |     template <class P>
122 |     static void deduce(io_description & deps) {
123 | #ifdef _DEBUG
124 |         DEBUG("%s::deduce[start]", demangle(typeid(depth_first_search_of_meta< meta_info_t<meta_storage_t, meta_name, super_meta_names...>>).name()).c_str());
125 | #endif
126 |         pop_and_process_M<storage_reference<meta_storage_t>, template_list<super_meta_names...>>::template deduce<P>(deps);
127 |     };
128 | };
129 | 
130 | template <template<class> class M>
131 | class input {
132 | public:
133 |     typedef typename M<none_type>::meta_info meta_info;
134 |     typedef typename M<none_type>::meta_storage_t meta_storage_t;
135 |     typedef depth_first_search_of_meta<meta_info> meta_imp_t;
136 |     input(meta_storage_t* data) : _m(data) {}
137 |     meta_imp_t* operator-> () {
138 |         return &_m;
139 |     }
140 | private:
141 |     meta_imp_t _m;
142 | };
143 | 
144 | template <template<class> class M>
145 | class output {
146 | public:
147 |     typedef typename M<none_type>::meta_info meta_info;
148 |     typedef typename M<none_type>::meta_storage_t meta_storage_t;
149 |     typedef depth_first_search_of_meta<meta_info> meta_imp_t;
150 |     output(meta_storage_t* data) : _m(data) {}
151 |     meta_imp_t* operator->() {
152 |         return &_m;
153 |     }
154 | private:
155 |     meta_imp_t _m;
156 | };
157 | 
158 | }


--------------------------------------------------------------------------------
/include/dag_schema.h:
--------------------------------------------------------------------------------
  1 | // solopointer1202@gmail.com
  2 | #pragma once
  3 | #include <string>
  4 | #include <vector>
  5 | #include <list>
  6 | #include <memory>
  7 | #include <algorithm>
  8 | #include <optional>
  9 | #include <regex> 
 10 | #include "node_deduce.h"
 11 | #include "node_schema.h"
 12 | #include "util.h"
 13 | #include "executor.h"
 14 | #include "type_id.h"
 15 | 
 16 | namespace galois::gparallel {
 17 | 
 18 | void operator += (id_set_t & i, const id_set_t & other);
 19 | bool operator -= (id_set_t & i, const id_set_t & other);
 20 | void operator += (id_set_t & i, const node_io_vec & other);
 21 | bool transitive_closure(topology_t& implies);
 22 | 
 23 | template<class meta_storage_t>
 24 | using dag_schema = std::list<node_schema_ptr<meta_storage_t>>;
 25 | 
 26 | template<class meta_storage_t>
 27 | using meta_to_nodevec_t = std::map< id_t, std::vector<node_schema_ptr<meta_storage_t>> >;
 28 | 
 29 | template<class meta_storage_t>
 30 | using meta_to_node_t = std::map< id_t, node_schema_ptr<meta_storage_t>>;
 31 | 
 32 | template<class meta_storage_t>
 33 | std::optional<dag_schema<meta_storage_t>> topological_sort(const dag_schema<meta_storage_t>& const_dag) {
 34 |     auto dag = const_dag;
 35 |     dag_schema<meta_storage_t> result;
 36 |     while(!dag.empty()) {
 37 |         auto res = std::find_if(dag.begin(), dag.end(), [](auto node)->bool{
 38 |             return node->mutable_input_nodes().size() == 0;
 39 |         });
 40 |         if (res != dag.end()) {
 41 |             TRACE("Found 0-input node[%s]", (*res)->name().c_str());
 42 |             result.push_back(*res);
 43 |             auto del = *res;
 44 |             dag.erase(res);
 45 |             std::for_each(dag.begin(), dag.end(), [del](auto node){
 46 |                 auto res = node->delete_input_nodes(del);
 47 |                 TRACE("Delete input [%s] for [%s] : [%s]", 
 48 |                     del->name().c_str(), node->name().c_str(),
 49 |                     res ? "true" : "false");
 50 |             });
 51 |         } else {
 52 |             return std::nullopt;
 53 |         }
 54 |     }
 55 |     return result;
 56 | }
 57 | 
 58 | template <class NT, class meta_storage_t>
 59 | void register_node_operator(dag_schema<meta_storage_t> & c) {
 60 |     std::string name = demangle(typeid(NT).name());
 61 |     auto new_node = std::make_shared<node_schema<meta_storage_t>>();
 62 |     c.push_back(new_node);
 63 |     io_description vec;
 64 |     deduce_depends<NT>::deduce(vec);
 65 |     c.back()->initialize(name, executor<meta_storage_t, decltype(NT::process)>::create(NT::process), vec);
 66 | }
 67 | 
 68 | // register_node
 69 | template <class meta_storage_t, class ...NTS>
 70 | struct register_node {
 71 |     static void reg(dag_schema<meta_storage_t>& c) {
 72 |         register_node<meta_storage_t, type_list<NTS ...>>::reg(c);
 73 |     };
 74 | };
 75 | 
 76 | template <class meta_storage_t, class NT, class ...NTS>
 77 | struct register_node<meta_storage_t, type_list<NT, NTS...>> {
 78 |     static void reg(dag_schema<meta_storage_t>& c) {
 79 |         register_node_operator<NT>(c);
 80 |         register_node<meta_storage_t, NTS...>::reg(c);
 81 |     };
 82 | };
 83 | 
 84 | template <class meta_storage_t>
 85 | struct register_node<meta_storage_t, type_list<>> {
 86 |     static void reg(dag_schema<meta_storage_t>& ) { /* stop recursion , do nothing*/}
 87 | };
 88 | 
 89 | template<class meta_storage_t>
 90 | bool build_meta_topology(const dag_schema<meta_storage_t> & _nodes, topology_t & me) {
 91 |     for (auto node : _nodes) {
 92 |         for (auto out : node->_output_metas) {
 93 |             std::transform(node->_input_metas.begin(), node->_input_metas.end(),
 94 |                 std::inserter(me[out.id], me[out.id].end()),
 95 |                 [](auto & node){ return node.id; });
 96 |         }
 97 |     }
 98 |     return true;
 99 | }
100 | 
101 | template<class meta_storage_t>
102 | bool build_node_topology(const dag_schema<meta_storage_t> & _nodes, topology_t & me) {
103 |     for (auto node : _nodes) {
104 |         for (const auto & node_out : node->_output_nodes) {
105 |             me[node_out->node_id()].insert(node->node_id());
106 |         }
107 |     }
108 |     return true;
109 | }
110 | 
111 | void show_meta_depends_graphviz(topology_t & meta_transitive_closure, std::string tag);
112 | 
113 | bool graphviz(topology_t & target, std::stringstream & ss, std::string tag);
114 | 
115 | template<class meta_storage_t>
116 | void show_node_depends_graphviz(const dag_schema<meta_storage_t>& _nodes, std::string tag) {
117 |     std::stringstream node_depends_log;
118 |     node_depends_log<<"\ndigraph "<<tag<<"{\n";
119 |     node_depends_log<<"rankdir=BT;\n";
120 |     node_depends_log<<"size=\"8,5\";\n";
121 |     for (auto node : _nodes) {
122 |         node->graphviz(node_depends_log);
123 |     }
124 |     node_depends_log<<"}";
125 |     auto log_str = node_depends_log.str();
126 |     std::regex re("galois::gparallel::none_type, |galois::gparallel::meta_info_t");
127 |     INFO("%s\nhttp://graphviz.it/#", tag.c_str());
128 |     INFO("%s", std::regex_replace(log_str, re, "").c_str());
129 | }
130 | 
131 | template<class meta_storage_t>
132 | bool setup_dag_schema(dag_schema<meta_storage_t> & _nodes) {
133 |     if (auto pos = std::find_if(_nodes.begin(), _nodes.end(), [](auto ptr){
134 |         size_t query_meta_cnt = 0;
135 |         size_t item_meta_cnt = 0;
136 |         for (auto & output : ptr->_output_metas) {
137 |             if (output.meta_level == meta_level_t::ITEM) {
138 |                 item_meta_cnt ++;
139 |             } else if (output.meta_level == meta_level_t::QUERY) {
140 |                 query_meta_cnt ++;
141 |             }
142 |         }
143 |         return item_meta_cnt > 0 && query_meta_cnt > 0;
144 |     }); pos != _nodes.end()) {
145 |         FATAL("can not process both query and item:%s", (*pos)->name().c_str());
146 |         return false;
147 |     }
148 |     meta_to_node_t<meta_storage_t> output2node;
149 |     for (auto node : _nodes) {
150 |         for (auto & meta: node->_output_metas) {
151 |             // for each output meta of each node
152 |             switch (meta.type) {
153 |             case parameter_type::OUTPUT:
154 |                 if (output2node.count(meta.id) != 0) {
155 |                     FATAL("%s output fail: node[%s] already output meta[%s]",
156 |                         node->name().c_str(), output2node[meta.id]->name().c_str(), 
157 |                         typeid_manager<none_type>::instance().name(meta.id).c_str());
158 |                     return false;
159 |                 }
160 |                 output2node[meta.id] = node;
161 |                 break;
162 |             case parameter_type::INPUT:
163 |             case parameter_type::NONE:
164 |             default:
165 |                 FATAL("should not be here", "");
166 |                 break;
167 |             }
168 |         }
169 |     }
170 | 
171 |     topology_t meta_transitive_closure;
172 |     if (build_meta_topology(_nodes, meta_transitive_closure)) {
173 |         if (transitive_closure(meta_transitive_closure)) {
174 |             show_meta_depends_graphviz(meta_transitive_closure, "meta_transitive_closure");
175 |         } else {
176 |             FATAL("transitive_closure(meta_transitive_closure) fail", "");
177 |             return false;
178 |         } 
179 |     }
180 | 
181 |     for (auto node : _nodes) {
182 |         id_set_t metas_direct_deps;
183 |         {
184 |             metas_direct_deps += node->_input_metas;
185 |             bool has_reduced = true;
186 |             while (has_reduced) {
187 |                 has_reduced = false;
188 |                 id_set_t tmp = metas_direct_deps;
189 |                 for (auto id : tmp) {
190 |                     if (metas_direct_deps -= meta_transitive_closure[id]) {
191 |                         has_reduced = true;
192 |                         break;
193 |                     } 
194 |                 }
195 |             }
196 |         }
197 |         auto link_node_by_meta = [&]() {
198 |             for (auto & input_meta : node->_input_metas) {
199 |                 if (metas_direct_deps.find(input_meta.id) == metas_direct_deps.end()) {
200 |                     // Only care about of the metas that direct depends.
201 |                     continue;
202 |                 }
203 | 
204 |                 if (auto upstream_node = output2node[input_meta.id]; 
205 |                     upstream_node != nullptr) {
206 |                     node->mutable_input_nodes().insert(upstream_node);
207 |                     upstream_node->mutable_output_nodes().insert(node);
208 |                     node->mutable_deps_count() += 1;
209 |                 } else {
210 |                     return false;
211 |                 }
212 |             }
213 |             return true;
214 |         };
215 |         link_node_by_meta();
216 |     }
217 |     show_node_depends_graphviz<meta_storage_t>(_nodes, "node_depends");
218 |     topology_t node_implies;
219 |     build_node_topology(_nodes, node_implies);
220 |     if (!transitive_closure(node_implies)) {
221 |         FATAL("node: transitive_closure fail.", "");
222 |         return false;
223 |     }
224 |     for (auto node : _nodes) {
225 |         auto nodes_direct_deps = node_implies[node->node_id()];
226 |         {
227 |             bool has_reduced = true;
228 |             while (has_reduced) {
229 |                 has_reduced = false;
230 |                 auto tmp = nodes_direct_deps;
231 |                 for (const auto& node_in : tmp) {
232 |                     if (nodes_direct_deps -= node_implies[node_in]) {
233 |                         has_reduced = true;
234 |                         break;
235 |                     }
236 |                 }
237 |             }
238 |         }
239 |         for (auto input_node_itr = node->mutable_input_nodes().begin(); 
240 |             input_node_itr != node->mutable_input_nodes().end(); ++input_node_itr) {
241 |             if (nodes_direct_deps.count((*input_node_itr)->node_id())) {
242 |                 continue;
243 |             }
244 |             if ((*input_node_itr)->mutable_output_nodes().erase(node) < 1) {
245 |                 return false;
246 |             }
247 |             node->mutable_input_nodes().erase(input_node_itr);
248 |             (*input_node_itr)->mutable_output_nodes().erase(*input_node_itr);
249 |             node->_deps_count -= 1;
250 |         }
251 |     }
252 |     show_node_depends_graphviz<meta_storage_t>(_nodes, "node_depends_after");
253 |     return true;
254 | }  
255 | 
256 | }
257 | 
258 | 


--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
  1 | # gParallel <img align="right" width="30%" src="./image/logo.png">
  2 | 
  3 | [![Build Status](https://www.travis-ci.org/galois-advertising/gparallel.svg?branch=master)](https://www.travis-ci.org/galois-advertising/gparallel)
  4 | 
  5 | 
  6 | `gparallel`是一个针对具有复杂流程或逻辑的单体式信息检索系统而设计的并行任务调度框架。使用`Meta Programming`技术根据任务的输入和输出自动推导依赖关系，生成`DAG(Directed acyclic graph)`并进行并行任务调度。
  7 | 
  8 | # Quick start
  9 | 
 10 | * 编译依赖
 11 |     - g++8
 12 |     - boost_log-mt v1.70
 13 |     - gtest v1.10.0
 14 | 
 15 | ## 下载编译test和demo
 16 | 
 17 | ```shell
 18 | $ git clone git@github.com:galois-advertising/gparallel.git
 19 | $ cd gparallel
 20 | $ git submodule update --init --recursive
 21 | $ mkdir build
 22 | $ cd build
 23 | $ cmake ..
 24 | $ make
 25 | $ ./test
 26 | $ ./demo
 27 | ```
 28 | 
 29 | ## 将gparallel作为你项目的一部分
 30 | 
 31 | 首先将`gparallel`以及所依赖的`common`和`gtest`设置为`git submodule`。
 32 | 
 33 | ```shell
 34 | cd your-project
 35 | git add submodule -b master https://github.com/galois-advertising/gparallel
 36 | git add submodule -b master https://github.com/galois-advertising/common
 37 | git add submodule https://github.com/google/googletest.git gtest
 38 | cd gtest
 39 | git checkout release-1.10.0
 40 | git add gtest
 41 | git commit -m "Add gparallel"
 42 | ```
 43 | 
 44 | 并且修改`CMakeLists.txt`，加入：
 45 | 
 46 | ```cmake
 47 | INCLUDE_DIRECTORIES("${CMAKE_SOURCE_DIR}/common/util/include")
 48 | INCLUDE_DIRECTORIES("${CMAKE_SOURCE_DIR}/gparallel/include")
 49 | IF (NOT TARGET gtest)
 50 |     ADD_SUBDIRECTORY(gtest)
 51 |     ENABLE_TESTING()
 52 |     INCLUDE_DIRECTORIES(SYSTEM
 53 |         ${gtest_SOURCE_DIR}
 54 |         ${gtest_SOURCE_DIR}/include)
 55 | ENDIF()
 56 | 
 57 | IF (NOT TARGET common)
 58 |     ADD_SUBDIRECTORY(common)
 59 | ENDIF()
 60 | 
 61 | IF (NOT TARGET gparallel)
 62 |     ADD_SUBDIRECTORY(gparallel)
 63 | ENDIF()
 64 | ADD_EXECUTABLE(your-bin ...)
 65 | TARGET_LINK_LIBRARIES(your-bin common gparallel)
 66 | ```
 67 | 
 68 | # 背景介绍
 69 | 
 70 | 对于单体型业务系统，在系统建立初期，系统业务还比较简单，每次`检索请求`到来时需要执行的业务逻辑也比较单一，此时请求级别的`数据变量`比较少，这些变量的赋值顺序与依赖关系也一目了然，系统很容易维护。
 71 | 
 72 | 但是，随着开发的人越来越多，大家都在上面加入自己的`业务逻辑`和新的`数据变量`，此时变量增加到了几百个，变量之间的赋值顺序与依赖关系开始变得复杂，一些代码逻辑甚至打破了已有的流程结构（俗称飞线），整个系统难以理解。没有一个人能说清楚这些变量之间的依赖关系以及这些业务逻辑之间的执行顺序，每次新的开发都如履薄冰，每次排查问题都耗时耗力。
 73 | 
 74 | 对于多人参与，迭代密集的系统，如何更合理地组织各类型的数据，如何更好地实现繁杂的业务逻辑，这就是为需要`gparallel`的理由.
 75 | 
 76 | 
 77 | > `gparallel`是一款基于`DAG(Directed acyclic graph)`的并且支持自动依赖推导的任务调度框架。
 78 | 
 79 | `DAG`在计算机领域有着广泛的应用，例如在大数据计算中可以使用DAG指导Hadoop任务的执行顺序等等。在软件设计中也被广泛应用，开源社区中DAG-based调度框架也有很多，例如[cpp-taskflow](https://github.com/cpp-taskflow/cpp-taskflow)。但是，几乎所有框架都采用了 **手工配置的方式** 生成调度DAG。例如在一个拥有四个任务的调度系统中，`cpp-taskflow`需要通过下面方式来配置DAG。
 80 | 
 81 | ```cpp
 82 |     auto [A, B, C, D] = taskflow.emplace(
 83 |       [] () { std::cout << "TaskA\n"; },
 84 |       [] () { std::cout << "TaskB\n"; },
 85 |       [] () { std::cout << "TaskC\n"; },
 86 |       [] () { std::cout << "TaskD\n"; }
 87 |     );
 88 |     A.precede(B);  // A runs before B 
 89 |     A.precede(C);  // A runs before C 
 90 |     B.precede(D);  // B runs before D 
 91 |     C.precede(D);  // C runs before D 
 92 | }
 93 | ```
 94 | <img align="right" width="20%" src="./image/cpp-task.png">
 95 | 
 96 | 上面代码中想要生成预期的DAG图需要人工显式定义每两个节点之间的依赖关系，这种方式虽然理解比较直观，但是缺点也非常明显：
 97 | 
 98 | * **在有大量任务的时候，人工定义DAG图比较困难并且容易出错。现实中的业务系统一般是多人同时开发，这就需要模块owner对所有的任务节点之间的依赖关系进行人工梳理，可维护性较差。**
 99 | * **工业环境中很多业务，往往以数据流驱动的方式表达会更加清晰，这就需要花费大量时间来将系统逻辑从数据驱动表示强行转化为任务驱动表示来适配调度系统，耗时耗力。**
100 | 
101 | # gparallel如何解决问题
102 | 
103 | gparallel的主要思想有3个：
104 | 
105 | * `数据划分`：将所有数据成员，按照**业务逻辑**和**数据状态**划分为不同的集合。
106 | * `依赖推导`：将所有的代码逻辑，按照功能划分为不同的task节点，并且自动推导task节点之间的依赖关系，建立DAG。
107 | * `任务调用`：通过拓扑排序，将`DAG`转化为`偏序`表示，并使用thread或者coroutine对task进行调度。
108 | 
109 | ## 数据划分
110 | 
111 | 在检索系统中，`数据`一般就是指检索过程中用来存储中间结果和最终结果的变量，比如存储广告的`std::list`，存储标题的`std::string`。gparallel主要从2个角度进行划分：
112 | 
113 | * `按照业务逻辑`：把不同业务逻辑所需要用到的数据划分为不同的集合。比如有不同的广告营销产品，各自都有自己的User、Plan和Ad的集合，以及一些存储数中间结果的变量。为了方便描述，我们用大写字母来表示按照业务逻辑划分出来的数据即可，例如`A`、`B`、`C`等等。
114 | 
115 | * `按照数据状态`：更进一步，对于服务于同一个业务的数据集合(A)，在不同的阶段，又可以划分为不同的状态。例如一个广告队列，初始状态是空(empty)，经过填充以后有N条广告(inited)，又经过了一次按照CTR的排序(ranked)，最后经历了一次截断(truncate)，那么对应四个状态`A_empty`，`A_inited`，`A_ranked`，`A_truncated`。
116 | 
117 | 为了方便理解，我们把划分出来的每个子集（包含不同的阶段），叫做`meta`。前面提到的`A_empty`，`A_inited`，`A_ranked`，`A_truncate`都是`meta`。在gparallel中，我们用[`DECL_META`](include/meta.h)宏来定义一个`meta`。
118 | 
119 | > meta：用来描述**指定业务**所需要的所有数据（指定节点）的集合的一种**数据结构**。
120 | 
121 | 理解gparallel对数据的2层递进划分方式非常重要，因为gparallel的DAG自动推导过程正是依赖于不同的meta。
122 | 
123 | 现实中的系统中，数据成员一般放置在一个叫做`context`或者`thread_data`的结构体中。顾名思义，这些数据的作用范围就是一次请求，一个比较常见的设计是一次请求由线程池中的一个线程来独立负责，所以请求级别的数据，往往也是线程级别的数据。这个`context`或者`thread_data`类型，在代码实现中通常用`meta_storage_t`来表示，即所一次检索中用到的所有数据，都统一存储在这里。
124 | 
125 | 通过定义`getter`和`setter`可以对子集需要包含的元素进行指定，如果定义了`getter`和`setter`就代表这个`meta`中包含这个数据成员。
126 | 
127 | 子集之间也可以互相包含，原理与面向对象中的`继承`是一样的。同理，如果一个任务依赖于一个`meta`，则也同样依赖于这个`meta`的父`meta`，`gparallel`在推导依赖时会自动将继承关系也考虑在内。`继承`机制的主要目的是为了避免重复定义集合的元素，增加代码的可维护性。在实践中，通常将很多业务公用的数据单独定义为一个`meta`，属于单独业务的`meta`，可以从前面的公共`meta`进行继承。
128 | 
129 | 通过下面的例子可以理解`meta_storage_t`、`meta`和`继承`的关系。
130 | 
131 | <div><img align="center" width="100%" src="./image/meta.png"></div>
132 | 
133 | 通过上图可以看到，所有数据被放置在`thread_data`这个对象中(`meta_storage_t`)，通过三个`meta`将`thread_data`中的数据划分为三个集合：
134 | * `meta_common`包含了`thread_data::id`
135 | * `meta_a`包含了`thread_data::business_a`并且继承了`meta_common`的所有元素。
136 | * `meta_b`包含了`thread_data::business_b`并且继承了`meta_common`的所有元素。
137 | 
138 | ## 任务定义
139 | 
140 | 在`gparallel`中，使用一个函数表示一个具体的任务，函数的参数表示任务的`输入`和`输出`。任何一个`meta`既可以作为`输入`，也可以作为`输出`。这里引入2个模版包装器`input`和`output`。如果`meta`用`input`包装，则任务函数会将其当作一个输入数据，同理如果用`output`包装，则会当作输出。
141 | 
142 | 表示任务的函数，必须定义为类的静态成员函数，函数名字必须为`process`，返回类型为`void`。例如：
143 | 
144 | ```cpp
145 | struct DemoNode {
146 |     void process(input<meta_a> a, input<meta_b> b, output<meta_c> c) {
147 |         // process code
148 |         c->mutable_business_c() = a->get_business_a() + b->get_business_b();
149 |     }
150 | }
151 | ```
152 | 上面的`DemoNode`实现了将`business_a`和`business_b`的和赋值给`business_c`的逻辑。
153 | `process`函数可以拥有任意多个`输入`和任意多个`输出`。其中没有`输入`的节点作为起始节点之一，没有`输出`的节点作为终止节点之一。
154 | 
155 | ## 任务调度
156 | 
157 | 通过`register_node`函数将所有节点注册到`DAG`中后，使用`setup_dag_schema`函数可自动实现节点依赖分析以及`DAG`生成。针对生成的`DAG`进行`拓扑排序`，就能得到任务调度顺序。后面可根据具体情况，实现多线程或者多协程调度。
158 | 
159 | ```cpp
160 | dag_schema<thread_data> nodes;
161 | register_node<thread_data, node_a, node_b, node_c ...>::reg(nodes);
162 | setup_dag_schema<thread_data>(nodes);
163 | if (auto tasks = topological_sort<thread_data>(nodes); tasks) {
164 |     for (auto task : tasks.value()) {
165 |         task->mutable_executor()(&td);
166 |     }
167 | }
168 | ```
169 | 
170 | <center><img align="center" src="./image/dispatch.png"></center>
171 | 
172 | # gparallel实战
173 | 
174 | 在本小结中，会从一个现实的场景来描述`gparallel`的使用逻辑。
175 | 
176 | > 问题描述：对一个指定的广告队列，分别请求其`CTR`(点击率)值和`CPM`(千次展示成本)并填充到广告的对应字段，最后分别按照`CTR`和`CPM`进行排序后生成2个新的广告队列供下游使用。
177 | 
178 | 上述流程是广告检索系统里面一个比较典型的逻辑，完整的代码在[./demo/advprocess.cpp](./demo/advprocess.cpp)。
179 | 
180 | ## 数据划分
181 | 
182 | 我们首先梳理一下所需要用到的数据对象：
183 | 
184 | 数据名称 | 类型 |  含义  
185 | -|-|-
186 | advs_original|  advlist_t |  原始的广告队列 |
187 | ctr_data |  advlist_t | 模型返回的ctr数据|
188 | cpm_data |  advlist_t |  模型返回的cpm数据|
189 | advs_ctr_ordered | ctr_response_t |  输出的ctr排序的广告队列|
190 | advs_cpm_ordered | cpm_response_t |  输出的cpm排序的广告队列|
191 | 
192 | 根据上面的定义，我们定义数据集合，业务执行需要用到的所有数据都放在`thread_data`这个集合中：
193 | 
194 | ![demo_thread_data.png](./image/demo_thread_data.png)
195 | 
196 | ```cpp
197 | class thread_data {
198 | public:
199 |     advlist_t advs_original;
200 |     advlist_t advs_ctr_ordered;
201 |     advlist_t advs_cpm_ordered;
202 |     ctr_response_t ctr_data;
203 |     cpm_response_t cpm_data;
204 | };
205 | ```
206 | 
207 | 接下来我们根据不同的业务，将集合划分为不同的子集，每个子集就是一个`meta`，一个元素可以同时属于多个`meta`，`meta`与`meta`之间可以互相包含。
208 | 根据问题的描述，我们可以很容易总结出5个子流程，每个子流程都对应一个数据处理节点： 
209 | <table width="60%">
210 |     <thead>
211 |         <tr>
212 |             <th>流程</th><th>节点名称</th><th>输入</th><th>输出</th>
213 |         </tr>
214 |     </thead>
215 |     <tbody>
216 |         <tr>
217 |             <td>获取CTR值</td><td>get_ctr_node</td><td>advs_original</td><td>ctr_data</td>
218 |         </tr>
219 |         <tr>
220 |             <td>获取CPM值</td><td>get_cpm_node</td><td>advs_original</td><td>cpm_data</td>
221 |         </tr>
222 |         <tr>
223 |             <td>填充字段</td><td>fill_node</td>
224 |             <td>advs_original <br>ctr_data <br>cpm_data</td>
225 |             <td>advs_original*</td>
226 |         </tr>
227 |         <tr>
228 |             <td>生成CTR<br>排序队列</td><td>gen_ctr_node</td><td>advs_original*</td>
229 |             <td>advs_ctr_ordered</td>
230 |         </tr>
231 |         <tr>
232 |             <td>生成CPM<br>排序队列</td><td>gen_cpm_node</td>
233 |             <td>advs_original*</td><td>advs_cpm_ordered</td>
234 |         </tr>
235 |     </tbody>
236 | </table>
237 | 
238 | 
239 | 可以看到原始输入的广告队列是`advs_original`，这里我们将其封装为meta`original`。
240 | 
241 | `get_ctr_node`节点和`get_cpm_node`节点通过meta`original`分别获取`ctr_data`和`cpm_data`两份数据，这两份数据我们用meta`ctr`和meta`cpm`来封装。
242 | 
243 | `fill_node`节点对广告队列进行数据填充，这里注意，节点的输入中有meta`original`，输出中有meta`original_with_ctr_cpm`。这2个meta其实本质上都是`advs_original`的封装，但是因为属于2个阶段(即填充前和填充后)，所以分别用2个不同的meta来表示，在实现上，我们可以直接使用继承功能，复用meta`original`。
244 | 
245 | `gen_ctr_node`和`gen_cpm_node`的输入都包含meta`original_with_ctr_cpm`，表示其依赖于填充后的`advs_original`而不是填充前。
246 | 
247 | 这样就可以根据不同的业务逻辑，把`thread_data`集合划分为不同的`meta`，每个业务只需要关注子集需要用到哪些`meta`，生成哪些`meta`即可。
248 | ![demo_meta.png](./image/demo_meta.png)
249 | 
250 | ## 任务定义
251 | 
252 | 首先实现`get_ctr_node`和`get_cpm_node`这两个任务节点。
253 | ```cpp
254 | struct get_ctr_node {
255 |     static void process(input<original> ori, output<ctr> ctr) {
256 |         INFO("[gparallel] get_ctr_node", "");
257 |         ctr->mutable_ctr_data().resize(ori->mutable_advs_original().size());
258 |         for (int pos = 0; pos < ori->mutable_advs_original().size(); pos++) {
259 |             auto & adv = ori->mutable_advs_original()[pos];
260 |             ctr->mutable_ctr_data()[pos] = 0.1 * static_cast<double>(adv.id);
261 |         }
262 |     }
263 | };
264 | 
265 | struct get_cpm_node {
266 |     static void process(input<original> ori, output<cpm> cpm) {
267 |         INFO("[gparallel] get_cpm_node", "");
268 |         cpm->mutable_cpm_data().resize(ori->mutable_advs_original().size());
269 |         for (int pos = 0; pos < ori->mutable_advs_original().size(); pos++) {
270 |             auto & adv = ori->mutable_advs_original()[pos];
271 |             cpm->mutable_cpm_data()[pos] = 100.2 * static_cast<double>(adv.id);
272 |         }
273 | 
274 |     }
275 | };
276 | ```
277 | 这两个任务的功能相似，都是根据`original`中存储的所有广告，获取对应的`点击率`和`千次展示成本`数据，并且分别保存到`ctr`和`cpm`这两个meta。这里为了简化，我们取一些随机的数字作为`ctr`作为`cpm`。现实中往往需要同步或者异步请求模型服务器来获取。
278 | 
279 | 接下来实现`fill_node`。
280 | ```cpp
281 | struct fill_node {
282 |     static void process(input<ctr> ctr, input<cpm> cpm, input<original> ori, 
283 |         output<original_with_ctr_cpm> ori_ctr_cpm) {
284 |         INFO("[gparallel] fill_node", "");
285 |         for (int pos = 0; pos < ori->mutable_advs_original().size(); pos++) {
286 |             auto & adv = ori_ctr_cpm->mutable_advs_original()[pos];
287 |             adv.ctr = ctr->mutable_ctr_data()[pos];
288 |             adv.cpm = cpm->mutable_cpm_data()[pos];
289 |             INFO("[gparallel] ori_ctr_cpm adv:[%d] ctr:[%lf] cpm:[%lf]", adv.id, adv.ctr, adv.cpm);
290 |         }
291 |     }
292 | };
293 | ```
294 | `fill_node`节点将前面`get_ctr_node`和`get_cpm_node`这两个节点的输出作为自己的输入，最后生成`original_with_ctr_cpm`。这里可以看到，`original`和`original_with_ctr_cpm`分别作为节点的输入和输出，虽然这两个meta中包含的数据都是`advs_original`，但是对应了**不同的状态**。`original`代表了`advs_original`一开始的状态，而`original_with_ctr_cpm`代表了已经填充了`ctr`作为`cpm`数据的状态。
295 | 
296 | 然后实现`gen_ctr_node`和`gen_cpm_node`。
297 | ```cpp
298 | struct gen_ctr_node {
299 |     static void process(input<original_with_ctr_cpm> ori_ctr_cpm, 
300 |         output<ctr_ordered_advlist> ctr_ordered) {
301 |         INFO("[gparallel] gen_ctr_node", "");
302 |         ctr_ordered->mutable_advs_ctr_ordered() = ori_ctr_cpm->mutable_advs_original();
303 |         std::sort(ctr_ordered->mutable_advs_ctr_ordered().begin(),
304 |             ctr_ordered->mutable_advs_ctr_ordered().end(), 
305 |             [](const auto& a, const auto& b)->bool{return a.ctr > b.ctr;});
306 | 
307 |     }
308 | };
309 | 
310 | struct gen_cpm_node {
311 |     static void process(input<original_with_ctr_cpm> ori_ctr_cpm, 
312 |         output<cpm_ordered_advlist> cpm_ordered) {
313 |         INFO("[gparallel] gen_cpm_node", "");
314 |         cpm_ordered->mutable_advs_cpm_ordered() = ori_ctr_cpm->mutable_advs_original();
315 |         std::sort(cpm_ordered->mutable_advs_cpm_ordered().begin(),
316 |             cpm_ordered->mutable_advs_cpm_ordered().end(),
317 |             [](const auto& a, const auto& b)->bool{return a.cpm > b.cpm;});
318 |     }
319 | };
320 | ```
321 | 这里需要注意的是，`gen_ctr_node`和`gen_cpm_node`这两个节点，需要的是**已经填充了`ctr`作为`cpm`数据**的`advs_original`，所以输入meta必须为`original_with_ctr_cpm`。这一点对于生成正确的DAG来说非常重要。`gparallel`正是通过区分同一数据的不同阶段，来实现正确的任务调度。
322 | 
323 | 最后，`end_node`对所有的结果进行汇总，并反馈给下游。
324 | ```cpp
325 | struct end_node {
326 |     static void process(input<ctr_ordered_advlist> ctr, input<cpm_ordered_advlist> cpm) {
327 |         INFO("[gparallel] end_node", "");
328 |         for (auto& adv : cpm->mutable_advs_cpm_ordered()) {
329 |             INFO("CPM ordered:[%d]", adv.id);
330 |         }
331 |         for (auto& adv : ctr->mutable_advs_ctr_ordered()) {
332 |             INFO("CTR ordered:[%d]", adv.id);
333 |         }
334 |     }
335 | };
336 | ```
337 | 
338 | ## 任务调度
339 | 
340 | 在所有的meta和node都定义好以后，我们可以通过下面流程进行任务调度。
341 | 首先我们需要申请相应的内存来存储我们所有的数据变量，这里我们申请一个`thread_data`的实例：
342 | 
343 | ```cpp
344 | thread_data td{{advertisement(1), advertisement(2), advertisement(3)}, {},{},{},{}};
345 | ```
346 | 
347 | 我们还需要一个`节点容器`，来存放所有的数据处理节点：
348 | 
349 | ```cpp
350 | dag_schema<thread_data> nodes;
351 | ```
352 | 
353 | 接下来我们将所有的`节点`，注册到刚才申请的`节点容器`中。
354 | 
355 | ```cpp
356 | register_node<thread_data, get_ctr_node, get_cpm_node>::reg(nodes);
357 | register_node<thread_data, fill_node>::reg(nodes);
358 | register_node<thread_data, gen_ctr_node, gen_cpm_node, end_node>::reg(nodes);
359 | ```
360 | 
361 | `register_node`模版负责注册节点到容器`nodes`中，其中第一个模版参数是我们所有数据最终存储的类，也就是`meta_storage_t`。剩余任意多个模版参数分别为各个node。`reg`函数的输入参数为`dag_schema`类型的节点容器实例。
362 | 
363 | 接下来推导所有节点的依赖关系：
364 | 
365 | ```cpp
366 | setup_dag_schema<thread_data>(nodes);
367 | ```
368 | 
369 | 最后，我们对DAG上面的所有节点进行`拓扑排序`，并且按照排序后的顺序依次进行调用：
370 | 
371 | ```cpp
372 | if (auto tasks = topological_sort<thread_data>(nodes); tasks) {
373 |     for (auto task : tasks.value()) {
374 |         INFO("Execute[%s]", task->name().c_str());
375 |         task->mutable_executor()(&td);
376 |     }
377 | }
378 | ```
379 | 编译执行：
380 | ```shell
381 | $ cd build
382 | $ cmake ../
383 | $ make demo
384 | $ ./demo
385 | ```
386 | 如果我们打开了debug日志，就可以在demo的输出中看到下面的DAG信息：
387 | ```
388 | [2020-05-20 23:24:11.082883] [] [info][~/gparallel/include/dag_schema.h][127]node_depends_after
389 | http://graphviz.it/#
390 | [2020-05-20 23:24:11.083212] [] [info][~/gparallel/include/dag_schema.h][128]
391 | digraph node_depends_after{
392 | rankdir=BT;
393 | size="8,5";
394 | "fill_node" -> "get_ctr_node";
395 | "fill_node" -> "get_cpm_node";
396 | "gen_ctr_node" -> "fill_node";
397 | "gen_cpm_node" -> "fill_node";
398 | "end_node" -> "gen_ctr_node";
399 | "end_node" -> "gen_cpm_node";
400 | }
401 | ```
402 | 
403 | 通过[http://graphviz.it/#](http://graphviz.it/#)，可以看到`gparallel`自动推导得到的DAG。
404 | 
405 | ![demo_dag.png](./image/demo_dag.png)
406 | 
407 |  同时可以看到全部业务执行的结果：
408 |  ```
409 | [2020-05-20 23:24:11.084784] [] [info][advprocess.cpp][141]Execute[get_ctr_node]
410 | [2020-05-20 23:24:11.084792] [] [info][advprocess.cpp][63][gparallel] get_ctr_node
411 | [2020-05-20 23:24:11.084866] [] [info][advprocess.cpp][141]Execute[get_cpm_node]
412 | [2020-05-20 23:24:11.084898] [] [info][advprocess.cpp][74][gparallel] get_cpm_node
413 | [2020-05-20 23:24:11.084905] [] [info][advprocess.cpp][141]Execute[fill_node]
414 | [2020-05-20 23:24:11.084910] [] [info][advprocess.cpp][87][gparallel] fill_node
415 | [2020-05-20 23:24:11.084916] [] [info][advprocess.cpp][92][gparallel] ori_ctr_cpm adv:[1] ctr:[0.100000] cpm:[100.200000]
416 | [2020-05-20 23:24:11.084920] [] [info][advprocess.cpp][92][gparallel] ori_ctr_cpm adv:[2] ctr:[0.200000] cpm:[200.400000]
417 | [2020-05-20 23:24:11.084956] [] [info][advprocess.cpp][92][gparallel] ori_ctr_cpm adv:[3] ctr:[0.300000] cpm:[300.600000]
418 | [2020-05-20 23:24:11.084966] [] [info][advprocess.cpp][141]Execute[gen_ctr_node]
419 | [2020-05-20 23:24:11.084992] [] [info][advprocess.cpp][100][gparallel] gen_ctr_node
420 | [2020-05-20 23:24:11.085003] [] [info][advprocess.cpp][141]Execute[gen_cpm_node]
421 | [2020-05-20 23:24:11.085007] [] [info][advprocess.cpp][112][gparallel] gen_cpm_node
422 | [2020-05-20 23:24:11.085011] [] [info][advprocess.cpp][141]Execute[end_node]
423 | [2020-05-20 23:24:11.085015] [] [info][advprocess.cpp][122][gparallel] end_node
424 | [2020-05-20 23:24:11.085046] [] [info][advprocess.cpp][124]CPM ordered:[3]
425 | [2020-05-20 23:24:11.085055] [] [info][advprocess.cpp][124]CPM ordered:[2]
426 | [2020-05-20 23:24:11.085062] [] [info][advprocess.cpp][124]CPM ordered:[1]
427 | [2020-05-20 23:24:11.085069] [] [info][advprocess.cpp][127]CTR ordered:[3]
428 | [2020-05-20 23:24:11.085076] [] [info][advprocess.cpp][127]CTR ordered:[2]
429 | [2020-05-20 23:24:11.085082] [] [info][advprocess.cpp][127]CTR ordered:[1]
430 |  ```
431 | 
432 | Some friends ask how to execute this DAG parallelly?
433 | 
434 | One solution is:
435 | ```C++
436 | void invoke(Node &node, std::shared_ptr<std::latch> done) {
437 |     std::shared_ptr<std::latch> dep_done = std::make_shared<>(node.dependency_list.size());
438 |     for (auto &dep : node.dependency_list) {
439 |         invoke(dep, dep_done);
440 |     }
441 |     thread_pool.push([&node, done, dep_done](){
442 |         dep_done->wait();
443 |         node.execute();
444 |         done->count_down();
445 |     })
446 | }
447 | 
448 | int main() {
449 |     std::list<Node> node_list;
450 |     // Find the final node
451 |     Node &final_node = xxx;
452 |     std::shared_ptr<std::latch> done = std::make_shared<>(1);
453 |     invoke(final_node, latch);
454 |     latch->wait();
455 |     // Final result is ready here
456 | }
457 | ```
458 | By huyifeng (2023/08/26)
459 | 
460 | 
461 | 
462 | 
463 | 
464 | 


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460 | Corresponding Source of the work from the predecessor in interest, if
461 | the predecessor has it or can get it with reasonable efforts.
462 | 
463 |   You may not impose any further restrictions on the exercise of the
464 | rights granted or affirmed under this License.  For example, you may
465 | not impose a license fee, royalty, or other charge for exercise of
466 | rights granted under this License, and you may not initiate litigation
467 | (including a cross-claim or counterclaim in a lawsuit) alleging that
468 | any patent claim is infringed by making, using, selling, offering for
469 | sale, or importing the Program or any portion of it.
470 | 
471 |   11. Patents.
472 | 
473 |   A "contributor" is a copyright holder who authorizes use under this
474 | License of the Program or a work on which the Program is based.  The
475 | work thus licensed is called the contributor's "contributor version".
476 | 
477 |   A contributor's "essential patent claims" are all patent claims
478 | owned or controlled by the contributor, whether already acquired or
479 | hereafter acquired, that would be infringed by some manner, permitted
480 | by this License, of making, using, or selling its contributor version,
481 | but do not include claims that would be infringed only as a
482 | consequence of further modification of the contributor version.  For
483 | purposes of this definition, "control" includes the right to grant
484 | patent sublicenses in a manner consistent with the requirements of
485 | this License.
486 | 
487 |   Each contributor grants you a non-exclusive, worldwide, royalty-free
488 | patent license under the contributor's essential patent claims, to
489 | make, use, sell, offer for sale, import and otherwise run, modify and
490 | propagate the contents of its contributor version.
491 | 
492 |   In the following three paragraphs, a "patent license" is any express
493 | agreement or commitment, however denominated, not to enforce a patent
494 | (such as an express permission to practice a patent or covenant not to
495 | sue for patent infringement).  To "grant" such a patent license to a
496 | party means to make such an agreement or commitment not to enforce a
497 | patent against the party.
498 | 
499 |   If you convey a covered work, knowingly relying on a patent license,
500 | and the Corresponding Source of the work is not available for anyone
501 | to copy, free of charge and under the terms of this License, through a
502 | publicly available network server or other readily accessible means,
503 | then you must either (1) cause the Corresponding Source to be so
504 | available, or (2) arrange to deprive yourself of the benefit of the
505 | patent license for this particular work, or (3) arrange, in a manner
506 | consistent with the requirements of this License, to extend the patent
507 | license to downstream recipients.  "Knowingly relying" means you have
508 | actual knowledge that, but for the patent license, your conveying the
509 | covered work in a country, or your recipient's use of the covered work
510 | in a country, would infringe one or more identifiable patents in that
511 | country that you have reason to believe are valid.
512 | 
513 |   If, pursuant to or in connection with a single transaction or
514 | arrangement, you convey, or propagate by procuring conveyance of, a
515 | covered work, and grant a patent license to some of the parties
516 | receiving the covered work authorizing them to use, propagate, modify
517 | or convey a specific copy of the covered work, then the patent license
518 | you grant is automatically extended to all recipients of the covered
519 | work and works based on it.
520 | 
521 |   A patent license is "discriminatory" if it does not include within
522 | the scope of its coverage, prohibits the exercise of, or is
523 | conditioned on the non-exercise of one or more of the rights that are
524 | specifically granted under this License.  You may not convey a covered
525 | work if you are a party to an arrangement with a third party that is
526 | in the business of distributing software, under which you make payment
527 | to the third party based on the extent of your activity of conveying
528 | the work, and under which the third party grants, to any of the
529 | parties who would receive the covered work from you, a discriminatory
530 | patent license (a) in connection with copies of the covered work
531 | conveyed by you (or copies made from those copies), or (b) primarily
532 | for and in connection with specific products or compilations that
533 | contain the covered work, unless you entered into that arrangement,
534 | or that patent license was granted, prior to 28 March 2007.
535 | 
536 |   Nothing in this License shall be construed as excluding or limiting
537 | any implied license or other defenses to infringement that may
538 | otherwise be available to you under applicable patent law.
539 | 
540 |   12. No Surrender of Others' Freedom.
541 | 
542 |   If conditions are imposed on you (whether by court order, agreement or
543 | otherwise) that contradict the conditions of this License, they do not
544 | excuse you from the conditions of this License.  If you cannot convey a
545 | covered work so as to satisfy simultaneously your obligations under this
546 | License and any other pertinent obligations, then as a consequence you may
547 | not convey it at all.  For example, if you agree to terms that obligate you
548 | to collect a royalty for further conveying from those to whom you convey
549 | the Program, the only way you could satisfy both those terms and this
550 | License would be to refrain entirely from conveying the Program.
551 | 
552 |   13. Use with the GNU Affero General Public License.
553 | 
554 |   Notwithstanding any other provision of this License, you have
555 | permission to link or combine any covered work with a work licensed
556 | under version 3 of the GNU Affero General Public License into a single
557 | combined work, and to convey the resulting work.  The terms of this
558 | License will continue to apply to the part which is the covered work,
559 | but the special requirements of the GNU Affero General Public License,
560 | section 13, concerning interaction through a network will apply to the
561 | combination as such.
562 | 
563 |   14. Revised Versions of this License.
564 | 
565 |   The Free Software Foundation may publish revised and/or new versions of
566 | the GNU General Public License from time to time.  Such new versions will
567 | be similar in spirit to the present version, but may differ in detail to
568 | address new problems or concerns.
569 | 
570 |   Each version is given a distinguishing version number.  If the
571 | Program specifies that a certain numbered version of the GNU General
572 | Public License "or any later version" applies to it, you have the
573 | option of following the terms and conditions either of that numbered
574 | version or of any later version published by the Free Software
575 | Foundation.  If the Program does not specify a version number of the
576 | GNU General Public License, you may choose any version ever published
577 | by the Free Software Foundation.
578 | 
579 |   If the Program specifies that a proxy can decide which future
580 | versions of the GNU General Public License can be used, that proxy's
581 | public statement of acceptance of a version permanently authorizes you
582 | to choose that version for the Program.
583 | 
584 |   Later license versions may give you additional or different
585 | permissions.  However, no additional obligations are imposed on any
586 | author or copyright holder as a result of your choosing to follow a
587 | later version.
588 | 
589 |   15. Disclaimer of Warranty.
590 | 
591 |   THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
592 | APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
596 | PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
597 | IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
599 | 
600 |   16. Limitation of Liability.
601 | 
602 |   IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
610 | SUCH DAMAGES.
611 | 
612 |   17. Interpretation of Sections 15 and 16.
613 | 
614 |   If the disclaimer of warranty and limitation of liability provided
615 | above cannot be given local legal effect according to their terms,
616 | reviewing courts shall apply local law that most closely approximates
617 | an absolute waiver of all civil liability in connection with the
618 | Program, unless a warranty or assumption of liability accompanies a
619 | copy of the Program in return for a fee.
620 | 
621 |                      END OF TERMS AND CONDITIONS
622 | 
623 |             How to Apply These Terms to Your New Programs
624 | 
625 |   If you develop a new program, and you want it to be of the greatest
626 | possible use to the public, the best way to achieve this is to make it
627 | free software which everyone can redistribute and change under these terms.
628 | 
629 |   To do so, attach the following notices to the program.  It is safest
630 | to attach them to the start of each source file to most effectively
631 | state the exclusion of warranty; and each file should have at least
632 | the "copyright" line and a pointer to where the full notice is found.
633 | 
634 |     <one line to give the program's name and a brief idea of what it does.>
635 |     Copyright (C) <year>  <name of author>
636 | 
637 |     This program is free software: you can redistribute it and/or modify
638 |     it under the terms of the GNU General Public License as published by
639 |     the Free Software Foundation, either version 3 of the License, or
640 |     (at your option) any later version.
641 | 
642 |     This program is distributed in the hope that it will be useful,
643 |     but WITHOUT ANY WARRANTY; without even the implied warranty of
644 |     MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
645 |     GNU General Public License for more details.
646 | 
647 |     You should have received a copy of the GNU General Public License
648 |     along with this program.  If not, see <https://www.gnu.org/licenses/>.
649 | 
650 | Also add information on how to contact you by electronic and paper mail.
651 | 
652 |   If the program does terminal interaction, make it output a short
653 | notice like this when it starts in an interactive mode:
654 | 
655 |     <program>  Copyright (C) <year>  <name of author>
656 |     This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
657 |     This is free software, and you are welcome to redistribute it
658 |     under certain conditions; type `show c' for details.
659 | 
660 | The hypothetical commands `show w' and `show c' should show the appropriate
661 | parts of the General Public License.  Of course, your program's commands
662 | might be different; for a GUI interface, you would use an "about box".
663 | 
664 |   You should also get your employer (if you work as a programmer) or school,
665 | if any, to sign a "copyright disclaimer" for the program, if necessary.
666 | For more information on this, and how to apply and follow the GNU GPL, see
667 | <https://www.gnu.org/licenses/>.
668 | 
669 |   The GNU General Public License does not permit incorporating your program
670 | into proprietary programs.  If your program is a subroutine library, you
671 | may consider it more useful to permit linking proprietary applications with
672 | the library.  If this is what you want to do, use the GNU Lesser General
673 | Public License instead of this License.  But first, please read
674 | <https://www.gnu.org/licenses/why-not-lgpl.html>.
675 | 


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