schedule.cpp 14.6 KB
Newer Older
Paul's avatar
Paul committed
1
2
3
#include <migraphx/schedule.hpp>
#include <migraphx/program.hpp>
#include <migraphx/instruction.hpp>
4
#include <migraphx/op/identity.hpp>
Paul's avatar
Paul committed
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
#include <migraphx/iterator_for.hpp>
#include <migraphx/dfor.hpp>
#include <migraphx/functional.hpp>
#include <migraphx/ranges.hpp>
#include <unordered_map>
#include <unordered_set>
#include <set>
#include <deque>

namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {

auto get_inputs()
{
    return [](auto i) { return i->inputs(); };
}

auto get_outputs()
{
    return [](auto i) { return i->outputs(); };
}

struct stream_info
{
    std::unordered_map<instruction_ref, std::size_t> ins2stream;
    std::unordered_map<instruction_ref, std::size_t> weights;
    std::unordered_map<instruction_ref, std::size_t> iweights;

    void accumulate_weights(instruction_ref last, const schedule_model& model)
    {
        fix<std::size_t>([&](auto self, auto ins) -> std::size_t {
            if(not contains(weights, ins))
            {
                std::size_t weight = 0;
                auto&& op          = ins->get_operator();
                if(not is_context_free(op) and op.name()[0] != '@')
                    weight = model.weight(op);
                iweights[ins] = weight;
                weights[ins] =
                    std::accumulate(ins->inputs().begin(),
                                    ins->inputs().end(),
                                    weight,
                                    [&](std::size_t w, instruction_ref i) { return w + self(i); });
            }
            return weights[ins];
        })(last);
    }

    std::vector<instruction_ref>::iterator sort_args(std::vector<instruction_ref>& args)
    {
        if(args.size() < 2)
        {
            return args.end();
        }

        const std::size_t min_partition_threshold = 2;
        auto compare                              = by(std::greater<>{}, [&](auto x) {
            return std::make_tuple(this->weights[x], x->inputs().size());
        });
        std::sort(args.begin(), args.end(), compare);

        auto it = std::lower_bound(std::next(args.begin()),
                                   args.end(),
                                   min_partition_threshold,
                                   [&](auto i, std::size_t w) { return this->weights[i] > w; });
        assert(it == args.end() or this->weights[*it] <= min_partition_threshold);
        assert(it == args.end() or std::prev(it) == args.begin() or
               this->weights[*std::prev(it)] > min_partition_threshold);
        return it;
    }

    struct partition
    {
        std::size_t weight = 0;
        std::vector<instruction_ref> instructions{};

        void add(instruction_ref ins, std::size_t w)
        {
            weight += w;
            instructions.push_back(ins);
        }
    };

    void assign_streams(program& p, std::size_t n)
    {
        partition critical;
        std::unordered_map<instruction_ref, std::deque<partition>> partitions;
        partitions.reserve(weights.size());
        fix([&](auto self, auto ins, auto& part) {
            assert(ins != p.end());
            if(contains(partitions, ins))
                return;
            assert(p.has_instruction(ins));
            // Add an entry so we know the instruction was visited
            partitions[ins];
            part.add(ins, this->iweights[ins]);

            auto args         = ins->inputs();
            auto threshold_it = this->sort_args(args);

            if(not args.empty())
            {
                assert(threshold_it != args.begin());
                self(args.front(), part);
                for(auto i : range(std::next(args.begin()), threshold_it))
                {
                    partitions[ins].emplace_back();
                    self(i, partitions[ins].back());
                }
                for(auto i : range(threshold_it, args.end()))
                {
                    self(i, part);
                }
            }
            // Sort instructions
            p.move_instruction(ins, p.end());
        })(std::prev(p.end()), critical);

        // Set the critical partition to stream 0
        set_stream(critical, 0);
        std::vector<std::size_t> streams(n - 1);
        // Assign streams for the other partitions
        for(auto&& ins_part : partitions)
        {
            std::sort(
                ins_part.second.begin(), ins_part.second.end(), by(std::greater<>{}, [](auto&& x) {
                    return std::make_tuple(x.weight, x.instructions.size());
                }));
            for(auto&& part : ins_part.second)
            {
                auto stream = std::min_element(streams.begin(), streams.end()) - streams.begin();
                set_stream(part, stream + 1);
                streams[stream] += part.weight;
            }
        }
    }

    void set_stream(const partition& p, std::size_t n)
    {
        for(auto ins : p.instructions)
            if(iweights[ins] > 0)
                set_stream(ins, n);
    }

    void set_stream(instruction_ref ins, std::size_t n)
    {
        assert(iweights[ins] > 0);
        ins2stream[ins] = n;
    }

    std::size_t get_stream(instruction_ref ins) const { return ins2stream.at(ins); }

    bool has_stream(instruction_ref ins) const { return contains(ins2stream, ins); }

    template <class F>
    bool different(F f, std::size_t stream) const
    {
        bool result = false;
        f([&](auto s) {
            if(s != stream)
            {
                result = true;
                return false;
            }
            // cppcheck-suppress uselessAssignmentArg
            stream = s;
            return true;
        });
        return result;
    }

    template <class F>
    bool different(F f) const
    {
        bool result = false;
        f([&](auto s) {
            result = this->different(f, s);
            return false;
        });
        return result;
    }

    template <class Selector>
    auto get_streams_from(instruction_ref start, Selector select) const
    {
        return [=](auto f) {
            return fix<bool>([&](auto self, auto ins) {
                for(auto i : select(ins))
                {
                    if(iweights.at(i) == 0)
                    {
                        if(not self(i))
                            return false;
                    }
                    else
                    {
                        if(not f(this->get_stream(i)))
                            return false;
                    }
                }
                return true;
            })(start);
        };
    }

    std::unordered_set<std::size_t> get_streams(instruction_ref ins) const
    {
        if(has_stream(ins))
            return {get_stream(ins)};
        std::unordered_set<std::size_t> result;
        get_streams_from(ins, get_inputs())([&](auto s) {
            result.insert(s);
            return true;
        });
        return result;
    }

    template <class... Ts>
    bool is_merge_point(instruction_ref ins, Ts... xs) const
    {
        return different(get_streams_from(ins, get_inputs()), xs...);
    }

    template <class... Ts>
    bool is_split_point(instruction_ref ins, Ts... xs) const
    {
        return different(get_streams_from(ins, get_outputs()), xs...);
    }

    std::vector<instruction_ref> get_recorded_instructions(instruction_ref start)
    {
        std::vector<instruction_ref> result;
        std::unordered_map<std::size_t, instruction_ref> m;
        fix([&](auto self, auto ins) {
            for(auto i : ins->inputs())
            {
                if(iweights.at(i) == 0)
                {
                    self(i);
                    continue;
                }
                auto stream = this->get_stream(i);
                if(not contains(m, stream))
                    m[stream] = i;
                else
                    m[stream] = std::min(m[stream], i, by(std::less<>{}, [&](auto x) {
                                             return std::distance(x, start);
                                         }));
            }
        })(start);
        std::transform(
            m.begin(), m.end(), std::back_inserter(result), [](auto&& p) { return p.second; });
        return result;
    }

    std::unordered_map<instruction_ref, std::vector<std::vector<instruction_ref>>>
    find_concurrent_instructions(program& p)
    {
        std::unordered_map<instruction_ref, std::vector<std::vector<instruction_ref>>> result;
        std::unordered_map<instruction_ref, std::unordered_set<instruction_ref>> merge_from;
        result.reserve(p.size());
        merge_from.reserve(p.size());
        for(auto ins : reverse_iterator_for(p))
        {
            for(auto&& arg : ins->outputs())
            {
                if(is_merge_point(arg))
                    merge_from[ins].insert(arg);
                merge_from[ins].insert(merge_from[arg].begin(), merge_from[arg].end());
            }

            auto streams = this->get_streams(ins);

            // Collect concur instructions for each merge point.
            for(auto& merge : merge_from[ins])
            {
                for(auto stream : streams)
                {
                    if(result[merge].size() <= stream)
                        result[merge].resize(stream + 1);
                    auto&& r = result[merge][stream];
                    r.push_back(ins);
                    // Copy inputs if they dont have a stream(and are not a builtin and context
                    // free). Inputs without a stream can have a implicit dependency
                    std::copy_if(ins->inputs().begin(),
                                 ins->inputs().end(),
                                 std::back_inserter(r),
                                 [&](auto x) {
                                     return not this->has_stream(x) and
                                            not is_context_free(x->get_operator()) and
                                            x->name().front() != '@';
                                 });
                }
            }
        }
        return result;
    }

    std::unordered_map<instruction_ref, std::unordered_set<instruction_ref>>
    get_conflicts(program& p)
    {
        std::unordered_map<instruction_ref, std::unordered_set<instruction_ref>> conflict_table;
        auto concur_ins = this->find_concurrent_instructions(p);
        for(auto&& merge : concur_ins)
        {
            dfor(merge.second.size(), merge.second.size())([&](auto i, auto j) {
                if(i == j)
                    return;
                for(auto ins1 : merge.second[i])
                {
                    auto p1 = std::distance(ins1, merge.first);
                    for(auto ins2 : merge.second[j])
                    {
                        if(ins1 == ins2)
                            continue;
                        auto p2 = std::distance(ins2, merge.first);
                        // The smaller distance means the instruction occurs later
                        if(p1 > p2)
                            conflict_table[ins2].insert(ins1);
                        else
                            conflict_table[ins1].insert(ins2);
                    }
                }
            });
        }
        // Remove duplicates
        for(auto&& ip : conflict_table)
        {
            auto ins1 = ip.first;
            for(auto ins2 : ip.second)
                if(contains(conflict_table[ins2], ins1))
                    conflict_table[ins2].erase(ins1);
        }
        return conflict_table;
    }
};

void schedule::apply(program& p) const
{
Paul's avatar
Paul committed
344
    if(not enable)
Paul's avatar
Paul committed
345
        return;
Paul's avatar
Paul committed
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
    stream_info si;
    auto last = std::prev(p.end());
    si.accumulate_weights(last, model);
    si.assign_streams(p, model.concurrency());

    if(enabled(MIGRAPHX_TRACE_COMPILE{}))
    {
        p.annotate(std::cout, [&](auto ins) {
            std::cout << ":";
            std::cout << " weight=" << si.weights.at(ins);
            std::cout << " input={";
            si.get_streams_from(ins, get_inputs())([&](auto s) {
                std::cout << s << ",";
                return true;
            });
            std::cout << "}";
            if(si.has_stream(ins))
                std::cout << " stream=" << si.get_stream(ins);
        });
        std::cout << std::endl;
    }

    // Schedule instructions
    std::size_t wait_id = 0;
    std::unordered_map<instruction_ref, std::size_t> ins2wait;
    std::unordered_map<std::size_t, std::unordered_set<std::size_t>> waited_for;
    std::unordered_map<instruction_ref, std::unordered_set<std::size_t>> ins2waited;
    ins2wait.reserve(p.size());
    ins2waited.reserve(p.size());
    for(auto ins : iterator_for(p))
    {
        // Only schedule instructions that have a stream
        if(not si.has_stream(ins))
            continue;
        assert(si.weights[ins] > 0);
        // Schedule instruction on the stream
        auto stream = si.get_stream(ins);
        assert(stream < model.concurrency());
        model.sched(p, ins, stream);
        // Insert wait instructions
        if(si.is_merge_point(ins, stream))
        {
            for(auto i : si.get_recorded_instructions(ins))
            {
                if(not si.has_stream(i))
                    continue;
                auto istream = si.get_stream(i);
                if(stream == istream)
                    continue;
                // Create a new event if it hasn't been recorded
                if(not contains(ins2wait, i))
                {
                    ins2wait[i] = wait_id;
                    model.record(p, i, wait_id);
                    wait_id++;
                }
                auto w = ins2wait.at(i);
                // If we already waited for the event on this stream then dont
                // insert another wait event
                if(not contains(waited_for[stream], w))
                    model.wait(p, ins, w);
                // Store the event as waited
                waited_for[stream].insert(w);
                // Store all wait events that have been waited on prior to the recorded instruction
                waited_for[stream].insert(ins2waited[i].begin(), ins2waited[i].end());
            }
        }
        // Store wait events that have already been waited on
        if(si.is_split_point(ins, stream))
        {
            ins2waited[ins] = waited_for[stream];
        }
    }

    // Add memory conflicts
    auto conflict_table = si.get_conflicts(p);
    for(auto&& ip : conflict_table)
    {
        if(ip.second.empty())
            continue;
        std::vector<instruction_ref> args;
        args.push_back(ip.first);
        args.insert(args.end(), ip.second.begin(), ip.second.end());
        p.insert_instruction(std::next(ip.first), op::identity{}, args);
    }
}

} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx