tile_distribution.hpp 17.4 KB
Newer Older
Chao Liu's avatar
Chao Liu committed
1
2
3
4
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
344
345
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
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
// SPDX-License-Identifier: MIT
// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.

#pragma once

#include "ck/utility/common_header.hpp"
#include "ck/tensor_description/tensor_descriptor.hpp"
#include "ck/tensor_description/tensor_descriptor_helper.hpp"
#include "ck/tensor_description/tensor_adaptor.hpp"
#include "ck/tensor_description/macro_func_tensor_adaptor_from_encoding.hpp"

#include "ck/tile_program/tile/static_tile_distribution_encoding.hpp"

namespace ck {
namespace tile_program {

// distributed span
template <index_t... PartialHsLengths>
struct TileDistributedSpan
{
    using Impl = Sequence<PartialHsLengths...>;

    static constexpr auto impl_ = Impl{};

    __host__ __device__ static constexpr bool IsStatic() { return true; }
};

// distributed index
template <index_t... PartialHsIndices>
struct TileDistributedIndex
{
    using Impl = Sequence<PartialHsIndices...>;

    static constexpr auto impl_ = Impl{};

    __host__ __device__ static constexpr bool IsStatic() { return true; }
};

namespace detail {

template <index_t... Is>
__host__ __device__ constexpr auto make_tile_distributed_span(Sequence<Is...>)
{
    return TileDistributedSpan<Is...>{};
}

template <index_t... Is>
__host__ __device__ constexpr auto make_tile_distributed_index(Sequence<Is...>)
{
    return TileDistributedIndex<Is...>{};
}

} // namespace detail

template <typename PsYs2XsAdaptor_,
          typename Ys2DDescriptor_,
          typename StaticTileDistributionEncoding_,
          typename TileDistributionDetail_> // FIXME: this is for hold ad-hoc but useful info,
                                            // should be more elegnat
struct TileDistribution
{
    using PsYs2XsAdaptor = remove_cvref_t<PsYs2XsAdaptor_>;
    using Ys2DDescriptor = remove_cvref_t<Ys2DDescriptor_>;
    using DstrEncode     = remove_cvref_t<StaticTileDistributionEncoding_>;
    using DstrDetail     = remove_cvref_t<TileDistributionDetail_>;

    static_assert(PsYs2XsAdaptor::IsStatic() && Ys2DDescriptor::IsStatic(),
                  "wrong! should be static");

    static constexpr index_t NDimX = PsYs2XsAdaptor::GetNumOfBottomDimension();
    static constexpr index_t NDimY = Ys2DDescriptor::GetNumOfTopDimension();
    static constexpr index_t NDimP = PsYs2XsAdaptor::GetNumOfTopDimension() - NDimY;
    static constexpr index_t NDimR = StaticTileDistributionEncoding_::NDimR;

    PsYs2XsAdaptor ps_ys_to_xs_;
    Ys2DDescriptor ys_to_d_;

    __host__ __device__ static constexpr index_t GetNumOfDimensionX() { return NDimX; }
    __host__ __device__ static constexpr index_t GetNumOfDimensionY() { return NDimY; }
    __host__ __device__ static constexpr index_t GetNumOfDimensionP() { return NDimP; }
    __host__ __device__ static constexpr index_t GetNumOfDimensionR() { return NDimR; }

    __host__ __device__ static constexpr auto GetLengths()
    {
#if 0
        // FIXME: TensorAdaptor::GetBottomDimensionLengths is wrong. re-enable this after it's fixed
        ps_ys_to_xs_.GetBottomDimensionLengths();
#else
        return generate_tuple(
            [&](auto i) {
                constexpr index_t x_length =
                    container_reduce(typename DstrEncode::HsLengthss{}[i], math::multiplies{}, 1);

                return Number<x_length>{};
            },
            Number<NDimX>{});
#endif
    }

    __host__ __device__ constexpr const auto& GetPsYs2XsAdaptor() const { return ps_ys_to_xs_; }

    __host__ __device__ constexpr const auto& GetYs2DDescriptor() const { return ys_to_d_; }

    __host__ __device__ static constexpr auto GetStaticTileDistributionEncoding()
    {
        return DstrEncode{};
    }

#if 1
    // Calculate Replication index [R0, R1, ...] based on Partion index
    // FIXME: very nasty implementation
    template <typename PartitionIndex>
    __host__ __device__ auto CalculateRsIndexFromPsIndex(const PartitionIndex& ps_idx) const
    {
        static_assert(PartitionIndex::Size() == NDimP, "wrong!");

        const auto ps_ys_idx = container_concat(ps_idx, Array<index_t, NDimY>{0});

        const auto dummy_adaptor_coord = make_tensor_adaptor_coordinate(ps_ys_to_xs_, ps_ys_idx);

        Array<index_t, NDimR> rs_idx;

        static_for<0, NDimP, 1>{}([&](auto idim_p) {
            constexpr index_t ndim_low = DstrEncode::ps_to_rhss_major_[idim_p].Size();

            static_for<0, ndim_low, 1>{}([&](auto i) {
                constexpr index_t rh_major = DstrEncode::ps_to_rhss_major_[idim_p][i];
                constexpr index_t rh_minor = DstrEncode::ps_to_rhss_minor_[idim_p][i];

                // 0-th rh_major is the replicate dimension
                if constexpr(rh_major == 0)
                {
                    constexpr index_t adaptor_hidden_id =
                        DstrDetail::rh_major_minor_to_adaptor_hidden_idss_[rh_major][rh_minor];

                    // fill in
                    rs_idx(rh_minor) = dummy_adaptor_coord.GetHiddenIndex()[adaptor_hidden_id];
                }
            });
        });

        return rs_idx;
    }
#endif

    __host__ __device__ static constexpr auto GetDistributedSpans()
    {
        constexpr auto distributed_spans_impl = DstrEncode::Detail::distributed_spans_lengthss_;
        constexpr auto ndims_spans_minor      = DstrEncode::Detail::ndims_distributed_spans_minor_;

        return generate_tuple(
            [&](auto i) {
                constexpr auto span_impl          = distributed_spans_impl[i];
                constexpr index_t ndim_span_minor = ndims_spans_minor[i];

                constexpr auto span = TO_SEQUENCE(span_impl, ndim_span_minor);

                return detail::make_tile_distributed_span(span);
            },
            Number<NDimX>{});
    }

    // FIXME: it's hacky to get Y index from Distributed-Index
    template <typename DistributedIndices>
    __host__ __device__ static constexpr auto GetYIndicesFromDistributedIndices(DistributedIndices)
    {
        constexpr auto ys_idx_arr = [] {
            Array<index_t, NDimY> ys_idx;

            static_for<0, NDimY, 1>{}([&](auto i) {
                constexpr index_t span_major = DstrEncode::Detail::ys_to_span_major_[i];
                constexpr index_t span_minor = DstrEncode::Detail::ys_to_span_minor_[i];

                constexpr auto dstr_index = DistributedIndices{}[Number<span_major>{}];

                ys_idx(i) = dstr_index.impl_[span_minor];
            });

            return ys_idx;
        }();

        constexpr index_t ndim_y = NDimY;

        return TO_SEQUENCE(ys_idx_arr, ndim_y);
    }

    __host__ __device__ static constexpr bool IsStatic()
    {
        return PsYs2XsAdaptor::IsStatic() && Ys2DDescriptor::IsStatic();
    }

    __host__ __device__ void Print() const
    {
        printf("TileDistribution{");
        //
        printf("StaticTileDistributionEncoding: ");
        print(DstrEncode{});
        printf(", ");
        //
        printf("ps_ys_to_xs_: ");
        print(ps_ys_to_xs_);
        printf(", ");
        //
        printf("ys_to_d_: ");
        print(ys_to_d_);
        //
        printf("}");
    }
};

namespace detail {

template <index_t NDimMax>
__host__ __device__ constexpr auto make_sequential_index(index_t ibegin, index_t iend)
{
    Array<index_t, NDimMax> arr{0};

    for(index_t i = 0; i < iend - ibegin; ++i)
    {
        arr(i) = ibegin + i;
    }

    return arr;
}

// this returns a constexpr encoding of TileDistribution
template <typename StaticTileDistributionEncoding_>
__host__ __device__ constexpr auto
    make_adaptor_encoding_for_tile_distribution(StaticTileDistributionEncoding_)
{
    using RsLengths    = typename StaticTileDistributionEncoding_::RsLengths;
    using HsLengthss   = typename StaticTileDistributionEncoding_::HsLengthss;
    using Ps2RHssMajor = typename StaticTileDistributionEncoding_::Ps2RHssMajor;
    using Ps2RHssMinor = typename StaticTileDistributionEncoding_::Ps2RHssMinor;
    using Ys2RHsMajor  = typename StaticTileDistributionEncoding_::Ys2RHsMajor;
    using Ys2RHsMinor  = typename StaticTileDistributionEncoding_::Ys2RHsMinor;

    // FIXME: increase max value if fail
    constexpr index_t kMaxNumTransforms = 20;
    constexpr index_t kMaxMetaDataSize  = 128;
    constexpr index_t kMaxNumDim        = 10;

    using Name     = IndexTransformEnum;
    using MetaData = MetaDataBuffer<kMaxMetaDataSize>;
    using NumDim   = index_t;
    using Dims     = Array<index_t, kMaxNumDim>;
    using Lengths  = Array<index_t, kMaxNumDim>;

    // Tile Adaptor
    //   bottom dims [x0, x1, x2, ...]
    //   top dims [p0, p1, ..., y0, y1, ...]
    constexpr index_t ndim_x = HsLengthss::Size();

    // Dim Ids: [idim_x_major, idim_x_minor] to [idim_hidden]
    Array<Array<index_t, kMaxNumDim>, ndim_x + 1> rh_major_minor_to_hidden_ids;
    Array<Array<index_t, kMaxNumDim>, ndim_x + 1> rh_major_minor_to_hidden_lengths;

    auto trans = Array<Tuple<Name, MetaData, NumDim, Dims, NumDim, Dims>, kMaxNumTransforms>{};

    index_t num_tran       = 0;
    index_t hidden_dim_cnt = ndim_x;

    // this is Replicate transform
    {
        constexpr index_t ndim_r_minor = RsLengths::Size();

        constexpr auto r_minor_lengths = RsLengths{};

        trans(num_tran++) = {
            IndexTransformEnum::Replicate,
            MetaData{to_array<index_t, ndim_r_minor>(r_minor_lengths)},
            NumDim{0},
            Dims{},
            NumDim{ndim_r_minor},
            make_sequential_index<kMaxNumDim>(hidden_dim_cnt, hidden_dim_cnt + ndim_r_minor)};

        for(index_t i = 0; i < ndim_r_minor; ++i)
        {
            rh_major_minor_to_hidden_ids(0)(i)     = hidden_dim_cnt;
            rh_major_minor_to_hidden_lengths(0)(i) = r_minor_lengths[i];

            hidden_dim_cnt++;
        }
    };

    // these are Unmerge transforms for X dimesions
    static_for<0, ndim_x, 1>{}([&trans,
                                &num_tran,
                                &hidden_dim_cnt,
                                &rh_major_minor_to_hidden_ids,
                                &rh_major_minor_to_hidden_lengths](auto idim_x) {
        constexpr auto h_minor_lengths = tuple_element_t<idim_x, HsLengthss>{};

        constexpr index_t ndim_h_minor = h_minor_lengths.Size();

        trans(num_tran++) = {
            IndexTransformEnum::UnMerge,
            MetaData{to_array<index_t, ndim_h_minor>(h_minor_lengths)},
            NumDim{1},
            Dims{idim_x},
            NumDim{ndim_h_minor},
            make_sequential_index<kMaxNumDim>(hidden_dim_cnt, hidden_dim_cnt + ndim_h_minor)};

        for(index_t i = 0; i < ndim_h_minor; ++i)
        {
            rh_major_minor_to_hidden_ids(idim_x + 1)(i)     = hidden_dim_cnt;
            rh_major_minor_to_hidden_lengths(idim_x + 1)(i) = h_minor_lengths[i];

            hidden_dim_cnt++;
        }
    });

    // transform: P dimensions
    constexpr index_t ndim_p = Ps2RHssMajor::Size();

    Dims hidden_dim_id_ps;

    static_for<0, ndim_p, 1>{}([&](auto iDimP) {
        //
        index_t hidden_dim_id_p = hidden_dim_cnt++;

        hidden_dim_id_ps(iDimP) = hidden_dim_id_p;

        constexpr auto p2RHsMajor = Ps2RHssMajor{}[iDimP];
        constexpr auto p2RHsMinor = Ps2RHssMinor{}[iDimP];

        static_assert(p2RHsMajor.Size() == p2RHsMinor.Size(), "wrong!");

        constexpr index_t ndim_low = p2RHsMajor.Size();

        Dims low_dims;
        Lengths low_lengths;

        for(index_t i = 0; i < ndim_low; ++i)
        {
            index_t rh_major = p2RHsMajor[i];
            index_t rh_minor = p2RHsMinor[i];
            low_dims(i)      = rh_major_minor_to_hidden_ids[rh_major][rh_minor];
            low_lengths(i)   = rh_major_minor_to_hidden_lengths[rh_major][rh_minor];
        }

        trans(num_tran++) = {IndexTransformEnum::Merge,
                             MetaData{to_array<index_t, ndim_low>(low_lengths)},
                             NumDim{ndim_low},
                             low_dims,
                             NumDim{1},
                             Dims{hidden_dim_id_p}};
    });

    constexpr index_t ndim_bottom = ndim_x;

    constexpr auto bottom_dim_ids = make_sequential_index<kMaxNumDim>(0, ndim_bottom);

    constexpr auto ys_to_rhs_major = Ys2RHsMajor{};
    constexpr auto ys_to_rhs_minor = Ys2RHsMinor{};

    constexpr index_t ndim_y   = Ys2RHsMajor::Size();
    constexpr index_t ndim_top = ndim_p + ndim_y;

    auto top_dim_ids = hidden_dim_id_ps;

    {
        for(index_t i = 0; i < ndim_y; ++i)
        {
            index_t rh_major        = ys_to_rhs_major[i];
            index_t rh_minor        = ys_to_rhs_minor[i];
            top_dim_ids(ndim_p + i) = rh_major_minor_to_hidden_ids[rh_major][rh_minor];
        }
    }

    //
    const auto ps_ys_to_xs_adaptor_encoding =
        make_tuple(trans, num_tran, bottom_dim_ids, ndim_bottom, top_dim_ids, ndim_top);

    // descriptor: [y0, y1, ...] to [d]
    Lengths y_lengths;
    index_t d_length = 1;

    for(index_t i = 0; i < ndim_y; ++i)
    {
        index_t rh_major = ys_to_rhs_major[i];
        index_t rh_minor = ys_to_rhs_minor[i];
        index_t y_length = rh_major_minor_to_hidden_lengths[rh_major][rh_minor];
        y_lengths(i)     = y_length;
        d_length *= y_length;
    }

    auto tran = make_tuple(IndexTransformEnum::UnMerge,
                           MetaData{to_array<index_t, ndim_y>(y_lengths)},
                           NumDim{1},
                           Dims{0},
                           NumDim{ndim_y},
                           make_sequential_index<kMaxNumDim>(1, ndim_y + 1));

    const auto ys_to_d_adaptor_encoding = make_tuple(
        make_tuple(tran), 1, Dims{0}, 1, make_sequential_index<kMaxNumDim>(1, ndim_y + 1), ndim_y);

    return make_tuple(ps_ys_to_xs_adaptor_encoding,
                      ys_to_d_adaptor_encoding,
                      d_length,
                      rh_major_minor_to_hidden_ids);
}

// FIXME: this is nasty. Need to find another way to hold this info
template <typename RhMajorMinor2AdaptorHiddenIdss> // Tuple<Sequence<...>, ...>
struct TileDistributionDetail
{
    static constexpr auto rh_major_minor_to_adaptor_hidden_idss_ =
        to_array_of_array(RhMajorMinor2AdaptorHiddenIdss{});
};

} // namespace detail

// this returns a constexpr TileDistribution
template <typename StaticTileDistributionEncoding_>
__host__ __device__ constexpr auto make_tile_distribution(StaticTileDistributionEncoding_)
{
    using DstrEncode = remove_cvref_t<StaticTileDistributionEncoding_>;

    constexpr auto adaptor_impl =
        detail::make_adaptor_encoding_for_tile_distribution(StaticTileDistributionEncoding_{});

    constexpr auto ps_ys_to_xs_adaptor_impl          = adaptor_impl.template At<0>();
    constexpr auto ys_to_d_adaptor_impl              = adaptor_impl.template At<1>();
    constexpr index_t d_length                       = adaptor_impl.template At<2>();
    constexpr auto rh_major_minor_to_hidden_ids_impl = adaptor_impl.template At<3>();

    constexpr auto ps_ys_to_xs_adaptor =
        CONSTRUCT_TENSOR_ADAPTOR_FROM_ENCODING(ps_ys_to_xs_adaptor_impl);

    constexpr auto ys_to_d_adaptor = CONSTRUCT_TENSOR_ADAPTOR_FROM_ENCODING(ys_to_d_adaptor_impl);

    constexpr auto ys_to_d_descriptor =
        make_tensor_descriptor_from_adaptor(ys_to_d_adaptor, d_length);

    //
    constexpr index_t ndim_rh_major = DstrEncode::Detail::ndim_rh_major_;
    constexpr auto ndims_rhs_minor  = DstrEncode::Detail::ndims_rhs_minor_;

    constexpr auto rh_major_minor_to_hidden_ids =
        TO_TUPLE_OF_SEQUENCE(rh_major_minor_to_hidden_ids_impl, ndim_rh_major, ndims_rhs_minor);

    return TileDistribution<
        remove_cvref_t<decltype(ps_ys_to_xs_adaptor)>,
        remove_cvref_t<decltype(ys_to_d_descriptor)>,
        remove_cvref_t<DstrEncode>,
        detail::TileDistributionDetail<remove_cvref_t<decltype(rh_major_minor_to_hidden_ids)>>>{
        ps_ys_to_xs_adaptor, ys_to_d_descriptor};
}

// this returns a static TileDistribution
template <typename StaticTileDistributionEncoding_>
__host__ __device__ constexpr auto make_static_tile_distribution(StaticTileDistributionEncoding_)
{
    using DstrEncode = remove_cvref_t<StaticTileDistributionEncoding_>;

    constexpr auto adaptor_impl =
        detail::make_adaptor_encoding_for_tile_distribution(StaticTileDistributionEncoding_{});

    constexpr auto ps_ys_to_xs_adaptor_impl          = adaptor_impl.template At<0>();
    constexpr auto ys_to_d_adaptor_impl              = adaptor_impl.template At<1>();
    constexpr index_t d_length                       = adaptor_impl.template At<2>();
    constexpr auto rh_major_minor_to_hidden_ids_impl = adaptor_impl.template At<3>();

    constexpr auto ps_ys_to_xs_adaptor =
        CONSTRUCT_STATIC_TENSOR_ADAPTOR_FROM_ENCODING(ps_ys_to_xs_adaptor_impl);

    constexpr auto ys_to_d_adaptor =
        CONSTRUCT_STATIC_TENSOR_ADAPTOR_FROM_ENCODING(ys_to_d_adaptor_impl);

    constexpr auto ys_to_d_descriptor =
        make_tensor_descriptor_from_adaptor(ys_to_d_adaptor, Number<d_length>{});

    //
    constexpr index_t ndim_rh_major = DstrEncode::Detail::ndim_rh_major_;
    constexpr auto ndims_rhs_minor  = DstrEncode::Detail::ndims_rhs_minor_;

    constexpr auto rh_major_minor_to_hidden_ids =
        TO_TUPLE_OF_SEQUENCE(rh_major_minor_to_hidden_ids_impl, ndim_rh_major, ndims_rhs_minor);

    return TileDistribution<
        remove_cvref_t<decltype(ps_ys_to_xs_adaptor)>,
        remove_cvref_t<decltype(ys_to_d_descriptor)>,
        remove_cvref_t<DstrEncode>,
        detail::TileDistributionDetail<remove_cvref_t<decltype(rh_major_minor_to_hidden_ids)>>>{
        ps_ys_to_xs_adaptor, ys_to_d_descriptor};
}

} // namespace tile_program
} // namespace ck