Ck tile/moe sorting (#1624)

* add moe_sorting & check ok

* fix comments & typo

* Run remod.py under include/ck_tile & example/ck_tile directories

* format codes

* fix output ci check bug

* fix moe sorting readme and error commit file

* use magiv div to accelerate compute

* add an loop unroll for moe lds ops

* add extblocksnel to set zeros for moebufs

* [Ck_tile] moe set zero run ok, add size check and fix ref check

* [Ck_tile]fix moe_sorting fuse set_zero remod

* [Ck_tile] change name style, fix zero buffer size err, change folder

* [Ck_tile] moe_sorting: fix name style

* [Ck_tile] moe_sorting, remove useless params in traits

* [Ck_tile] change outputtile cnt * unit_size; change output buf alloc

---------
Co-authored-by: dummycoderfe <noplydummmycoder@163.com>
Co-authored-by: Po Yen, Chen <PoYen.Chen@amd.com>
Co-authored-by: carlushuang <carlus.huang@amd.com>

example/ck_tile/13_moe_sorting/CMakeLists.txt

+add_executable(tile_example_moe_sorting EXCLUDE_FROM_ALL moe_sorting.cpp moe_sorting_api.cpp)
+target_include_directories(tile_example_moe_sorting PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/)
+
+set(EXAMPLE_MOE_SORTING_COMPILE_OPTIONS)
+# NOTE: we turn off undefined-func-template to let source compile without explicit declare function specializations
+list(APPEND EXAMPLE_MOE_SORTING_COMPILE_OPTIONS -Wno-undefined-func-template -Wno-float-equal)
+# list(APPEND EXAMPLE_MOE_SORTING_COMPILE_OPTIONS -v --save-temps -Wno-gnu-line-marker)
+target_compile_options(tile_example_moe_sorting PRIVATE ${EXAMPLE_MOE_SORTING_COMPILE_OPTIONS})

example/ck_tile/13_moe_sorting/README.md

+# moe-sorting
+
+This folder contains example for moe-sorting kernel using ck_tile tile-programming implementation. This kernel is often used in Moe model, before launching the fused-moe-gemm block. The input&weight is a `token*topk` 2d matrix. The op rearange the input weight ids into different experts and feed into fuse moe gemm kernel.
+
+## build
+```
+# in the root of ck_tile
+mkdir build && cd build
+sh ../script/cmake-ck-dev.sh  ../ <arch>  # you can replace this <arch> to gfx90a, gfx942...
+make tile_example_moe_sorting -j
+```
+This will result in an executable `build/bin/tile_example_moe_sorting`
+
+## example
+```
+args:
+          -v    weather do CPU validation or not (default:1)
+       -pr_i    index data type. (currently only fp32 supported now) (default:int32)
+       -pr_w    output weight data type(currently only fp32 supported now) (default:fp32)
+          -t    number of input tokens (default:32)
+          -e    number of experts (default:8)
+          -k    topk (default:2)
+       -st_i    row stride of input, -1 means same as experts (default:-1)
+       -seed    seed to be used, -1 means random every time (default:-1)
+      -kname    when set to 1 it will print kernel name (default:0)
+
+```

example/ck_tile/13_moe_sorting/moe_sorting.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <set>
+#include <vector>
+#include <iostream>
+#include <numeric>
+#include <cassert>
+#include <cstdlib>
+#include <iostream>
+#include <time.h>
+#include <unordered_set>
+
+#include "ck_tile/core.hpp"
+#include "ck_tile/ops/reduce.hpp"
+#include "moe_sorting_api.hpp"
+
+auto create_args(int argc, char* argv[])
+{
+    ck_tile::ArgParser arg_parser;
+    arg_parser.insert("v", "1", "weather do CPU validation or not")
+        .insert("pr_i", "int32", "index data type. (currently only int32 supported now)")
+        .insert("pr_w", "fp32", "output weight data type(currently only fp32 supported now)")
+        .insert("t", "128", "number of input tokens")
+        .insert("e", "8", "number of num_experts")
+        .insert("k", "4", "topk")
+        .insert("unit", "32", "unit_size")
+        .insert("moe_buf_size", "0", "moe_buf_size")
+        .insert("seed", "-1", "seed to be used, -1 means random every time")
+        .insert("kname", "0", "when set to 1 it will print kernel name")
+        .insert("warmup", "5", "number of iterations before benchmark the kernel")
+        .insert("repeat", "20", "number of iterations to benchmark the kernel");
+
+    bool result = arg_parser.parse(argc, argv);
+    return std::make_tuple(result, arg_parser);
+}
+
+template <typename IndexType>
+void topid_unique_gen(
+    std::vector<IndexType>& host_tensor, int tokens, int topk, int num_expert, int seed)
+{
+    size_t total_size = topk * tokens;
+    std::srand(seed);
+    std::set<IndexType> unique_set;
+    IndexType current_v;
+    for(size_t i = 0; i < total_size; i++)
+    {
+        if(i % topk == 0)
+        {
+            unique_set.clear();
+        }
+        current_v = std::rand() % num_expert;
+        while(unique_set.find(current_v) != unique_set.end())
+        {
+            current_v = std::rand() % num_expert;
+        }
+        unique_set.insert(current_v);
+        host_tensor[i] = current_v;
+    }
+}
+
+template <typename WeightType, typename IndexType = ck_tile::index_t>
+bool test_moe_sorting(ck_tile::ArgParser args)
+{
+    int validate            = args.get_int("v");
+    std::string index_prec  = args.get_str("pr_i");
+    std::string weight_prec = args.get_str("pr_w");
+    int tokens              = args.get_int("t");
+    int num_experts         = args.get_int("e");
+    int topk                = args.get_int("k");
+    int seed                = args.get_int("seed");
+    int unit_size           = args.get_int("unit");
+    int moe_buf_size        = args.get_int("moe_buf_size");
+    int kname               = args.get_int("kname");
+    int warmup              = args.get_int("warmup");
+    int repeat              = args.get_int("repeat");
+    int max_output_ids =
+        ck_tile::integer_least_multiple(topk * tokens + num_experts * unit_size - topk, unit_size);
+
+    if(seed < 0)
+    {
+        seed = std::time(nullptr);
+    }
+
+    if(topk > num_experts)
+    {
+        printf("topk:%d value should be smaller than, or equal to number of num_experts:%d\n",
+               topk,
+               num_experts);
+        return false;
+    }
+
+    // tokens already considered batch size
+    ck_tile::HostTensor<IndexType> topk_ids_host({tokens, topk}, {topk, 1});
+    ck_tile::HostTensor<WeightType> weights_host({tokens, topk}, {topk, 1});
+    ck_tile::HostTensor<IndexType> sorted_ids_host({max_output_ids}, {1});
+    ck_tile::HostTensor<WeightType> sorted_weights_host({max_output_ids}, {1});
+    ck_tile::HostTensor<IndexType> sorted_expert_ids_host({max_output_ids / unit_size}, {1});
+    ck_tile::HostTensor<IndexType> sorted_id_cnt_host({1}, {1});
+    ck_tile::HostTensor<float> moe_buf_host({moe_buf_size});
+
+    ck_tile::FillUniformDistribution<WeightType>{-.5f, .5f}(weights_host);
+    ck_tile::FillUniformDistribution<WeightType>{-.5f, .5f}(moe_buf_host);
+    topid_unique_gen<IndexType>(topk_ids_host.mData, tokens, topk, num_experts, seed);
+
+    ck_tile::DeviceMem topk_ids_dev(topk_ids_host.get_element_space_size_in_bytes());
+    ck_tile::DeviceMem weights_dev(weights_host.get_element_space_size_in_bytes());
+    ck_tile::DeviceMem sorted_ids_dev(sorted_ids_host.get_element_space_size_in_bytes());
+    ck_tile::DeviceMem sorted_weights_dev(sorted_weights_host.get_element_space_size_in_bytes());
+    ck_tile::DeviceMem sorted_expert_ids_dev(
+        sorted_expert_ids_host.get_element_space_size_in_bytes());
+    ck_tile::DeviceMem sorted_id_cnt_dev(sorted_id_cnt_host.get_element_space_size_in_bytes());
+    ck_tile::DeviceMem moe_buf_dev(moe_buf_host.get_element_space_size_in_bytes());
+
+    topk_ids_dev.ToDevice(topk_ids_host.data());
+    weights_dev.ToDevice(weights_host.data());
+    if(moe_buf_size > 0)
+    {
+        moe_buf_dev.ToDevice(moe_buf_host.data());
+    }
+
+    moe_sorting_trait trait{index_prec, weight_prec};
+
+    moe_sorting_args karg{topk_ids_dev.GetDeviceBuffer(),
+                          weights_dev.GetDeviceBuffer(),
+                          sorted_ids_dev.GetDeviceBuffer(),
+                          sorted_weights_dev.GetDeviceBuffer(),
+                          sorted_expert_ids_dev.GetDeviceBuffer(),
+                          sorted_id_cnt_dev.GetDeviceBuffer(),
+                          moe_buf_size > 0 ? moe_buf_dev.GetDeviceBuffer() : nullptr,
+                          tokens,
+                          unit_size,
+                          num_experts,
+                          topk,
+                          static_cast<ck_tile::index_t>(moe_buf_size * sizeof(float))};
+
+    ck_tile::stream_config sc{nullptr,
+                              true,
+                              /* log_level = */ (kname ? 1 : 0),
+                              warmup,
+                              repeat};
+    auto ms = moe_sorting(trait, karg, sc);
+    printf("[%s|%s]tokens:%d, num_experts:%d, topk:%d,  ms:%f , ",
+           index_prec.c_str(),
+           weight_prec.c_str(),
+           tokens,
+           num_experts,
+           topk,
+           ms);
+    if(ms < 0)
+        printf("not supported\n");
+    fflush(stdout);
+    if(ms < 0)
+    {
+        return false;
+    }
+
+    sorted_ids_dev.FromDevice(sorted_ids_host.data());
+    sorted_weights_dev.FromDevice(sorted_weights_host.data());
+    sorted_expert_ids_dev.FromDevice(sorted_expert_ids_host.data());
+    sorted_id_cnt_dev.FromDevice(sorted_id_cnt_host.data());
+    if(moe_buf_size > 0)
+    {
+        moe_buf_dev.FromDevice(moe_buf_host.data());
+    }
+
+    bool rtn = true;
+    if(validate)
+    {
+        ck_tile::HostTensor<IndexType> sorted_ids_ref({max_output_ids}, {1});
+        ck_tile::HostTensor<WeightType> sorted_weights_ref({max_output_ids}, {1});
+        ck_tile::HostTensor<IndexType> sorted_expert_ids_ref({max_output_ids / unit_size}, {1});
+
+        int32_t ref_total_tokens_post_pad = 0;
+        ck_tile::reference_moe_sorting<WeightType, IndexType>(topk_ids_host,
+                                                              weights_host,
+                                                              sorted_ids_ref,
+                                                              sorted_weights_ref,
+                                                              sorted_expert_ids_ref,
+                                                              ref_total_tokens_post_pad,
+                                                              num_experts,
+                                                              unit_size);
+        rtn &= ck_tile::check_err(
+            sorted_ids_host, sorted_ids_ref, std::string("OUT Error: Incorrect ids!"), 1e-6, 1e-6);
+        rtn &= ck_tile::check_err(sorted_weights_host,
+                                  sorted_weights_ref,
+                                  std::string("OUT Error: Incorrect w!"),
+                                  1e-6,
+                                  1e-6);
+        rtn &= ck_tile::check_err(sorted_expert_ids_host,
+                                  sorted_expert_ids_ref,
+                                  std::string("OUT Error: Incorrect eid!"),
+                                  1e-6,
+                                  1e-6);
+        if(moe_buf_size)
+        {
+            ck_tile::HostTensor<WeightType> moe_buf_ref({moe_buf_size});
+            rtn &= ck_tile::check_err(
+                moe_buf_host, moe_buf_ref, std::string("OUT Error: Incorrect zero buf!"), 0, 0);
+        }
+        rtn &= ref_total_tokens_post_pad == sorted_id_cnt_host.mData[0];
+    }
+
+    printf("valid:%s\n", rtn ? "y" : "n");
+    fflush(stdout);
+    return rtn;
+}
+
+int main(int argc, char** argv)
+{
+    auto [result, args] = create_args(argc, argv);
+    if(!result)
+        return -1;
+    std::string index_prec  = args.get_str("pr_i");
+    std::string weight_prec = args.get_str("pr_w");
+
+    bool r = true;
+    if(weight_prec.compare("fp32") == 0 && index_prec.compare("int32") == 0)
+    {
+        r &= test_moe_sorting<float, ck_tile::index_t>(args);
+    }
+    return r ? 0 : -1;
+}

example/ck_tile/13_moe_sorting/moe_sorting_api.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "moe_sorting_api.hpp"
+
+#define MOE_SORTING_DISPATCH(unroll_num_)                                                   \
+    constexpr ck_tile::index_t unroll_num = unroll_num_;                                    \
+    using ms_problem     = ck_tile::MoeSortingProblem<index_t, ms_weight_type, unroll_num>; \
+    using kernel         = ck_tile::MoeSortingKernel<ms_problem>;                           \
+    auto kargs           = kernel::MakeKargs(a);                                            \
+    const dim3 grids     = kernel::GridSize(a);                                             \
+    const dim3 blocks    = kernel::BlockSize(a);                                            \
+    const auto lds_bytes = kernel::GetSmemSize(a);                                          \
+    float ave_time       = ck_tile::launch_kernel(                                          \
+        s, ck_tile::make_kernel(kernel{}, grids, blocks, lds_bytes, kargs));          \
+    return ave_time;
+
+float moe_sorting(moe_sorting_trait t, moe_sorting_args a, ck_tile::stream_config s)
+{
+    if(t.weight_type == "fp32" && t.index_type == "int32")
+    {
+        if(a.num_experts > 127)
+        {
+            printf("lds size exceed, only support experts <127 \n");
+            return -1;
+        }
+        if(a.moe_buf_bytes % 16)
+        {
+            printf("buf set size %d unaligned, must be multiple of 16\n", a.moe_buf_bytes);
+            return -1;
+        }
+        using index_t              = ck_tile::index_t;
+        using ms_weight_type       = float;
+        index_t smem_io_unroll_num = ck_tile::integer_divide_ceil(a.tokens * a.topk, 64);
+        switch(smem_io_unroll_num)
+        {
+        case(1): {
+            MOE_SORTING_DISPATCH(1);
+        }
+        case(2): {
+            MOE_SORTING_DISPATCH(2);
+        }
+        case(3): {
+            MOE_SORTING_DISPATCH(3);
+        }
+        case(5): {
+            MOE_SORTING_DISPATCH(5);
+        }
+        case(6): {
+            MOE_SORTING_DISPATCH(6);
+        }
+        case(7): {
+            MOE_SORTING_DISPATCH(7);
+        }
+        case(8): {
+            MOE_SORTING_DISPATCH(8);
+        }
+        case(9): {
+            MOE_SORTING_DISPATCH(9);
+        }
+        case(10): {
+            MOE_SORTING_DISPATCH(10);
+        }
+        case(11): {
+            MOE_SORTING_DISPATCH(11);
+        }
+        default: {
+            MOE_SORTING_DISPATCH(4);
+        }
+        }
+    }
+    return -1;
+}

example/ck_tile/13_moe_sorting/moe_sorting_api.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+#include <string>
+#include "ck_tile/core.hpp"
+#include "ck_tile/host.hpp"
+#include "ck_tile/ops/moe_sorting.hpp"
+
+struct moe_sorting_trait
+{
+    std::string index_type;
+    std::string weight_type; // currently always float
+};
+
+struct moe_sorting_args : public ck_tile::MoeSortingHostArgs
+{
+};
+
+float moe_sorting(moe_sorting_trait t, moe_sorting_args a, ck_tile::stream_config s);

example/ck_tile/13_moe_sorting/script/smoke_test.sh

+# #!/bin/sh
+
+EXE=./build/bin/tile_example_moe_sorting
+
+$EXE -t=80 -e=17 -moe_buf_size=16
+$EXE -t=111 -e=117 -moe_buf_size=4
+$EXE -t=1000 -e=55 -moe_buf_size=1024
+$EXE -t=99 -e=120  -moe_buf_size=10244
+$EXE -t=175 -e=64 -k=8
+$EXE -t=65 -e=8 -k=2
+$EXE -t=1 -e=25
+$EXE -t=31 -e=19 -k=15
+$EXE -t=81 -e=37 -k=7
+$EXE -t=23 -e=1 -k=1
+$EXE -t=127 -e=99 -k=19
+$EXE -t=71 -e=11 -k=11
+$EXE -t=1 -e=1 -k=1
+$EXE -t=99 -e=2 -k=1
+$EXE -t=333 -e=99 -k=13
\ No newline at end of file

example/ck_tile/CMakeLists.txt

@@ -12,3 +12,4 @@ add_subdirectory(09_topk_softmax)
 add_subdirectory(10_rmsnorm2d)
 add_subdirectory(11_add_rmsnorm2d_rdquant)
 add_subdirectory(12_smoothquant)
+add_subdirectory(13_moe_sorting)

include/ck_tile/host.hpp

@@ -23,6 +23,7 @@
 #include "ck_tile/host/reference/reference_gemm.hpp"
 #include "ck_tile/host/reference/reference_im2col.hpp"
 #include "ck_tile/host/reference/reference_layernorm2d_fwd.hpp"
+#include "ck_tile/host/reference/reference_moe_sorting.hpp"
 #include "ck_tile/host/reference/reference_permute.hpp"
 #include "ck_tile/host/reference/reference_reduce.hpp"
 #include "ck_tile/host/reference/reference_rmsnorm2d_fwd.hpp"

include/ck_tile/host/reference/reference_moe_sorting.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include "ck_tile/core.hpp"
+#include "ck_tile/host/host_tensor.hpp"
+
+namespace ck_tile {
+
+template <typename WeightType, typename IndexType = index_t>
+CK_TILE_HOST void reference_moe_sorting(const HostTensor<IndexType>& topk_ids,
+                                        const HostTensor<WeightType>& weights,
+                                        HostTensor<IndexType>& p_sorted_token_ids,
+                                        HostTensor<WeightType>& sorted_weight,
+                                        HostTensor<IndexType>& sorted_expert_ids,
+                                        index_t& unit_cnt,
+                                        const index_t experts,
+                                        const index_t unit_size)
+{
+    const index_t num_token = topk_ids.mDesc.get_lengths()[0];
+    const index_t topk      = topk_ids.mDesc.get_lengths()[1];
+    std::vector<std::vector<IndexType>> expert_tokens(experts,
+                                                      std::vector<IndexType>(unit_size, num_token));
+    std::vector<std::vector<WeightType>> expert_token_weights(
+        experts, std::vector<WeightType>(unit_size, 0));
+    std::vector<IndexType> expert_slices(experts, 1);
+    std::vector<IndexType> expert_slice_idxs(experts, 0);
+
+    for(index_t t = 0; t < num_token; t++)
+    {
+        for(index_t k = 0; k < topk; k++)
+        {
+            IndexType e  = topk_ids(t, k);
+            WeightType w = weights(t, k);
+            index_t idx  = expert_slice_idxs[e];
+            if(idx > expert_slices[e] * unit_size - 1)
+            {
+                expert_slices[e]++;
+                index_t new_size = expert_slices[e] * unit_size;
+                expert_tokens[e].resize(new_size);
+                expert_token_weights[e].resize(new_size);
+                for(index_t i = (expert_slices[e] - 1) * unit_size; i < new_size; i++)
+                {
+                    expert_tokens[e][i]        = num_token;
+                    expert_token_weights[e][i] = 0;
+                }
+            }
+
+            expert_tokens[e][idx]        = t;
+            expert_token_weights[e][idx] = w;
+            expert_slice_idxs[e]++;
+        }
+    }
+
+    IndexType* out_tokens    = p_sorted_token_ids.data();
+    WeightType* out_weights  = sorted_weight.data();
+    IndexType* out_expert_id = sorted_expert_ids.data();
+    for(index_t e = 0; e < experts; e++)
+    {
+        memcpy(out_tokens, expert_tokens[e].data(), sizeof(index_t) * expert_slices[e] * unit_size);
+        out_tokens += expert_slices[e] * unit_size;
+        memcpy(out_weights,
+               expert_token_weights[e].data(),
+               sizeof(WeightType) * expert_slices[e] * unit_size);
+        out_weights += expert_slices[e] * unit_size;
+
+        for(index_t s = 0; s < expert_slices[e]; s++)
+        {
+            out_expert_id[s] = e;
+            unit_cnt++;
+        }
+        out_expert_id += expert_slices[e];
+    }
+    unit_cnt *= unit_size;
+    return;
+}
+} // namespace ck_tile

include/ck_tile/ops/fused_moe/kernel/moe_sorting_kernel.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include "ck_tile/core.hpp"
+#include "ck_tile/ops/common.hpp"
+#include "ck_tile/ops/elementwise.hpp"
+#include "ck_tile/host/hip_check_error.hpp"
+#include <string>
+#include <type_traits>
+
+namespace ck_tile {
+
+struct MoeSortingHostArgs
+{
+    const void* p_topk_ids;
+    const void* p_weights;
+    void* p_sorted_token_ids;
+    void* p_sorted_weights;
+    void* p_sorted_expert_ids;
+    void* p_total_tokens_post_pad;
+    void* p_moe_buf;
+    index_t tokens;
+    index_t unit_size;
+    index_t num_experts;
+    index_t topk;
+    index_t moe_buf_bytes;
+};
+
+template <typename Problem_>
+struct MoeSortingKernel
+{
+    using Problem = remove_cvref_t<Problem_>;
+
+    using IndexType  = typename Problem::IndexType;
+    using WeightType = typename Problem::WeightType;
+
+    typedef MoeSortingHostArgs MoeSortingKargs;
+
+    using Hargs = MoeSortingHostArgs;
+
+    struct Kargs
+    {
+        const void* p_topk_ids;
+        const void* p_weights;
+        void* p_sorted_token_ids;
+        void* p_sorted_weights;
+        void* p_sorted_expert_ids;
+        void* p_total_tokens_post_pad;
+        void* p_moe_buf;
+        index_t tokens;
+        index_t num_experts;
+        index_t moe_buf_bytes;
+
+        index_t tokens_per_thread;
+        mdiv unit_size_mdiv;
+        mdiv topk_mdiv;
+    };
+
+    CK_TILE_HOST static constexpr auto GridSize(const Hargs& h)
+    {
+        // TODO: assume num-experts not too much
+        return dim3(1 + ck_tile::integer_divide_ceil(h.moe_buf_bytes, BlockSize(h).x * 16));
+    }
+
+    CK_TILE_HOST static constexpr auto BlockSize(const Hargs& h)
+    {
+        return dim3(ck_tile::integer_least_multiple(h.num_experts, ck_tile::get_warp_size()));
+    }
+
+    // in byte
+    CK_TILE_HOST static constexpr auto GetSmemSize(const Hargs& h)
+    {
+        const auto blocks = BlockSize(h);
+        return ((blocks.x + 1) * h.num_experts + (h.num_experts + 1)) * sizeof(index_t);
+    }
+
+    CK_TILE_HOST static constexpr auto MakeKargs(const Hargs& h)
+    {
+        Kargs k;
+        k.p_topk_ids              = h.p_topk_ids;
+        k.p_weights               = h.p_weights;
+        k.p_sorted_token_ids      = h.p_sorted_token_ids;
+        k.p_sorted_weights        = h.p_sorted_weights;
+        k.p_sorted_expert_ids     = h.p_sorted_expert_ids;
+        k.p_moe_buf               = h.p_moe_buf;
+        k.p_total_tokens_post_pad = h.p_total_tokens_post_pad;
+        k.tokens                  = h.tokens;
+        k.num_experts             = h.num_experts;
+        k.moe_buf_bytes           = h.moe_buf_bytes;
+
+        const auto blocks   = BlockSize(h);
+        k.tokens_per_thread = integer_divide_ceil(h.tokens * h.topk, blocks.x);
+        k.unit_size_mdiv    = mdiv{static_cast<uint32_t>(h.unit_size)};
+        k.topk_mdiv         = mdiv{static_cast<uint32_t>(h.topk)};
+        return k;
+    }
+
+    CK_TILE_DEVICE index_t calc_index(index_t total_col, index_t row, index_t col) const
+    {
+        return row * total_col + col;
+    }
+
+    CK_TILE_DEVICE void moe_buf_set_zero_kernel(uint8x16_t* buf, index_t buf_bytes) const
+    {
+        const index_t offset = (blockIdx.x - 1) * blockDim.x + threadIdx.x;
+        if(offset < buf_bytes / 16)
+        {
+            buf[offset] = uint8x16_t{0};
+        }
+    }
+
+    CK_TILE_DEVICE void moe_align_block_size_kernel(const IndexType* __restrict__ topk_id,
+                                                    const WeightType* __restrict__ weights,
+                                                    index_t* p_sorted_token_ids,
+                                                    WeightType* p_sorted_weights,
+                                                    index_t* p_sorted_expert_ids,
+                                                    index_t* p_total_tokens_post_pad,
+                                                    const index_t num_experts,
+                                                    const index_t tokens_per_thread,
+                                                    const index_t numel,
+                                                    const mdiv unit_size_mdiv,
+                                                    const mdiv topk_mdiv,
+                                                    void* smem) const
+    {
+        const index_t tid       = static_cast<index_t>(threadIdx.x);
+        const index_t start_idx = tid * tokens_per_thread;
+
+        index_t* shared_mem = reinterpret_cast<index_t*>(smem);
+
+        index_t* tokens_cnts = shared_mem; // 2d: (blockDim.x + 1, num_experts)
+        index_t* cumsum      = shared_mem + (blockDim.x + 1) * num_experts; // 1: (num_experts + 1)
+        for(int i = 0; i < num_experts; ++i)
+        {
+            tokens_cnts[calc_index(num_experts, tid + 1, i)] = 0;
+        }
+#pragma unroll Problem_::InternalLoadUnroll
+        for(int i = start_idx; i < numel && i < start_idx + tokens_per_thread; ++i)
+        {
+            ++tokens_cnts[calc_index(num_experts, tid + 1, topk_id[i])];
+        }
+        __syncthreads();
+
+        if(tid < num_experts)
+        {
+            tokens_cnts[calc_index(num_experts, 0, tid)] = 0;
+            for(int i = 1; i <= static_cast<index_t>(blockDim.x); ++i)
+            {
+                tokens_cnts[calc_index(num_experts, i, tid)] +=
+                    tokens_cnts[calc_index(num_experts, i - 1, tid)];
+            }
+        }
+
+        // __syncthreads();
+        if(tid == 0)
+        {
+            cumsum[0] = 0;
+            for(int i = 1; i <= num_experts; ++i)
+            {
+                auto current_units = [&]() {
+                    index_t x_ = tokens_cnts[calc_index(num_experts, blockDim.x, i - 1)] +
+                                 unit_size_mdiv.divisor - 1;
+                    index_t y_ = unit_size_mdiv.div(x_);
+                    return max(y_, 1) * unit_size_mdiv.divisor;
+                }();
+                cumsum[i] = cumsum[i - 1] + current_units;
+            }
+            *p_total_tokens_post_pad = cumsum[num_experts];
+        }
+        __syncthreads();
+        if(tid < num_experts)
+        {
+            for(int i = cumsum[tid]; i < cumsum[tid + 1]; i += unit_size_mdiv.divisor)
+            {
+                p_sorted_expert_ids[unit_size_mdiv.div(i)] = tid;
+            }
+        }
+
+#pragma unroll Problem_::InternalLoadUnroll
+        for(int i = start_idx; i < numel && i < start_idx + tokens_per_thread; ++i)
+        {
+            index_t expert_id = topk_id[i];
+            index_t rank_post_pad =
+                tokens_cnts[calc_index(num_experts, tid, expert_id)] + cumsum[expert_id];
+            p_sorted_token_ids[rank_post_pad] = topk_mdiv.div(i);
+            p_sorted_weights[rank_post_pad]   = weights[i];
+            ++tokens_cnts[calc_index(num_experts, tid, expert_id)];
+        }
+
+        const index_t prefill_token = topk_mdiv.div(numel);
+        if(tid < num_experts)
+        {
+            index_t expert_offset =
+                cumsum[tid] + tokens_cnts[calc_index(num_experts, blockDim.x, tid)];
+            while(expert_offset < cumsum[tid + 1])
+            {
+                p_sorted_token_ids[expert_offset] = prefill_token;
+                p_sorted_weights[expert_offset]   = static_cast<WeightType>(0.0);
+                expert_offset++;
+            }
+        }
+    }
+
+    CK_TILE_DEVICE void operator()(Kargs kargs) const
+    {
+        if(blockIdx.x > 0)
+        {
+            if(kargs.p_moe_buf)
+            {
+                moe_buf_set_zero_kernel(reinterpret_cast<uint8x16_t*>(kargs.p_moe_buf),
+                                        kargs.moe_buf_bytes);
+            }
+            return;
+        }
+        const size_t numel = kargs.tokens * kargs.topk_mdiv.divisor;
+        extern __shared__ char smem[];
+        return moe_align_block_size_kernel(static_cast<const IndexType*>(kargs.p_topk_ids),
+                                           static_cast<const WeightType*>(kargs.p_weights),
+                                           static_cast<IndexType*>(kargs.p_sorted_token_ids),
+                                           static_cast<WeightType*>(kargs.p_sorted_weights),
+                                           static_cast<IndexType*>(kargs.p_sorted_expert_ids),
+                                           static_cast<IndexType*>(kargs.p_total_tokens_post_pad),
+                                           kargs.num_experts,
+                                           kargs.tokens_per_thread,
+                                           numel,
+                                           kargs.unit_size_mdiv,
+                                           kargs.topk_mdiv,
+                                           smem);
+    }
+};
+} // namespace ck_tile

include/ck_tile/ops/fused_moe/pipeline/moe_sorting_pipeline.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include "ck_tile/core.hpp"
+#include "ck_tile/ops/fused_moe/pipeline/moe_sorting_policy.hpp"
+#include <string>
+#include <type_traits>
+
+#ifndef TOPK_SOFTMAX_USE_RAW_TILE_WINDOW
+#define TOPK_SOFTMAX_USE_RAW_TILE_WINDOW 0
+#endif
+
+namespace ck_tile {
+
+// template <typename Problem_, typename Policy_ = MoeSortingPolicy>
+// struct MoeSortingPipeline
+// {
+//     // TODO: this kernel only support warp per row
+//     using Problem    = remove_cvref_t<Problem_>;
+//     using Policy     = remove_cvref_t<Policy_>;
+//     using WeightType = typename Problem::WeightType;
+
+//     template <typename TopkIdWindow, typename WeightWindow>
+//     CK_TILE_DEVICE auto operator()(const TopkIdWindow& topk_id_window,
+//                                    const WeightWindow& weight_window,
+//                                     index_t* p_sorted_token_ids,
+//                                     WeightType* p_sorted_weights,
+//                                     index_t* p_sorted_expert_ids,
+//                                     index_t* p_total_tokens_post_pad,
+//                                     const index_t num_experts,
+//                                     const index_t unit_size,
+//                                     const size_t numel,
+//                                     const index_t topk)
+//     {
+//     }
+// };
+} // namespace ck_tile

include/ck_tile/ops/fused_moe/pipeline/moe_sorting_policy.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include "ck_tile/core.hpp"
+#include "ck_tile/ops/softmax.hpp"
+#include "ck_tile/ops/topk.hpp"
+
+namespace ck_tile {
+
+struct MoeSortingPolicy
+{
+};
+} // namespace ck_tile

include/ck_tile/ops/fused_moe/pipeline/moe_sorting_problem.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include "ck_tile/core.hpp"
+#include <string>
+#include <type_traits>
+
+namespace ck_tile {
+
+template <typename IndexType_, typename WeightType_, index_t InternalLoadUnroll_>
+struct MoeSortingProblem
+{
+    // TODO: this kernel only support warp per row
+    using WeightType = remove_cvref_t<WeightType_>;
+    using IndexType  = remove_cvref_t<IndexType_>;
+
+    static constexpr index_t WarpSize           = get_warp_size();
+    static constexpr index_t WarpsPerBlock      = 1;
+    static constexpr index_t InternalLoadUnroll = InternalLoadUnroll_;
+};
+} // namespace ck_tile

include/ck_tile/ops/moe_sorting.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include "ck_tile/ops/fused_moe/kernel/moe_sorting_kernel.hpp"
+#include "ck_tile/ops/fused_moe/pipeline/moe_sorting_pipeline.hpp"
+#include "ck_tile/ops/fused_moe/pipeline/moe_sorting_policy.hpp"
+#include "ck_tile/ops/fused_moe/pipeline/moe_sorting_problem.hpp"
+#include "ck_tile/ops/common/generic_2d_block_shape.hpp"
+#include "ck_tile/ops/common/tensor_layout.hpp"