/home/docs/checkouts/readthedocs.org/user_builds/advanced-micro-devices-composable-kernel/checkouts/docs-7.0.2/include/ck_tile/ops/flatmm/block/flatmm_32x512x128_1x4x1_16x16x32.hpp Source File

/home/docs/checkouts/readthedocs.org/user_builds/advanced-micro-devices-composable-kernel/checkouts/docs-7.0.2/include/ck_tile/ops/flatmm/block/flatmm_32x512x128_1x4x1_16x16x32.hpp Source File#

Composable Kernel: /home/docs/checkouts/readthedocs.org/user_builds/advanced-micro-devices-composable-kernel/checkouts/docs-7.0.2/include/ck_tile/ops/flatmm/block/flatmm_32x512x128_1x4x1_16x16x32.hpp Source File
Go to the documentation of this file.
 // 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/gemm/warp/warp_gemm.hpp"
 #include "ck_tile/ops/flatmm/block/flatmm_uk_config.hpp"
  
 namespace ck_tile {
  
 // A async load to LDS, B direct to AGPR
 // B matrix preshuffled in br*kr*w
 // require 4 wave, occupancy=1c
 // agpr useage:256
 // vgpr usage:64(A local) + 64(acc) + 8(os_a) + 8(os_b) = 144 (rem:112)
 //
 // for this gemm, 4 16x16x16 transposed layout
 //  input A vpgpr layout
 //   v0-v15: [ 0:15](gemm_m)x128(gemm_k)
 //  v16-v31: [16:31](gemm_m)x128(gemm_k)
  
 //  input B vpgpr layout
 //   v0-v15: [  0: 15](gemm_n)x128(gemm_k)
 //  v16-v31: [ 64: 79](gemm_n)x128(gemm_k)
 //  ......................
 //  v111-v127: [448:463](gemm_n)x128(gemm_k)
  
 //  output C vpgpr layout
 //   v0-v3 : [ 0:15](gemm_m)x[ 0: 15](gemm_n)
 //   v4-v7 : [16:31](gemm_m)x[ 0: 15](gemm_n)
 //   v8-v11: [ 0:15](gemm_m)x[64: 79](gemm_n)
 //  v12-v15: [16:31](gemm_m)x[64: 79](gemm_n)
 //  ......................
 //  v56-v59: [ 0:15](gemm_m)x[448:463](gemm_n)
 //  v60-v63: [16:31](gemm_m)x[448:463](gemm_n)
 struct Flatmm_32x512x128_1x4x1_16x16x32_Base // for f16/bf16
 {
     static constexpr index_t Block_M = 32;
     static constexpr index_t Block_N = 512;
     static constexpr index_t Block_K = 128;
  
     static constexpr index_t WarpPerBlock_M = 1;
     static constexpr index_t WarpPerBlock_N = 4;
     static constexpr index_t WarpPerBlock_K = 1;
  
     static constexpr index_t NumWarps = 4;
  
     static constexpr index_t Warp_M = 16;
     static constexpr index_t Warp_N = 16;
     static constexpr index_t Warp_K = 32; // 16 * SubKPacks
  
     static constexpr index_t BlockSize = 256;
  
     static constexpr index_t SubKPacks = 2; // this is used to gurantee every threads can do dwordx4
  
     // TODO: note Nr/Kr/W need consider SubKPacks
     static constexpr index_t Block_W  = Warp_N * Warp_K;  // 512 element
     static constexpr index_t Block_Nr = Block_N / Warp_N; // 32 element, 4 per wave
     static constexpr index_t Block_Kr = Block_K / Warp_K; // 4
  
     static constexpr index_t Repeat_M = Block_M / (Warp_M * WarpPerBlock_M); // 2
     static constexpr index_t Repeat_N = Block_N / (Warp_N * WarpPerBlock_N); // 8
     static constexpr index_t Repeat_K = Block_K / (Warp_K * WarpPerBlock_K); // 8/2=4
  
     static CK_TILE_DEVICE constexpr auto MakeCBlockDist()
     {
         constexpr auto c_block_outer_dstr_encoding = tile_distribution_encoding<
             sequence<>,
             tuple<sequence<Repeat_M, WarpPerBlock_M>, sequence<Repeat_N, WarpPerBlock_N>>,
             tuple<sequence<1, 2>>,
             tuple<sequence<1, 1>>,
             sequence<2, 1>, // !! note here is different
             sequence<0, 0>>{};
  
         using WG = WarpGemmMfmaF16F16F32M16N16K32TransposedCDistribution;
  
         constexpr auto c_block_dstr_encode = detail::make_embed_tile_distribution_encoding(
             c_block_outer_dstr_encoding, typename WG::CWarpDstrEncoding{});
         constexpr auto c_block_dstr = make_static_tile_distribution(c_block_dstr_encode);
         return c_block_dstr;
     }
  
     static CK_TILE_DEVICE constexpr auto MakeCBlockTile()
     {
         using CDataType             = float;
         constexpr auto c_block_dstr = MakeCBlockDist();
         auto c_block_tensor         = make_static_distributed_tensor<CDataType>(c_block_dstr);
         return c_block_tensor;
     }
  
     CK_TILE_HOST_DEVICE static constexpr auto MakeLdsStoreDesc_A()
     {
         // A async->LDS
         // constexpr index_t Block_M = Problem::BlockShape::Block_M0;
         // constexpr index_t Block_K = Problem::BlockShape::Block_K0;
         // constexpr index_t BlockSize = Problem::BlockShape::BlockSize;
         constexpr index_t WarpSize = ck_tile::get_warp_size();
         // constexpr index_t NumWarps = Problem::BlockShape::NumWarps;
  
         constexpr index_t KPack_  = 8;      // GetSmemKPack_A<Problem>(); // LDS
         constexpr index_t KVector = 2;      // GetAlignment_A<Problem>(); // async copy 1 dword
         constexpr index_t KPad    = KPack_; // pad between warps
  
         static_assert(Block_K % KVector == 0);
         constexpr index_t LanesPerK = Block_K / KVector; // how many thread loading K
         if constexpr(LanesPerK >= WarpSize)
         {
             // need multiple waves to load K
             static_assert(LanesPerK % WarpSize == 0);
             constexpr index_t wavesPerK = LanesPerK / WarpSize;
             if constexpr(wavesPerK > NumWarps)
             {
                 // TODO: need multiple issues along K to load all data
             }
             else
             {
                 constexpr index_t wavesPerM     = NumWarps / wavesPerK;
                 constexpr index_t NumIssues     = Block_M / wavesPerM;
                 constexpr auto lds_block_desc_0 = make_naive_tensor_descriptor(
                     make_tuple(number<NumIssues>{},                             // m0
                                number<wavesPerM>{},                             // m1
                                number<wavesPerK>{},                             // k0
                                number<WarpSize>{},                              // k1
                                number<KVector>{}),                              // k2
                     make_tuple(number<NumWarps*(WarpSize * KVector + KPad)>{},  // m0
                                number<wavesPerK*(WarpSize * KVector + KPad)>{}, // m1
                                number<WarpSize * KVector + KPad>{},             // k0
                                number<KVector>{},                               // k1
                                number<1>{}),                                    // k2
                     number<KVector>{}, // lds store vector(actually no explicit store)
                     number<1>{});
  
                 constexpr auto lds_block_desc_issues_warps_lanes = transform_tensor_descriptor(
                     lds_block_desc_0,
                     make_tuple(
                         make_pass_through_transform(number<NumIssues>{}),
                         make_merge_transform(make_tuple(number<wavesPerM>{}, number<wavesPerK>{})),
                         make_merge_transform(make_tuple(number<WarpSize>{}, number<KVector>{}))),
                     make_tuple(sequence<0>{}, sequence<1, 2>{}, sequence<3, 4>{}),
                     make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}));
  
                 return lds_block_desc_issues_warps_lanes;
             }
         }
         else
         {
             // lanes within a wave load different M but same K
             static_assert(WarpSize % LanesPerK == 0);
             constexpr index_t LaneGroups = WarpSize / LanesPerK; // along m
             constexpr index_t NumIssues  = Block_M / (LaneGroups * NumWarps);
  
             constexpr auto lds_block_desc_0 = make_naive_tensor_descriptor(
                 make_tuple(number<NumIssues>{},                            // m0
                            number<LaneGroups>{},                           // m1
                            number<NumWarps>{},                             // m2
                            number<LanesPerK>{},                            // k0
                            number<KVector>{}),                             // k1
                 make_tuple(number<NumWarps*(WarpSize * KVector + KPad)>{}, // m0
                            number<Block_K>{},                              // m1
                            number<WarpSize * KVector + KPad>{},            // m2
                            number<KVector>{},                              // k0
                            number<1>{}),                                   // k1
                 number<KVector>{}, // lds store vector(actually no explicit store)
                 number<1>{});
  
             constexpr auto lds_block_desc_issues_warps_lanes = transform_tensor_descriptor(
                 lds_block_desc_0,
                 make_tuple(make_pass_through_transform(number<NumIssues>{}),
                            make_pass_through_transform(number<NumWarps>{}),
                            make_merge_transform(make_tuple(
                                number<LaneGroups>{}, number<LanesPerK>{}, number<KVector>{}))),
                 make_tuple(sequence<0>{}, sequence<2>{}, sequence<1, 3, 4>{}),
                 make_tuple(sequence<0>{}, sequence<1>{}, sequence<2>{}));
  
             return lds_block_desc_issues_warps_lanes;
         }
     }
  
     // template <typename Problem>
     CK_TILE_HOST_DEVICE static constexpr auto MakeLdsLoadDesc_A()
     {
         // load from LDS to register, every wave has same layout
         constexpr index_t KPack_ = 8;      // GetSmemKPack_A<Problem>(); // LDS
         constexpr index_t KPad   = KPack_; // pad between warps
  
         constexpr index_t kAMLane     = 16;
         constexpr index_t kABKLane    = 4;
         constexpr index_t kABKPerLane = 4;
         constexpr index_t kKIter      = 2;
         static_assert(KPack_ == (kABKPerLane * kKIter));
  
         constexpr auto lds_block_desc_0 =
             make_naive_tensor_descriptor(make_tuple(number<Repeat_M>{}, // m0 y
                                                     number<kAMLane>{},  // m1 p
                                                     number<Repeat_K>{}, // k0 y
                                                     number<kABKLane>{}, // k1 p
                                                     number<KPack_>{}),  // k2 y-vector
                                          make_tuple(number<kAMLane*(Block_K + KPad)>{}, // m0
                                                     number<Block_K + KPad>{},           // m1
                                                     number<kABKLane * KPack_>{},        // k0
                                                     number<KPack_>{},                   // k1
                                                     number<1>{}),                       // k2
                                          number<KPack_>{}, // lds load vector
                                          number<1>{});
  
         constexpr auto lds_desc_m_k = transform_tensor_descriptor(
             lds_block_desc_0,
             make_tuple(make_merge_transform(make_tuple(number<Repeat_M>{}, number<kAMLane>{})),
                        make_merge_transform(
                            make_tuple(number<Repeat_K>{}, number<kABKLane>{}, number<KPack_>{}))),
             make_tuple(sequence<0, 1>{}, sequence<2, 3, 4>{}),
             make_tuple(sequence<0>{}, sequence<1>{}));
  
         return lds_desc_m_k;
     }
  
     static constexpr auto GetGemm_AWarpEnc()
     {
         constexpr index_t kAMLane     = 16;
         constexpr index_t kABKLane    = 4;
         constexpr index_t kABKPerLane = 4;
         constexpr index_t kKIter      = 2;
  
         using enc_ = tile_distribution_encoding<
             sequence<>,
             tuple<sequence<kAMLane>, sequence<kABKLane, kABKPerLane * kKIter>>,
             tuple<sequence<2, 1>>,
             tuple<sequence<0, 0>>,
             sequence<2>,
             sequence<1>>;
         return enc_{};
     }
  
     CK_TILE_HOST_DEVICE static constexpr ck_tile::index_t GetSmemSize()
     {
         // return 32 * (128 + 8) * sizeof(bf16_t);
         return MakeLdsLoadDesc_A().get_element_space_size() * sizeof(bf16_t) * 2; // 2 lds buffers
     }
 };
  
 // clang-format off
 #define _EXPAND_ASM_ARGS_OUT_ONE_ACC        \
             [s_loop_cnt]"+s"(loop_cnt),     \
                 [v_acc_0]"+v"(v_acc[0]),    \
                 [v_acc_1]"+v"(v_acc[1]),    \
                 [v_acc_2]"+v"(v_acc[2]),    \
                 [v_acc_3]"+v"(v_acc[3]),    \
                 [v_acc_4]"+v"(v_acc[4]),    \
                 [v_acc_5]"+v"(v_acc[5]),    \
                 [v_acc_6]"+v"(v_acc[6]),    \
                 [v_acc_7]"+v"(v_acc[7]),    \
                 [v_acc_8]"+v"(v_acc[8]),    \
                 [v_acc_9]"+v"(v_acc[9]),    \
                 [v_acc_10]"+v"(v_acc[10]),    \
                 [v_acc_11]"+v"(v_acc[11]),    \
                 [v_acc_12]"+v"(v_acc[12]),    \
                 [v_acc_13]"+v"(v_acc[13]),    \
                 [v_acc_14]"+v"(v_acc[14]),    \
                 [v_acc_15]"+v"(v_acc[15]),    \
                 [s_mem_]"+r"(smem)
  
 #define _EXPAND_ASM_ARGS_OUT_TWO_ACC        \
             [s_loop_cnt]"+s"(loop_cnt),     \
                 [v_acc_0]"+v"(v_acc[0]),    \
                 [v_acc_1]"+v"(v_acc[1]),    \
                 [v_acc_2]"+v"(v_acc[2]),    \
                 [v_acc_3]"+v"(v_acc[3]),    \
                 [v_acc_4]"+v"(v_acc[4]),    \
                 [v_acc_5]"+v"(v_acc[5]),    \
                 [v_acc_6]"+v"(v_acc[6]),    \
                 [v_acc_7]"+v"(v_acc[7]),    \
                 [v_acc_8]"+v"(v_acc[8]),    \
                 [v_acc_9]"+v"(v_acc[9]),    \
                 [v_acc_10]"+v"(v_acc[10]),    \
                 [v_acc_11]"+v"(v_acc[11]),    \
                 [v_acc_12]"+v"(v_acc[12]),    \
                 [v_acc_13]"+v"(v_acc[13]),    \
                 [v_acc_14]"+v"(v_acc[14]),    \
                 [v_acc_15]"+v"(v_acc[15]),    \
                 [v_acc_16]"+v"(v_acc[16]),    \
                 [v_acc_17]"+v"(v_acc[17]),    \
                 [v_acc_18]"+v"(v_acc[18]),    \
                 [v_acc_19]"+v"(v_acc[19]),    \
                 [v_acc_20]"+v"(v_acc[20]),    \
                 [v_acc_21]"+v"(v_acc[21]),    \
                 [v_acc_22]"+v"(v_acc[22]),    \
                 [v_acc_23]"+v"(v_acc[23]),    \
                 [v_acc_24]"+v"(v_acc[24]),    \
                 [v_acc_25]"+v"(v_acc[25]),    \
                 [v_acc_26]"+v"(v_acc[26]),    \
                 [v_acc_27]"+v"(v_acc[27]),    \
                 [v_acc_28]"+v"(v_acc[28]),    \
                 [v_acc_29]"+v"(v_acc[29]),    \
                 [v_acc_30]"+v"(v_acc[30]),    \
                 [v_acc_31]"+v"(v_acc[31]),    \
                 [s_mem_]"+r"(smem)
  
 #define _EXPAND_ASM_ARGS_IN     \
               [s_res_a0]"s"(res_a[0]),    \
                 [s_res_a1]"s"(res_a[1]),    \
                 [s_res_a2]"s"(res_a[2]),    \
                 [s_res_a3]"s"(res_a[3]),    \
                 [s_res_b0]"s"(res_b[0]),    \
                 [s_res_b1]"s"(res_b[1]),    \
                 [s_res_b2]"s"(res_b[2]),    \
                 [s_res_b3]"s"(res_b[3]),    \
                 [v_os_a0]"v"(static_cast<index_t>(cached_coords_a[number<0>{}] * sizeof(ADataType))),    \
                 [v_os_a1]"v"(static_cast<index_t>(cached_coords_a[number<1>{}] * sizeof(ADataType))),    \
                 [v_os_a2]"v"(static_cast<index_t>(cached_coords_a[number<2>{}] * sizeof(ADataType))),    \
                 [v_os_a3]"v"(static_cast<index_t>(cached_coords_a[number<3>{}] * sizeof(ADataType))),    \
                 [v_os_a4]"v"(static_cast<index_t>(cached_coords_a[number<4>{}] * sizeof(ADataType))),    \
                 [v_os_a5]"v"(static_cast<index_t>(cached_coords_a[number<5>{}] * sizeof(ADataType))),    \
                 [v_os_a6]"v"(static_cast<index_t>(cached_coords_a[number<6>{}] * sizeof(ADataType))),    \
                 [v_os_a7]"v"(static_cast<index_t>(cached_coords_a[number<7>{}] * sizeof(ADataType))),    \
                                                                                                         \
                 [v_os_b0]"v"(static_cast<index_t>(cached_coords_b[number<0>{}] * sizeof(BDataType))),    \
                 [v_os_b1]"v"(static_cast<index_t>(cached_coords_b[number<1>{}] * sizeof(BDataType))),    \
                 [v_os_b2]"v"(static_cast<index_t>(cached_coords_b[number<2>{}] * sizeof(BDataType))),    \
                 [v_os_b3]"v"(static_cast<index_t>(cached_coords_b[number<3>{}] * sizeof(BDataType))),    \
                 [v_os_b4]"v"(static_cast<index_t>(cached_coords_b[number<4>{}] * sizeof(BDataType))),    \
                 [v_os_b5]"v"(static_cast<index_t>(cached_coords_b[number<5>{}] * sizeof(BDataType))),    \
                 [v_os_b6]"v"(static_cast<index_t>(cached_coords_b[number<6>{}] * sizeof(BDataType))),    \
                 [v_os_b7]"v"(static_cast<index_t>(cached_coords_b[number<7>{}] * sizeof(BDataType))),    \
                                                                                                             \
                 [v_os_slda]"v"(static_cast<index_t>(a_sld.cached_coords_[number<0>{}].get_offset() * sizeof(ADataType))),\
                 [s_m0_init]"s"(m0_init_value),    \
                 [s_size_per_issue]"s"(size_per_issue),    \
                 [smem_sz]"n"(smem_buf_size),   \
                 [sld_os_0]"n"(sld_os[number<0>{}].value),    \
                 [sld_os_1]"n"(sld_os[number<1>{}].value),    \
                 [sld_os_2]"n"(sld_os[number<2>{}].value),    \
                 [sld_os_3]"n"(sld_os[number<3>{}].value),    \
                 [sld_os_4]"n"(sld_os[number<4>{}].value),    \
                 [sld_os_5]"n"(sld_os[number<5>{}].value),    \
                 [sld_os_6]"n"(sld_os[number<6>{}].value),    \
                 [sld_os_7]"n"(sld_os[number<7>{}].value),    \
                 [s_tile_os_a]"s"(tile_offset_a_bytes),    \
                 [s_tile_os_b]"s"(tile_offset_b_bytes)
  
 #define _EXPAND_ASM_ARGS_CLOBBER     \
           "memory", "a0", "a1", "a2", "a3", "a4", "a5", "a6", "a7", "a8", "a9",    \
           "a10", "a11", "a12", "a13", "a14", "a15", "a16", "a17", "a18", "a19",    \
           "a20", "a21", "a22", "a23", "a24", "a25", "a26", "a27", "a28", "a29",    \
           "a30", "a31", "a32", "a33", "a34", "a35", "a36", "a37", "a38", "a39",    \
           "a40", "a41", "a42", "a43", "a44", "a45", "a46", "a47", "a48", "a49",    \
           "a50", "a51", "a52", "a53", "a54", "a55", "a56", "a57", "a58", "a59",    \
           "a60", "a61", "a62", "a63", "a64", "a65", "a66", "a67", "a68", "a69",    \
           "a70", "a71", "a72", "a73", "a74", "a75", "a76", "a77", "a78", "a79",    \
           "a80", "a81", "a82", "a83", "a84", "a85", "a86", "a87", "a88", "a89",    \
           "a90", "a91", "a92", "a93", "a94", "a95", "a96", "a97", "a98", "a99",    \
           "a100", "a101", "a102", "a103", "a104", "a105", "a106", "a107",    \
           "a108", "a109", "a110", "a111", "a112", "a113", "a114", "a115",    \
           "a116", "a117", "a118", "a119", "a120", "a121", "a122", "a123",    \
           "a124", "a125", "a126", "a127", "a128", "a129", "a130", "a131",    \
           "a132", "a133", "a134", "a135", "a136", "a137", "a138", "a139",    \
           "a140", "a141", "a142", "a143", "a144", "a145", "a146", "a147",    \
           "a148", "a149", "a150", "a151", "a152", "a153", "a154", "a155",    \
           "a156", "a157", "a158", "a159", "a160", "a161", "a162", "a163",    \
           "a164", "a165", "a166", "a167", "a168", "a169", "a170", "a171",    \
           "a172", "a173", "a174", "a175", "a176", "a177", "a178", "a179",    \
           "a180", "a181", "a182", "a183", "a184", "a185", "a186", "a187",    \
           "a188", "a189", "a190", "a191", "a192", "a193", "a194", "a195",    \
           "a196", "a197", "a198", "a199", "a200", "a201", "a202", "a203",    \
           "a204", "a205", "a206", "a207", "a208", "a209", "a210", "a211",    \
           "a212", "a213", "a214", "a215", "a216", "a217", "a218", "a219",    \
           "a220", "a221", "a222", "a223", "a224", "a225", "a226", "a227",    \
           "a228", "a229", "a230", "a231", "a232", "a233", "a234", "a235",    \
           "a236", "a237", "a238", "a239", "a240", "a241", "a242", "a243",    \
           "a244", "a245", "a246", "a247", "a248", "a249", "a250", "a251",    \
           "a252", "a253", "a254", "a255",     \
           "s16", "s17", "s18", "s19", "s20", "s21", "s22", "s23",    \
           "s86",                         \
           "v64", "v65", "v66", "v67", "v68", "v69",                 \
           "v70", "v71", "v72", "v73", "v74", "v75", "v76", "v77", "v78", "v79",     \
           "v80", "v81", "v82", "v83", "v84", "v85", "v86", "v87", "v88", "v89",    \
           "v90", "v91", "v92", "v93", "v94", "v95", "v96", "v97", "v98", "v99",    \
           "v100", "v101", "v102", "v103", "v104", "v105", "v106", "v107",    \
           "v108", "v109", "v110", "v111", "v112", "v113", "v114", "v115",    \
           "v116", "v117", "v118", "v119", "v120", "v121", "v122", "v123",    \
           "v124", "v125", "v126", "v127"
 // clang-format on
  
 struct Flatmm_32x512x128_1x4x1_16x16x32_BF16 : public Flatmm_32x512x128_1x4x1_16x16x32_Base
 {
     using ADataType = bf16_t;
     using BDataType = bf16_t;
  
     // TODO: need paired with tile_window_linear!
     // TODO: need call init_raw() before call this function!
     // Is2B: originally for B matrix we have 2 prefetch buffers. If set this to true
     // we can support A matric serve 2 B matrix, B0/B1, each B0/B1 still have same tile size
     template <typename ARes, typename ACoords, typename BRes, typename BCoords, bool Is2B = false>
     CK_TILE_DEVICE auto
     operator()(const ARes& res_a,
                const ACoords& cached_coords_a,
                const BRes& res_b,
                const BCoords& cached_coords_b,
                CK_TILE_LDS_ADDR void* smem,
                index_t k,
                index_t tile_offset_a, // for each tile, the offset to move for each unroll
                index_t tile_offset_b,
                bool_constant<Is2B> = {}) // for each tile, the offset to move for each unroll
     {
         static_assert(ACoords::size() == Block_M * Block_K / BlockSize / 2 /*2x per dword*/); // 8
         static_assert(BCoords::size() == Repeat_N);
  
         auto a_sst = make_tile_window(
             make_tensor_view<address_space_enum::lds>(
                 reinterpret_cast<CK_TILE_LDS_ADDR ADataType*>(smem), MakeLdsStoreDesc_A()),
             MakeLdsStoreDesc_A().get_lengths(),
             {0, 0, 0});
  
         auto a_sld = [&]() {
             constexpr auto a_warp_enc_      = GetGemm_AWarpEnc();
             constexpr auto a_outer_dstr_enc = tile_distribution_encoding<
                 sequence<WarpPerBlock_N>,
                 tuple<sequence<Repeat_M, WarpPerBlock_M>, sequence<Repeat_K>>,
                 tuple<sequence<1, 0>>,
                 tuple<sequence<1, 0>>,
                 sequence<1, 2>,
                 sequence<0, 0>>{};
             constexpr auto a_block_dstr_encode =
                 detail::make_embed_tile_distribution_encoding(a_outer_dstr_enc, a_warp_enc_);
             return make_tile_window_linear(
                 make_tensor_view<address_space_enum::lds>(
                     reinterpret_cast<CK_TILE_LDS_ADDR ADataType*>(smem), MakeLdsLoadDesc_A()),
                 MakeLdsLoadDesc_A().get_lengths(),
                 {0, 0},
                 make_static_tile_distribution(a_block_dstr_encode));
         }();
  
         const index_t tile_offset_a_bytes = tile_offset_a * sizeof(ADataType);
         const index_t tile_offset_b_bytes = tile_offset_b * sizeof(BDataType);
  
         const auto [m0_init_value, size_per_issue] = get_async_store_smem_info(a_sst);
         constexpr auto smem_buf_size =
             MakeLdsLoadDesc_A().get_element_space_size() * sizeof(ADataType);
         static_assert(a_sld.get_num_of_access() == 8);
         constexpr auto sld_os = generate_tuple(
             [&](auto i_access) {
                 return number<a_sld.get_bottom_linear_offset(i_access) * sizeof(ADataType)>{};
             },
             number<a_sld.get_num_of_access()>{});
  
         index_t loop_cnt = k / Block_K;
  
         if constexpr(Is2B)
         {
             // this is the acc thread buffer
             fp32x4_t v_acc[32]{.0f};
  
             // B nr->kr
 #pragma clang diagnostic push
 #pragma clang diagnostic ignored "-Winline-asm"
             // clang-format off
             asm volatile(
 #define CK_TILE_FLATMM_UK_MFMA CK_TILE_FLATMM_UK_MFMA_BF16
 #define CK_TILE_FLATMM_UK_2B 1
 #include "uk/flatmm_uk_gfx9_32x512x128_1x1x1_16x16x16.inc"
                 : _EXPAND_ASM_ARGS_OUT_TWO_ACC
                 : _EXPAND_ASM_ARGS_IN, 
                     [s_res_b4]"s"(res_b[4]), 
                     [s_res_b5]"s"(res_b[5]),
                     [s_res_b6]"s"(res_b[6]),
                     [s_res_b7]"s"(res_b[7])
                 : _EXPAND_ASM_ARGS_CLOBBER, "s24", "s25", "s26", "s27"
             );
             // clang-format on
 #pragma clang diagnostic pop
  
             // return local scratch
             auto c = make_tuple(MakeCBlockTile(), MakeCBlockTile());
             for(auto i = 0; i < 16; i++)
             {
                 c.at(number<0>{}).get_thread_buffer()[4 * i + 0] = v_acc[i].x;
                 c.at(number<0>{}).get_thread_buffer()[4 * i + 1] = v_acc[i].y;
                 c.at(number<0>{}).get_thread_buffer()[4 * i + 2] = v_acc[i].z;
                 c.at(number<0>{}).get_thread_buffer()[4 * i + 3] = v_acc[i].w;
             }
             for(auto i = 0; i < 16; i++)
             {
                 c.at(number<1>{}).get_thread_buffer()[4 * i + 0] = v_acc[16 + i].x;
                 c.at(number<1>{}).get_thread_buffer()[4 * i + 1] = v_acc[16 + i].y;
                 c.at(number<1>{}).get_thread_buffer()[4 * i + 2] = v_acc[16 + i].z;
                 c.at(number<1>{}).get_thread_buffer()[4 * i + 3] = v_acc[16 + i].w;
             }
             return c;
         }
         else
         {
             // this is the acc thread buffer
             fp32x4_t v_acc[16]{.0f};
  
             // B nr->kr
 #pragma clang diagnostic push
 #pragma clang diagnostic ignored "-Winline-asm"
             // clang-format off
             asm volatile(
 #define CK_TILE_FLATMM_UK_MFMA CK_TILE_FLATMM_UK_MFMA_BF16
 #include "uk/flatmm_uk_gfx9_32x512x128_1x1x1_16x16x16.inc"
                 : _EXPAND_ASM_ARGS_OUT_ONE_ACC
                 : _EXPAND_ASM_ARGS_IN
                 : _EXPAND_ASM_ARGS_CLOBBER
             );
             // clang-format on
 #pragma clang diagnostic pop
  
             // return local scratch
             auto c = MakeCBlockTile();
             for(auto i = 0; i < 16; i++)
             {
                 c.get_thread_buffer()[4 * i + 0] = v_acc[i].x;
                 c.get_thread_buffer()[4 * i + 1] = v_acc[i].y;
                 c.get_thread_buffer()[4 * i + 2] = v_acc[i].z;
                 c.get_thread_buffer()[4 * i + 3] = v_acc[i].w;
             }
             return c;
         }
     }
 };
  
 struct Flatmm_32x512x128_1x4x1_16x16x32_FP16 : public Flatmm_32x512x128_1x4x1_16x16x32_Base
 {
     using ADataType = fp16_t;
     using BDataType = fp16_t;
  
     // TODO: need paired with tile_window_linear!
     // TODO: need call init_raw() before call this function!
     template <typename ARes, typename ACoords, typename BRes, typename BCoords, bool Is2B = false>
     CK_TILE_DEVICE auto
     operator()(const ARes& res_a,
                const ACoords& cached_coords_a,
                const BRes& res_b,
                const BCoords& cached_coords_b,
                CK_TILE_LDS_ADDR void* smem,
                index_t k,
                index_t tile_offset_a, // for each tile, the offset to move for each unroll
                index_t tile_offset_b, // for each tile, the offset to move for each unroll
                bool_constant<Is2B> = {})
     {
         static_assert(ACoords::size() == Block_M * Block_K / BlockSize / 2 /*2x per dword*/); // 8
         static_assert(BCoords::size() == Repeat_N);
  
         auto a_sst = make_tile_window(
             make_tensor_view<address_space_enum::lds>(
                 reinterpret_cast<CK_TILE_LDS_ADDR ADataType*>(smem), MakeLdsStoreDesc_A()),
             MakeLdsStoreDesc_A().get_lengths(),
             {0, 0, 0});
  
         auto a_sld = [&]() {
             constexpr auto a_warp_enc_      = GetGemm_AWarpEnc();
             constexpr auto a_outer_dstr_enc = tile_distribution_encoding<
                 sequence<WarpPerBlock_N>,
                 tuple<sequence<Repeat_M, WarpPerBlock_M>, sequence<Repeat_K>>,
                 tuple<sequence<1, 0>>,
                 tuple<sequence<1, 0>>,
                 sequence<1, 2>,
                 sequence<0, 0>>{};
             constexpr auto a_block_dstr_encode =
                 detail::make_embed_tile_distribution_encoding(a_outer_dstr_enc, a_warp_enc_);
             return make_tile_window_linear(
                 make_tensor_view<address_space_enum::lds>(
                     reinterpret_cast<CK_TILE_LDS_ADDR ADataType*>(smem), MakeLdsLoadDesc_A()),
                 MakeLdsLoadDesc_A().get_lengths(),
                 {0, 0},
                 make_static_tile_distribution(a_block_dstr_encode));
         }();
  
         const index_t tile_offset_a_bytes = tile_offset_a * sizeof(ADataType);
         const index_t tile_offset_b_bytes = tile_offset_b * sizeof(BDataType);
  
         const auto [m0_init_value, size_per_issue] = get_async_store_smem_info(a_sst);
         constexpr auto smem_buf_size =
             MakeLdsLoadDesc_A().get_element_space_size() * sizeof(ADataType);
         static_assert(a_sld.get_num_of_access() == 8);
         constexpr auto sld_os = generate_tuple(
             [&](auto i_access) {
                 return number<a_sld.get_bottom_linear_offset(i_access) * sizeof(ADataType)>{};
             },
             number<a_sld.get_num_of_access()>{});
  
         index_t loop_cnt = k / Block_K;
  
         if constexpr(Is2B)
         {
             // this is the acc thread buffer
             fp32x4_t v_acc[32]{.0f};
  
             // B nr->kr
 #pragma clang diagnostic push
 #pragma clang diagnostic ignored "-Winline-asm"
             // clang-format off
             asm volatile(
 #define CK_TILE_FLATMM_UK_MFMA CK_TILE_FLATMM_UK_MFMA_FP16
 #define CK_TILE_FLATMM_UK_2B 1
 #include "uk/flatmm_uk_gfx9_32x512x128_1x1x1_16x16x16.inc"
                 : _EXPAND_ASM_ARGS_OUT_TWO_ACC
                 : _EXPAND_ASM_ARGS_IN, 
                     [s_res_b4]"s"(res_b[4]), 
                     [s_res_b5]"s"(res_b[5]),
                     [s_res_b6]"s"(res_b[6]),
                     [s_res_b7]"s"(res_b[7])
                 : _EXPAND_ASM_ARGS_CLOBBER, "s24", "s25", "s26", "s27"
             );
             // clang-format on
 #pragma clang diagnostic pop
  
             // return local scratch
             auto c = make_tuple(MakeCBlockTile(), MakeCBlockTile());
             for(auto i = 0; i < 16; i++)
             {
                 c.at(number<0>{}).get_thread_buffer()[4 * i + 0] = v_acc[i].x;
                 c.at(number<0>{}).get_thread_buffer()[4 * i + 1] = v_acc[i].y;
                 c.at(number<0>{}).get_thread_buffer()[4 * i + 2] = v_acc[i].z;
                 c.at(number<0>{}).get_thread_buffer()[4 * i + 3] = v_acc[i].w;
             }
             for(auto i = 0; i < 16; i++)
             {
                 c.at(number<1>{}).get_thread_buffer()[4 * i + 0] = v_acc[16 + i].x;
                 c.at(number<1>{}).get_thread_buffer()[4 * i + 1] = v_acc[16 + i].y;
                 c.at(number<1>{}).get_thread_buffer()[4 * i + 2] = v_acc[16 + i].z;
                 c.at(number<1>{}).get_thread_buffer()[4 * i + 3] = v_acc[16 + i].w;
             }
             return c;
         }
         else
         {
             // this is the acc thread buffer
             fp32x4_t v_acc[16]{.0f};
  
             // B nr->kr
 #pragma clang diagnostic push
 #pragma clang diagnostic ignored "-Winline-asm"
             // clang-format off
             asm volatile(
 #define CK_TILE_FLATMM_UK_MFMA CK_TILE_FLATMM_UK_MFMA_FP16
 #include "uk/flatmm_uk_gfx9_32x512x128_1x1x1_16x16x16.inc"
                 : _EXPAND_ASM_ARGS_OUT_ONE_ACC
                 : _EXPAND_ASM_ARGS_IN
                 : _EXPAND_ASM_ARGS_CLOBBER
             );
             // clang-format on
 #pragma clang diagnostic pop
  
             // return local scratch
             auto c = MakeCBlockTile();
             for(auto i = 0; i < 16; i++)
             {
                 c.get_thread_buffer()[4 * i + 0] = v_acc[i].x;
                 c.get_thread_buffer()[4 * i + 1] = v_acc[i].y;
                 c.get_thread_buffer()[4 * i + 2] = v_acc[i].z;
                 c.get_thread_buffer()[4 * i + 3] = v_acc[i].w;
             }
             return c;
         }
     }
 };
 #undef _EXPAND_ASM_ARGS_OUT_ONE_ACC
 #undef _EXPAND_ASM_ARGS_OUT_TWO_ACC
 #undef _EXPAND_ASM_ARGS_IN
 #undef _EXPAND_ASM_ARGS_CLOBBER
 } // namespace ck_tile