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Unverified Commit c8517e46 authored by jakpiase's avatar jakpiase Committed by GitHub
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Merge branch 'develop' into jakpiase/ck_tile_examples_package

parents 17aa1102 c0adab48
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Showing with 936 additions and 71 deletions
example/ck_tile/13_moe_sorting/moe_sorting.cpp
View file @ c8517e46
......@@ -26,6 +26,10 @@ auto create_args(int argc, char* argv[])
.insert("k", "4", "topk")
.insert("unit", "32", "unit_size")
.insert("moe_buf_size", "0", "moe_buf_size")
.insert("local_eid",
"-1",
"a list of experts enabled as local expert. e.g. \"0,1,4,5\"\n"
"please make sure eid is in ascending order!")
.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")
......@@ -74,6 +78,7 @@ bool test_moe_sorting(ck_tile::ArgParser args)
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);
......@@ -90,6 +95,30 @@ bool test_moe_sorting(ck_tile::ArgParser args)
return false;
}
bool local_expert_masking = args.get_str("local_eid") != "-1";
auto local_expert_masking_host = [&]() {
if(local_expert_masking)
{
auto local_eid = args.get_int_vec("local_eid");
// std::vector<int> v_ {num_experts, 0};
ck_tile::HostTensor<IndexType> v_{{num_experts}};
v_.SetZero();
for(auto eid : local_eid)
{
if(eid >= num_experts)
{
throw std::runtime_error(
"local_eid larger than number of expert, please check");
}
v_.mData[eid] = 1;
}
return v_;
}
else
// return std::vector<int>{};
return ck_tile::HostTensor<IndexType>{{1}};
}();
// 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});
......@@ -111,6 +140,8 @@ bool test_moe_sorting(ck_tile::ArgParser args)
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());
ck_tile::DeviceMem local_expert_masking_dev(
local_expert_masking_host.get_element_space_size_in_bytes());
topk_ids_dev.ToDevice(topk_ids_host.data());
weights_dev.ToDevice(weights_host.data());
......@@ -118,11 +149,15 @@ bool test_moe_sorting(ck_tile::ArgParser args)
{
moe_buf_dev.ToDevice(moe_buf_host.data());
}
if(local_expert_masking)
local_expert_masking_dev.ToDevice(local_expert_masking_host.data());
moe_sorting_trait trait{index_prec, weight_prec};
moe_sorting_trait trait{index_prec, weight_prec, local_expert_masking};
moe_sorting_args karg{topk_ids_dev.GetDeviceBuffer(),
weights_dev.GetDeviceBuffer(),
local_expert_masking ? local_expert_masking_dev.GetDeviceBuffer()
: nullptr,
sorted_ids_dev.GetDeviceBuffer(),
sorted_weights_dev.GetDeviceBuffer(),
sorted_expert_ids_dev.GetDeviceBuffer(),
......@@ -140,15 +175,22 @@ bool test_moe_sorting(ck_tile::ArgParser args)
warmup,
repeat};
auto ms = moe_sorting(trait, karg, sc);
printf("[%s|%s]tokens:%d, num_experts:%d, topk:%d, ms:%f , ",
printf("[%s|%s]tokens:%d, num_experts:%d, topk:%d, ",
index_prec.c_str(),
weight_prec.c_str(),
tokens,
num_experts,
topk,
ms);
topk);
if(local_expert_masking)
{
printf("local_eid:%s, ", args.get_str("local_eid").c_str());
}
if(ms < 0)
printf("not supported\n");
else
printf("ms:%f, ", ms);
fflush(stdout);
if(ms < 0)
{
......@@ -174,12 +216,14 @@ bool test_moe_sorting(ck_tile::ArgParser args)
int32_t ref_total_tokens_post_pad = 0;
ck_tile::reference_moe_sorting<WeightType, IndexType>(topk_ids_host,
weights_host,
local_expert_masking_host,
sorted_ids_ref,
sorted_weights_ref,
sorted_expert_ids_ref,
ref_total_tokens_post_pad,
num_experts,
unit_size);
unit_size,
local_expert_masking);
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,
......@@ -199,9 +243,16 @@ bool test_moe_sorting(ck_tile::ArgParser args)
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("total_tokens_post_pad:%d(%d), ",
ref_total_tokens_post_pad,
sorted_id_cnt_host.mData[0]);
}
printf("valid:%s\n", rtn ? "y" : "n");
printf("valid:%s", rtn ? "y" : "n");
fflush(stdout);
if(!rtn)
printf(", (%d)", seed);
printf("\n");
fflush(stdout);
return rtn;
}
......
example/ck_tile/13_moe_sorting/moe_sorting_api.cpp
View file @ c8517e46
......@@ -3,6 +3,12 @@
#include "moe_sorting_api.hpp"
#ifndef MOE_SORTING_USE_EX_KERNEL
#define MOE_SORTING_USE_EX_KERNEL 1
#endif
#if !MOE_SORTING_USE_EX_KERNEL
#define MOE_SORTING_DISPATCH_ETILE(unroll_num_, expert_tile_) \
constexpr ck_tile::index_t unroll_num = unroll_num_; \
constexpr ck_tile::index_t expert_tile = expert_tile_; \
......@@ -17,6 +23,67 @@
s, ck_tile::make_kernel(kernel{}, grids, blocks, lds_bytes, kargs)); \
return ave_time;
#else
#define MOE_SORTING_DISPATCH_(sub_token_tile_, sub_token_onshot_, local_expert_masking_) \
constexpr ck_tile::index_t sub_token_tile = sub_token_tile_; \
constexpr bool sub_token_onshot = sub_token_onshot_; \
constexpr bool local_expert_masking = local_expert_masking_; \
using ms_problem = ck_tile::MoeSortingProblemEx<index_t, \
ms_weight_type, \
sub_token_tile, \
sub_token_onshot, \
local_expert_masking>; \
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;
#define MOE_SORTING_DISPATCH_SUB_TOKEN_(row_, sub_token_onshot_, local_expert_masking_) \
if(row_ % 8 == 0) \
{ \
MOE_SORTING_DISPATCH_(8, sub_token_onshot_, local_expert_masking_); \
} \
else if(row_ % 4 == 0) \
{ \
MOE_SORTING_DISPATCH_(4, sub_token_onshot_, local_expert_masking_); \
} \
else if(row_ % 2 == 0) \
{ \
MOE_SORTING_DISPATCH_(2, sub_token_onshot_, local_expert_masking_); \
} \
else \
{ \
MOE_SORTING_DISPATCH_(1, sub_token_onshot_, local_expert_masking_); \
}
#define MOE_SORTING_DISPATCH_SUBTO_(row_, local_expert_masking_) \
if(is_sub_token_onshot) \
{ \
MOE_SORTING_DISPATCH_SUB_TOKEN_(row_, true, local_expert_masking_) \
} \
else \
{ \
MOE_SORTING_DISPATCH_SUB_TOKEN_(row_, false, local_expert_masking_) \
}
#define MOE_SORTING_DISPATCH_EMASK_(row_) \
if(is_local_expert_masking) \
{ \
MOE_SORTING_DISPATCH_SUBTO_(row_, true) \
} \
else \
{ \
MOE_SORTING_DISPATCH_SUBTO_(row_, false) \
}
#endif
#if !MOE_SORTING_USE_EX_KERNEL
#define MOE_SORTING_DISPATCH(unroll_num_) \
if(a.num_experts <= 8) \
{ \
......@@ -38,11 +105,13 @@
{ \
MOE_SORTING_DISPATCH_ETILE(unroll_num_, 0) \
}
#endif
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 !MOE_SORTING_USE_EX_KERNEL
if(a.num_experts > 127)
{
printf("lds size exceed, only support experts <127 \n");
......@@ -83,6 +152,19 @@ float moe_sorting(moe_sorting_trait t, moe_sorting_args a, ck_tile::stream_confi
MOE_SORTING_DISPATCH(4);
}
}
#else
using index_t = ck_tile::index_t;
using ms_weight_type = float;
auto [r_, c_] = ck_tile::moe_sorting_get_smem_row_col(a.tokens, a.num_experts);
auto sub_token_ = r_ - 2;
r_ = (r_ - 2) / 8;
bool is_sub_token_onshot = a.tokens <= sub_token_;
bool is_local_expert_masking = t.local_expert_masking;
(void)c_;
MOE_SORTING_DISPATCH_EMASK_(r_);
// MOE_SORTING_DISPATCH_ETILE(0, 0);
#endif
}
return -1;
}
example/ck_tile/13_moe_sorting/moe_sorting_api.hpp
View file @ c8517e46
......@@ -10,7 +10,8 @@
struct moe_sorting_trait
{
std::string index_type;
std::string weight_type; // currently always float
std::string weight_type; // currently always float
bool local_expert_masking; // if mask experts as local expert
};
struct moe_sorting_args : public ck_tile::MoeSortingHostArgs
......
example/ck_tile/13_moe_sorting/script/smoke_test.sh
View file @ c8517e46
......@@ -17,4 +17,12 @@ $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
$EXE -t=11 -e=256 -k=5
$EXE -t=64 -e=455 -k=8
$EXE -t=777 -e=802 -k=99
$EXE -t=4097 -e=906 -k=51
$EXE -t=128 -e=32 -k=5 -moe_buf_size=262144
$EXE -t=13 -e=64 -k=3 -local_eid=4,5,6,7,8,9,10,11
$EXE -t=99 -e=33 -k=9 -local_eid=6,10,11,15,19
$EXE -t=80 -e=99 -k=10 -local_eid=0,8,12,33
$EXE -t=11 -e=256 -k=5 -local_eid=99,110,129
example/ck_tile/15_fused_moe/README.md
View file @ c8517e46
......@@ -42,7 +42,7 @@ summary of the key design of this fused-moe operator:
// (only for reference) exp-0 exp-1 exp-2 exp-3 exp-4 exp-5
// weight_id_per_expert is: [[a], [g, j, m], [d, k], [b, e, h, l, n], [], [c, f, i, o]]
//
// max_num_tokens_padded : topk * input_tokens + num_experts * (M_a - 1)
// max_num_tokens_padded : topk * input_tokens + num_experts * M_a - topk (updated)
// * this could be larger than actual, since actual tokens are on GPU
//
// sorted_token_ids_ptr : [0, 6, 6, 6, 2, 3, 4, 6, 1, 3, 6, 6, 0, 1, 2, 3, 4, 6, 6, 6, 6, 6, 6, 6, 0, 1, 2, 5]
......
example/ck_tile/15_fused_moe/instances/fused_moesorting_api.cpp
View file @ c8517e46
......@@ -3,6 +3,12 @@
#include "fused_moesorting.hpp"
#ifndef MOE_SORTING_USE_EX_KERNEL
#define MOE_SORTING_USE_EX_KERNEL 1
#endif
#if !MOE_SORTING_USE_EX_KERNEL
#define MOE_SORTING_DISPATCH_ETILE(unroll_num_, expert_tile_) \
constexpr ck_tile::index_t unroll_num = unroll_num_; \
constexpr ck_tile::index_t expert_tile = expert_tile_; \
......@@ -17,6 +23,24 @@
s, ck_tile::make_kernel(kernel{}, grids, blocks, lds_bytes, kargs)); \
return ave_time;
#else
#define MOE_SORTING_DISPATCH_(sub_token_tile_, sub_token_onshot_) \
constexpr ck_tile::index_t sub_token_tile = sub_token_tile_; \
constexpr bool sub_token_onshot = sub_token_onshot_; \
using ms_problem = \
ck_tile::MoeSortingProblemEx<index_t, ms_weight_type, sub_token_tile, sub_token_onshot>; \
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;
#endif
#if !MOE_SORTING_USE_EX_KERNEL
#define MOE_SORTING_DISPATCH(unroll_num_) \
if(a.num_experts <= 8) \
{ \
......@@ -38,11 +62,13 @@
{ \
MOE_SORTING_DISPATCH_ETILE(unroll_num_, 0) \
}
#endif
float fused_moesorting(fused_moesorting_trait t, fused_moesorting_args a, ck_tile::stream_config s)
{
if(t.weight_type == "fp32" && t.index_type == "int32")
{
#if !MOE_SORTING_USE_EX_KERNEL
if(a.num_experts > 127)
{
printf("lds size exceed, only support experts <127 \n");
......@@ -83,6 +109,54 @@ float fused_moesorting(fused_moesorting_trait t, fused_moesorting_args a, ck_til
MOE_SORTING_DISPATCH(4);
}
}
#else
using index_t = ck_tile::index_t;
using ms_weight_type = float;
auto [r_, c_] = ck_tile::moe_sorting_get_smem_row_col(a.tokens, a.num_experts);
auto sub_token_ = r_ - 2;
r_ = (r_ - 2) / 8;
bool is_sub_token_onshot = a.tokens <= sub_token_;
(void)c_;
if(is_sub_token_onshot)
{
if(r_ % 8 == 0)
{
MOE_SORTING_DISPATCH_(8, true);
}
else if(r_ % 4 == 0)
{
MOE_SORTING_DISPATCH_(4, true);
}
else if(r_ % 2 == 0)
{
MOE_SORTING_DISPATCH_(2, true);
}
else
{
MOE_SORTING_DISPATCH_(1, true);
}
}
else
{
if(r_ % 8 == 0)
{
MOE_SORTING_DISPATCH_(8, false);
}
else if(r_ % 4 == 0)
{
MOE_SORTING_DISPATCH_(4, false);
}
else if(r_ % 2 == 0)
{
MOE_SORTING_DISPATCH_(2, false);
}
else
{
MOE_SORTING_DISPATCH_(1, false);
}
}
// MOE_SORTING_DISPATCH_ETILE(0, 0);
#endif
}
return -1;
}
include/ck_tile/host/reference/reference_moe_sorting.hpp
View file @ c8517e46
......@@ -14,12 +14,15 @@ 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,
const HostTensor<IndexType>& local_expert_mask,
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 unit_size,
bool local_expert_masking,
bool skip_experts_with_zero_token = true)
{
const index_t num_token = topk_ids.mDesc.get_lengths()[0];
const index_t topk = topk_ids.mDesc.get_lengths()[1];
......@@ -33,8 +36,11 @@ CK_TILE_HOST void reference_moe_sorting(const HostTensor<IndexType>& topk_ids,
#endif
std::vector<std::vector<WeightType>> expert_token_weights(
experts, std::vector<WeightType>(unit_size, 0));
// count number of unit-size slices in this expert
std::vector<IndexType> expert_slices(experts, 1);
// count the tokens used in this expert
std::vector<IndexType> expert_slice_idxs(experts, 0);
// TODO: above 2 buffer seems duplicated
for(index_t t = 0; t < num_token; t++)
{
......@@ -72,8 +78,23 @@ CK_TILE_HOST void reference_moe_sorting(const HostTensor<IndexType>& topk_ids,
IndexType* out_tokens = p_sorted_token_ids.data();
WeightType* out_weights = sorted_weight.data();
IndexType* out_expert_id = sorted_expert_ids.data();
int curr_expert_id = 0;
for(index_t e = 0; e < experts; e++)
{
if(local_expert_masking)
{
if(local_expert_mask(e) == 0)
continue;
}
if(skip_experts_with_zero_token)
{
if(expert_slice_idxs[e] == 0)
{
curr_expert_id++;
continue;
}
}
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,
......@@ -83,10 +104,11 @@ CK_TILE_HOST void reference_moe_sorting(const HostTensor<IndexType>& topk_ids,
for(index_t s = 0; s < expert_slices[e]; s++)
{
out_expert_id[s] = e;
out_expert_id[s] = curr_expert_id;
unit_cnt++;
}
out_expert_id += expert_slices[e];
curr_expert_id++;
}
unit_cnt *= unit_size;
return;
......
include/ck_tile/ops/fused_moe.hpp
View file @ c8517e46
......@@ -7,6 +7,7 @@
#include "ck_tile/ops/fused_moe/kernel/fused_moegemm_shape.hpp"
#include "ck_tile/ops/fused_moe/kernel/fused_moegemm_tile_partitioner.hpp"
#include "ck_tile/ops/fused_moe/kernel/moe_sorting_kernel.hpp"
#include "ck_tile/ops/fused_moe/kernel/moe_sorting_problem.hpp"
#include "ck_tile/ops/fused_moe/pipeline/fused_moegemm_pipeline_flatmm_ex.hpp"
#include "ck_tile/ops/fused_moe/pipeline/fused_moegemm_pipeline_flatmm_policy.hpp"
#include "ck_tile/ops/fused_moe/pipeline/fused_moegemm_pipeline_flatmm_uk.hpp"
......@@ -14,7 +15,6 @@
#include "ck_tile/ops/fused_moe/pipeline/fused_moegemm_traits.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"
#include "ck_tile/ops/common/utils.hpp"
include/ck_tile/ops/fused_moe/kernel/fused_moegemm_kernel.hpp
View file @ c8517e46
......@@ -22,7 +22,7 @@
// (only for reference) exp-0 exp-1 exp-2 exp-3 exp-4 exp-5
// weight_id_per_expert is: [[a], [g, j, m], [d, k], [b, e, h, l, n], [], [c, f, i, o]]
//
// max_num_tokens_padded : topk * input_tokens + num_experts * (M_a - 1)
// max_num_tokens_padded : topk * input_tokens + num_experts * M_a - topk (updated)
// * this could be larger than actual, since actual tokens are on GPU
//
// sorted_token_ids_ptr : [0, 6, 6, 6, 2, 3, 4, 6, 1, 3, 6, 6, 0, 1, 2, 3, 4, 6, 6, 6, 6, 6, 6, 6, 0, 1, 2, 5]
......
include/ck_tile/ops/fused_moe/pipeline/moe_sorting_problem.hpp → include/ck_tile/ops/fused_moe/kernel/moe_sorting_problem.hpp
View file @ c8517e46
......@@ -25,4 +25,28 @@ struct MoeSortingProblem
InternalLoadUnroll_; // TODO: need better design(like tile size)
static constexpr index_t ExpertTile = ExpertTile_; // TODO: only used in store out
};
template <typename IndexType_,
typename WeightType_,
index_t SubTokenTile_, // 1,2,4,8, or 0 in the future
bool SubTokenOneShot_, // if we only loop over once or not
bool LocalExpertMasking_, // used in EP case
bool SkipExpertsWithZeroTokens_ = true,
index_t ExpertTile_ = 0>
struct MoeSortingProblemEx
{
// 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 SubTokenTile = SubTokenTile_;
static constexpr bool SubTokenOneShot = SubTokenOneShot_;
static constexpr bool LocalExpertMasking = LocalExpertMasking_;
static constexpr bool SkipExpertsWithZeroTokens = SkipExpertsWithZeroTokens_;
static_assert(SubTokenTile == 1 || SubTokenTile == 2 || SubTokenTile == 4 || SubTokenTile == 8);
static constexpr index_t ExpertTile = ExpertTile_; // TODO: only used in store out
};
} // namespace ck_tile
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