TensorRT-LLMs/cpp/kernels/xqa/tma.h
Kanghwan 41e5870a70
[#8476][chore] Update license (#8807)
Signed-off-by: Kanghwan Jang <861393+karljang@users.noreply.github.com>
2025-11-19 15:05:25 -08:00

325 lines
13 KiB
C++

/*
* SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#pragma once
#include "cuda_hint.cuh"
#include "utils.h"
#ifndef GENERATE_CUBIN
#include <cstdint>
#include <cuda.h>
#include <cuda_runtime.h>
#endif
#include "barriers.cuh"
enum class StateSpace
{
kCONSTANT,
kPARAMETER,
kGENERIC
};
#ifdef GENERATE_CUBIN
#define CU_TENSOR_MAP_NUM_QWORDS 16
typedef struct CUtensorMap_st
{
#if defined(__cplusplus) && (__cplusplus >= 201103L)
alignas(64)
#elif __STDC_VERSION__ >= 201112L
_Alignas(64)
#endif
uint64_t opaque[CU_TENSOR_MAP_NUM_QWORDS];
} CUtensorMap;
#endif
namespace tma
{
__device__ inline void loadLinearAsync(void* dst, void const* src, uint32_t nbBytes, CtaBarrier& bar)
{
asm volatile("cp.async.bulk.shared::cta.global.mbarrier::complete_tx::bytes [%0], [%1], %2, [%3];\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(src)), "r"(nbBytes),
"l"(__cvta_generic_to_shared(&bar))
: "memory");
}
__device__ inline void prefetchLinear(void const* src, uint32_t nbBytes)
{
asm volatile("cp.async.bulk.prefetch.L2.global [%0], %1;\n" ::"l"(reinterpret_cast<uint64_t>(src)), "r"(nbBytes)
: "memory");
}
// dsr and &bar must be remote address generated by mapa and src must be local address
__device__ inline void sm2smCopyAsync(void* dst, void const* src, uint32_t nbBytes, CgaBarrier& bar)
{
asm volatile("cp.async.bulk.shared::cluster.shared::cta.mbarrier::complete_tx::bytes [%0], [%1], %2, [%3];\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(src)), "r"(nbBytes),
"l"(__cvta_generic_to_shared(&bar))
: "memory");
}
template <uint32_t nbDims>
__device__ inline void loadAsync(void* dst, CUtensorMap const& tensorMap, DimsLE<nbDims> offset, CtaBarrier& bar)
{
if constexpr (nbDims == 1)
{
// nbDims==1 does not need tensormap and should just use cp.async.bulk
asm volatile(
"cp.async.bulk.tensor.1d.shared::cta.global.mbarrier::complete_tx::bytes.tile [%0], [%1, {%2}], [%3];\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"l"(__cvta_generic_to_shared(&bar))
: "memory");
}
else if constexpr (nbDims == 2)
{
asm volatile(
"cp.async.bulk.tensor.2d.shared::cta.global.mbarrier::complete_tx::bytes.tile [%0], [%1, {%2, %3}], [%4];\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"r"(offset[1]), "l"(__cvta_generic_to_shared(&bar))
: "memory");
}
else if constexpr (nbDims == 3)
{
asm volatile(
"cp.async.bulk.tensor.3d.shared::cta.global.mbarrier::complete_tx::bytes.tile [%0], [%1, {%2, %3, %4}], "
"[%5];\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"r"(offset[1]), "r"(offset[2]), "l"(__cvta_generic_to_shared(&bar))
: "memory");
}
else if constexpr (nbDims == 4)
{
asm volatile(
"cp.async.bulk.tensor.4d.shared::cta.global.mbarrier::complete_tx::bytes.tile [%0], [%1, {%2, %3, %4, "
"%5}], [%6];\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"r"(offset[1]), "r"(offset[2]), "r"(offset[3]), "l"(__cvta_generic_to_shared(&bar))
: "memory");
}
else if constexpr (nbDims == 5)
{
asm volatile(
"cp.async.bulk.tensor.5d.shared::cta.global.mbarrier::complete_tx::bytes.tile [%0], [%1, {%2, %3, %4, %5, "
"%6}], [%7];\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"r"(offset[1]), "r"(offset[2]), "r"(offset[3]), "r"(offset[4]), "l"(__cvta_generic_to_shared(&bar))
: "memory");
}
else
{
static_assert(nbDims >= 1 && nbDims <= 5);
}
}
template <uint32_t nbDims>
__device__ inline void loadAsync(
void* dst, CUtensorMap const& tensorMap, DimsLE<nbDims> offset, CtaBarrier& bar, uint64_t cacheHint)
{
if constexpr (nbDims == 1)
{
// nbDims==1 does not need tensormap and should just use cp.async.bulk
asm volatile(
"cp.async.bulk.tensor.1d.shared::cta.global.mbarrier::complete_tx::bytes.tile.L2::cache_hint [%0], [%1, "
"{%2}], [%3], %4;\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"l"(__cvta_generic_to_shared(&bar)), "l"(cacheHint)
: "memory");
}
else if constexpr (nbDims == 2)
{
asm volatile(
"cp.async.bulk.tensor.2d.shared::cta.global.mbarrier::complete_tx::bytes.tile.L2::cache_hint [%0], [%1, "
"{%2, %3}], [%4], %5;\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"r"(offset[1]), "l"(__cvta_generic_to_shared(&bar)), "l"(cacheHint)
: "memory");
}
else if constexpr (nbDims == 3)
{
asm volatile(
"cp.async.bulk.tensor.3d.shared::cta.global.mbarrier::complete_tx::bytes.tile.L2::cache_hint [%0], [%1, "
"{%2, %3, %4}], [%5], %6;\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"r"(offset[1]), "r"(offset[2]), "l"(__cvta_generic_to_shared(&bar)), "l"(cacheHint)
: "memory");
}
else if constexpr (nbDims == 4)
{
asm volatile(
"cp.async.bulk.tensor.4d.shared::cta.global.mbarrier::complete_tx::bytes.tile.L2::cache_hint [%0], [%1, "
"{%2, %3, %4, %5}], [%6], %7;\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"r"(offset[1]), "r"(offset[2]), "r"(offset[3]), "l"(__cvta_generic_to_shared(&bar)), "l"(cacheHint)
: "memory");
}
else if constexpr (nbDims == 5)
{
asm volatile(
"cp.async.bulk.tensor.5d.shared::cta.global.mbarrier::complete_tx::bytes.tile.L2::cache_hint [%0], [%1, "
"{%2, %3, %4, %5, %6}], [%7], %8;\n"
:
: "l"(__cvta_generic_to_shared(dst)), "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]),
"r"(offset[1]), "r"(offset[2]), "r"(offset[3]), "r"(offset[4]), "l"(__cvta_generic_to_shared(&bar)),
"l"(cacheHint)
: "memory");
}
else
{
static_assert(nbDims >= 1 && nbDims <= 5);
}
}
// shared::cta -> global
__device__ inline void store1DAsync(void* dst, void const* src, uint32_t nbBytes)
{
asm volatile("cp.async.bulk.global.shared::cta.bulk_group [%0], [%1], %2;\n"
:
: "l"(reinterpret_cast<uint64_t>(dst)), "l"(__cvta_generic_to_shared(src)), "r"(nbBytes));
}
template <uint32_t nbDims>
__device__ inline void storeAsync(CUtensorMap const& tensorMap, DimsLE<nbDims> const& offset, void* src)
{
if constexpr (nbDims == 1)
{
// nbDims==1 does not need tensormap and should just use cp.async.bulk
asm volatile("cp.async.bulk.tensor.1d.global.shared::cta.bulk_group.tile [%0, {%1}], [%2];\n"
:
: "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]), "l"(__cvta_generic_to_shared(src))
: "memory");
}
else if constexpr (nbDims == 2)
{
asm volatile("cp.async.bulk.tensor.2d.global.shared::cta.bulk_group.tile [%0, {%1, %2}], [%3];\n"
:
: "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]), "r"(offset[1]),
"l"(__cvta_generic_to_shared(src))
: "memory");
}
else if constexpr (nbDims == 3)
{
asm volatile("cp.async.bulk.tensor.2d.global.shared::cta.bulk_group.tile [%0, {%1, %2, %3}], [%4];\n"
:
: "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]), "r"(offset[1]), "r"(offset[2]),
"l"(__cvta_generic_to_shared(src))
: "memory");
}
else if constexpr (nbDims == 4)
{
asm volatile("cp.async.bulk.tensor.2d.global.shared::cta.bulk_group.tile [%0, {%1, %2, %3, %4}], [%5];\n"
:
: "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]), "r"(offset[1]), "r"(offset[2]),
"r"(offset[3]), "l"(__cvta_generic_to_shared(src))
: "memory");
}
else if constexpr (nbDims == 5)
{
asm volatile("cp.async.bulk.tensor.2d.global.shared::cta.bulk_group.tile [%0, {%1, %2, %3, %4, %5}], [%6];\n"
:
: "l"(reinterpret_cast<uint64_t>(&tensorMap)), "r"(offset[0]), "r"(offset[1]), "r"(offset[2]),
"r"(offset[3]), "r"(offset[4]), "l"(__cvta_generic_to_shared(src))
: "memory");
}
else
{
static_assert(nbDims >= 1 && nbDims <= 5);
}
}
__device__ inline void setTensorMapGlbAddr(CUtensorMap& tensorMap, void* ptr)
{
asm volatile("tensormap.replace.tile.global_address.global.b1024.b64 [%0], %1;\n" ::"l"(&tensorMap), "l"(ptr)
: "memory");
}
__device__ inline void commitGroup()
{
asm volatile("cp.async.bulk.commit_group;\n" : : : "memory");
}
// wait until only targetNbInFlightGroups groups are still in-flight.
template <uint32_t targetNbInFlightGroups>
__device__ inline void waitGroup()
{
asm volatile("cp.async.bulk.wait_group %0;\n" ::"n"(targetNbInFlightGroups) : "memory");
}
__device__ inline void prefetchTensorMap(CUtensorMap const& tensorMap, StateSpace loc = StateSpace::kGENERIC)
{
assert(reinterpret_cast<uint64_t>(&tensorMap) % alignof(CUtensorMap) == 0);
switch (loc)
{
case StateSpace::kCONSTANT:
asm volatile("prefetch.const.tensormap [%0];\n" ::"l"(__cvta_generic_to_constant(&tensorMap)) : "memory");
break;
case StateSpace::kPARAMETER:
asm volatile("prefetch.param.tensormap [%0];\n" ::"l"(__cvta_generic_to_grid_constant(&tensorMap)) : "memory");
break;
case StateSpace::kGENERIC:
asm volatile("prefetch.tensormap [%0];\n" ::"l"(reinterpret_cast<uint64_t>(&tensorMap)) : "memory");
break;
default: asm volatile("trap;\n");
}
}
template <typename T>
__device__ inline void storeAsync(void* dst, T const& src, CgaBarrier& bar)
{
constexpr uint32_t nbWords = exactDiv(sizeof(T), sizeof(uint32_t));
Vec<uint32_t, nbWords> const& srcVec = reinterpret_cast<Vec<uint32_t, nbWords> const&>(src);
if constexpr (nbWords == 1)
{
asm volatile("st.async.weak.shared::cluster.mbarrier::complete_tx::bytes.u32 [%0], %1, [%2];\n" ::"l"(
__cvta_generic_to_shared(dst)),
"r"(srcVec[0]), "l"(__cvta_generic_to_shared(&bar))
: "memory");
}
else if constexpr (nbWords == 2)
{
asm volatile("st.async.weak.shared::cluster.mbarrier::complete_tx::bytes.v2.u32 [%0], {%1, %2}, [%3];\n" ::"l"(
__cvta_generic_to_shared(dst)),
"r"(srcVec[0]), "r"(srcVec[1]), "l"(__cvta_generic_to_shared(&bar))
: "memory");
}
else if constexpr (nbWords == 4)
{
asm volatile(
"st.async.weak.shared::cluster.mbarrier::complete_tx::bytes.v4.u32 [%0], {%1, %2, %3, %4}, [%5];\n" ::"l"(
__cvta_generic_to_shared(dst)),
"r"(srcVec[0]), "r"(srcVec[1]), "r"(srcVec[2]), "r"(srcVec[3]), "l"(__cvta_generic_to_shared(&bar))
: "memory");
}
else
{
static_assert(nbWords == 1 || nbWords == 2 || nbWords == 4, "src size must be 4, 8 or 16 bytes");
}
}
} // namespace tma