mirror of
https://github.com/NVIDIA/TensorRT-LLM.git
synced 2026-01-14 06:27:45 +08:00
325 lines
13 KiB
C++
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
|