danieldk's picture
danieldk HF Staff
Import EETQ kernels
1dc29e9
raw
history blame
17.7 kB
/***************************************************************************************************
* Copyright (c) 2017 - 2022 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
* SPDX-License-Identifier: BSD-3-Clause
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions are met:
*
* 1. Redistributions of source code must retain the above copyright notice, this
* list of conditions and the following disclaimer.
*
* 2. Redistributions in binary form must reproduce the above copyright notice,
* this list of conditions and the following disclaimer in the documentation
* and/or other materials provided with the distribution.
*
* 3. Neither the name of the copyright holder nor the names of its
* contributors may be used to endorse or promote products derived from
* this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*
**************************************************************************************************/
/*!
\file
\brief Boost-like numeric conversion operator for int8 and CUTLASS int4b_t interleaved in a register
*/
#pragma once
#include "cutlass/arch/arch.h"
#include "cutlass/array.h"
#include "cutlass/half.h"
#include "cutlass/numeric_types.h"
namespace cutlass {
// This converter is meant to be used with data interleaved in a 32-bit register where the even elements are in the low
// bits and the odd elemeents are in the high bits of the register. In addition, it assumes elements were originally
// signed and had a bias of 2**(b-1) added (where b is the number of bits in the type) to make all numbers unsigned.
// This converter will uninterleave the data and subtract the bias while converting to the result type.
template<typename T, typename S, int N>
struct FastInterleavedAndBiasedNumericArrayConverter {
};
template<>
struct FastInterleavedAndBiasedNumericArrayConverter<half_t, uint8_t, 4> {
using result_type = Array<half_t, 4>;
using source_type = Array<uint8_t, 4>;
CUTLASS_DEVICE
static result_type convert(source_type const& source)
{
result_type result;
uint32_t* h = reinterpret_cast<uint32_t*>(&result);
uint32_t const i8s = reinterpret_cast<uint32_t const&>(source);
static constexpr uint32_t mask_for_elt_01 = 0x5250;
static constexpr uint32_t mask_for_elt_23 = 0x5351;
static constexpr uint32_t start_byte_for_fp16 = 0x64646464;
asm volatile("prmt.b32 %0,%1,%2,%3;\n" : "=r"(h[0]) : "r"(i8s), "n"(start_byte_for_fp16), "n"(mask_for_elt_01));
asm volatile("prmt.b32 %0,%1,%2,%3;\n" : "=r"(h[1]) : "r"(i8s), "n"(start_byte_for_fp16), "n"(mask_for_elt_23));
// Lastly, we subtract 1152 from our constructed number using fp16 math to get our signed integer as fp16.
static constexpr uint32_t I8s_TO_F16s_MAGIC_NUM = 0x64806480;
asm volatile("sub.f16x2 %0, %1, %2;\n" : "=r"(h[0]) : "r"(h[0]), "r"(I8s_TO_F16s_MAGIC_NUM));
asm volatile("sub.f16x2 %0, %1, %2;\n" : "=r"(h[1]) : "r"(h[1]), "r"(I8s_TO_F16s_MAGIC_NUM));
return result;
}
CUTLASS_DEVICE
result_type operator()(source_type const& s)
{
return convert(s);
}
};
template<int N>
struct FastInterleavedAndBiasedNumericArrayConverter<half_t, uint8_t, N> {
static constexpr int VEC_WIDTH = 4;
static_assert(!(N % VEC_WIDTH), "N must be multiple of 4.");
using result_type = Array<half_t, N>;
using source_type = Array<uint8_t, N>;
CUTLASS_DEVICE
static result_type convert(source_type const& source)
{
using scalar_result_type = typename result_type::Element;
using scalar_source_type = typename source_type::Element;
FastInterleavedAndBiasedNumericArrayConverter<scalar_result_type, scalar_source_type, VEC_WIDTH>
convert_vector_;
result_type result;
using vec_result = Array<scalar_result_type, VEC_WIDTH>;
using vec_source = Array<scalar_source_type, VEC_WIDTH>;
vec_result* result_ptr = reinterpret_cast<vec_result*>(&result);
vec_source const* source_ptr = reinterpret_cast<vec_source const*>(&source);
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N / VEC_WIDTH; ++i) {
result_ptr[i] = convert_vector_(source_ptr[i]);
}
return result;
}
CUTLASS_DEVICE
result_type operator()(source_type const& s)
{
return convert(s);
}
};
template<>
struct FastInterleavedAndBiasedNumericArrayConverter<bfloat16_t, uint8_t, 4> {
using result_type = Array<bfloat16_t, 4>;
using source_type = Array<uint8_t, 4>;
CUTLASS_DEVICE
static result_type convert(source_type const& source)
{
result_type result;
#if (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 800))
uint32_t* bf16_result_ptr = reinterpret_cast<uint32_t*>(&result);
uint32_t const i8s = reinterpret_cast<uint32_t const&>(source);
static constexpr uint32_t fp32_base = 0x4B000000;
float fp32_intermediates[4];
// Construct FP32s, bfloat does not have enough mantissa for IADD trick
uint32_t* fp32_intermediates_casted = reinterpret_cast<uint32_t*>(fp32_intermediates);
fp32_intermediates_casted[0] = __byte_perm(i8s, fp32_base, 0x7650);
fp32_intermediates_casted[1] = __byte_perm(i8s, fp32_base, 0x7652);
fp32_intermediates_casted[2] = __byte_perm(i8s, fp32_base, 0x7651);
fp32_intermediates_casted[3] = __byte_perm(i8s, fp32_base, 0x7653);
// Subtract out fp32_base + 128 to make the unsigned integer signed.
CUTLASS_PRAGMA_UNROLL
for (int ii = 0; ii < 4; ++ii) {
fp32_intermediates[ii] -= 8388736.f;
}
// Truncate the fp32 representation and pack up as bfloat16s.
CUTLASS_PRAGMA_UNROLL
for (int ii = 0; ii < 2; ++ii) {
bf16_result_ptr[ii] =
__byte_perm(fp32_intermediates_casted[2 * ii + 0], fp32_intermediates_casted[2 * ii + 1], 0x7632);
}
#else
// Disable this on architectures older than Ampere since they lack hardware for bf16 mma. If one wishes to use
// HMMA on older hardware, they should Convert directly to FP16 using FP16 converters.
result.clear(); // Suppress compiler warning
arch::device_breakpoint();
#endif
return result;
}
CUTLASS_DEVICE
result_type operator()(source_type const& s)
{
return convert(s);
}
};
template<int N>
struct FastInterleavedAndBiasedNumericArrayConverter<bfloat16_t, uint8_t, N> {
static constexpr int VEC_WIDTH = 4;
static_assert(!(N % VEC_WIDTH), "N must be multiple of 4.");
using result_type = Array<bfloat16_t, N>;
using source_type = Array<uint8_t, N>;
CUTLASS_DEVICE
static result_type convert(source_type const& source)
{
using scalar_result_type = typename result_type::Element;
using scalar_source_type = typename source_type::Element;
FastInterleavedAndBiasedNumericArrayConverter<scalar_result_type, scalar_source_type, VEC_WIDTH>
convert_vector_;
result_type result;
using vec_result = Array<scalar_result_type, VEC_WIDTH>;
using vec_source = Array<scalar_source_type, VEC_WIDTH>;
vec_result* result_ptr = reinterpret_cast<vec_result*>(&result);
vec_source const* source_ptr = reinterpret_cast<vec_source const*>(&source);
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N / VEC_WIDTH; ++i) {
result_ptr[i] = convert_vector_(source_ptr[i]);
}
return result;
}
CUTLASS_DEVICE
result_type operator()(source_type const& s)
{
return convert(s);
}
};
template<>
struct FastInterleavedAndBiasedNumericArrayConverter<half_t, uint4b_t, 8> {
using result_type = Array<half_t, 8>;
using source_type = Array<uint4b_t, 8>;
CUTLASS_DEVICE
static result_type convert(source_type const& source)
{
result_type result;
uint32_t* h = reinterpret_cast<uint32_t*>(&result);
uint32_t const i4s = reinterpret_cast<uint32_t const&>(source);
// First, we extract the i4s and construct an intermediate fp16 number.
static constexpr uint32_t immLut = (0xf0 & 0xcc) | 0xaa;
static constexpr uint32_t BOTTOM_MASK = 0x000f000f;
static constexpr uint32_t TOP_MASK = 0x00f000f0;
static constexpr uint32_t I4s_TO_F16s_MAGIC_NUM = 0x64006400;
// Note that the entire sequence only requires 1 shift instruction. This is thanks to the register packing
// format and the fact that we force our integers to be unsigned, and account for this in the fp16 subtractions.
// In addition, I exploit the fact that sub and fma have the same throughput in order to convert elt_23 and
// elt_67 to fp16 without having to shift them to the bottom bits before hand.
// Shift right by 8 to now consider elt_45 and elt_67. Issue first to hide RAW dependency if we issue
// immediately before required.
const uint32_t top_i4s = i4s >> 8;
// Extract elt_01 - (i4s & 0x000f000f) | 0x64006400
asm volatile("lop3.b32 %0, %1, %2, %3, %4;\n"
: "=r"(h[0])
: "r"(i4s), "n"(BOTTOM_MASK), "n"(I4s_TO_F16s_MAGIC_NUM), "n"(immLut));
// Extract elt_23 (i4s & 0x00f000f0) | 0x64006400
asm volatile("lop3.b32 %0, %1, %2, %3, %4;\n"
: "=r"(h[1])
: "r"(i4s), "n"(TOP_MASK), "n"(I4s_TO_F16s_MAGIC_NUM), "n"(immLut));
// Extract elt_45 (top_i4s & 0x000f000f) | 0x64006400
asm volatile("lop3.b32 %0, %1, %2, %3, %4;\n"
: "=r"(h[2])
: "r"(top_i4s), "n"(BOTTOM_MASK), "n"(I4s_TO_F16s_MAGIC_NUM), "n"(immLut));
// Extract elt_67 (top_i4s & 0x00f000f0) | 0x64006400
asm volatile("lop3.b32 %0, %1, %2, %3, %4;\n"
: "=r"(h[3])
: "r"(top_i4s), "n"(TOP_MASK), "n"(I4s_TO_F16s_MAGIC_NUM), "n"(immLut));
// I use inline PTX below because I am not sure if the compiler will emit float2half instructions if I use the
// half2 ctor. In this case, I chose performance reliability over code readability.
// This is the half2 {1032, 1032} represented as an integer.
static constexpr uint32_t FP16_TOP_MAGIC_NUM = 0x64086408;
// This is the half2 {1 / 16, 1 / 16} represented as an integer.
static constexpr uint32_t ONE_SIXTEENTH = 0x2c002c00;
// This is the half2 {-72, -72} represented as an integer.
static constexpr uint32_t NEG_72 = 0xd480d480;
// Finally, we construct the output numbers.
// Convert elt_01
asm volatile("sub.f16x2 %0, %1, %2;\n" : "=r"(h[0]) : "r"(h[0]), "r"(FP16_TOP_MAGIC_NUM));
// Convert elt_23
asm volatile("fma.rn.f16x2 %0, %1, %2, %3;\n" : "=r"(h[1]) : "r"(h[1]), "r"(ONE_SIXTEENTH), "r"(NEG_72));
// Convert elt_45
asm volatile("sub.f16x2 %0, %1, %2;\n" : "=r"(h[2]) : "r"(h[2]), "r"(FP16_TOP_MAGIC_NUM));
// Convert elt_67
asm volatile("fma.rn.f16x2 %0, %1, %2, %3;\n" : "=r"(h[3]) : "r"(h[3]), "r"(ONE_SIXTEENTH), "r"(NEG_72));
return result;
}
CUTLASS_DEVICE
result_type operator()(source_type const& s)
{
return convert(s);
}
};
template<int N>
struct FastInterleavedAndBiasedNumericArrayConverter<half_t, uint4b_t, N> {
static constexpr int VEC_WIDTH = 8;
static_assert(!(N % VEC_WIDTH), "N must be multiple of 8.");
using result_type = Array<half_t, N>;
using source_type = Array<uint4b_t, N>;
CUTLASS_DEVICE
static result_type convert(source_type const& source)
{
using scalar_result_type = typename result_type::Element;
using scalar_source_type = typename source_type::Element;
FastInterleavedAndBiasedNumericArrayConverter<scalar_result_type, scalar_source_type, VEC_WIDTH>
convert_vector_;
result_type result;
using vec_result = Array<scalar_result_type, VEC_WIDTH>;
using vec_source = Array<scalar_source_type, VEC_WIDTH>;
vec_result* result_ptr = reinterpret_cast<vec_result*>(&result);
vec_source const* source_ptr = reinterpret_cast<vec_source const*>(&source);
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N / VEC_WIDTH; ++i) {
result_ptr[i] = convert_vector_(source_ptr[i]);
}
return result;
}
CUTLASS_DEVICE
result_type operator()(source_type const& s)
{
return convert(s);
}
};
template<>
struct FastInterleavedAndBiasedNumericArrayConverter<bfloat16_t, uint4b_t, 8> {
using result_type = Array<bfloat16_t, 8>;
using source_type = Array<uint4b_t, 8>;
CUTLASS_DEVICE
static result_type convert(source_type const& source)
{
result_type result;
#if (defined(__CUDA_ARCH__) && (__CUDA_ARCH__ >= 800))
uint32_t* h = reinterpret_cast<uint32_t*>(&result);
uint32_t const source_i4s = reinterpret_cast<uint32_t const&>(source);
// First, we extract the i4s and construct an intermediate fp16 number.
static constexpr uint32_t immLut = (0xf0 & 0xcc) | 0xaa;
static constexpr uint32_t MASK = 0x000f000f;
static constexpr uint32_t I4s_TO_BF16s_MAGIC_NUM = 0x43004300;
// We don't have enough mantissa to remove as much shift overhead as FP16, so we must loop.
// No shift needed for first item.
uint32_t i4s = source_i4s;
asm volatile("lop3.b32 %0, %1, %2, %3, %4;\n"
: "=r"(h[0])
: "r"(i4s), "n"(MASK), "n"(I4s_TO_BF16s_MAGIC_NUM), "n"(immLut));
CUTLASS_PRAGMA_UNROLL
for (int ii = 1; ii < result_type::kElements / 2; ++ii) {
i4s >>= sizeof_bits<typename source_type::Element>::value;
// (i4s & 0x000f000f) | 0x43004300
asm volatile("lop3.b32 %0, %1, %2, %3, %4;\n"
: "=r"(h[ii])
: "r"(i4s), "n"(MASK), "n"(I4s_TO_BF16s_MAGIC_NUM), "n"(immLut));
}
// This is the BF16 {-136, -136} represented as an integer.
static constexpr uint32_t BF16_BIAS = 0xC308C308;
static constexpr uint32_t BF16_ONE = 0x3F803F80;
// Finally, we construct the output numbers.
CUTLASS_PRAGMA_UNROLL
for (int ii = 0; ii < result_type::kElements / 2; ++ii) {
// Since this section is for Ampere+, we use bf16 fma to do the bias subtraction
asm("fma.rn.bf16x2 %0, %1, %2, %3;\n" : "=r"(h[ii]) : "r"(h[ii]), "r"(BF16_ONE), "r"(BF16_BIAS));
}
#else
// Disable this on architectures older than Ampere since they lack hardware for bf16 mma. If one wishes to use
// HMMA on older hardware, they should Convert directly to FP16 using FP16 converters.
arch::device_breakpoint();
result.clear(); // Suppress compiler warning.
#endif
return result;
}
CUTLASS_DEVICE
result_type operator()(source_type const& s)
{
return convert(s);
}
};
template<int N>
struct FastInterleavedAndBiasedNumericArrayConverter<bfloat16_t, uint4b_t, N> {
static constexpr int VEC_WIDTH = 8;
static_assert(!(N % VEC_WIDTH), "N must be multiple of 8.");
using result_type = Array<bfloat16_t, N>;
using source_type = Array<uint4b_t, N>;
CUTLASS_DEVICE
static result_type convert(source_type const& source)
{
using scalar_result_type = typename result_type::Element;
using scalar_source_type = typename source_type::Element;
FastInterleavedAndBiasedNumericArrayConverter<scalar_result_type, scalar_source_type, VEC_WIDTH>
convert_vector_;
result_type result;
using vec_result = Array<scalar_result_type, VEC_WIDTH>;
using vec_source = Array<scalar_source_type, VEC_WIDTH>;
vec_result* result_ptr = reinterpret_cast<vec_result*>(&result);
vec_source const* source_ptr = reinterpret_cast<vec_source const*>(&source);
CUTLASS_PRAGMA_UNROLL
for (int i = 0; i < N / VEC_WIDTH; ++i) {
result_ptr[i] = convert_vector_(source_ptr[i]);
}
return result;
}
CUTLASS_DEVICE
result_type operator()(source_type const& s)
{
return convert(s);
}
};
/////////////////////////////////////////////////////////////////////////////////////////////////
} // namespace cutlass
/////////////////////////////////////////////////////////////////////////////////////////////////