/*
Adapted from https://github.com/mit-han-lab/llm-awq
Modified from NVIDIA FasterTransformer: https://github.com/NVIDIA/FasterTransformer/blob/main/src/fastertransformer/cutlass_extensions/include/cutlass_extensions/interleaved_numeric_conversion.h
@article{lin2023awq,
  title={AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration},
  author={Lin, Ji and Tang, Jiaming and Tang, Haotian and Yang, Shang and Dang, Xingyu and Han, Song},
  journal={arXiv},
  year={2023}
}
*/

#pragma once

namespace vllm {
namespace awq {

__device__ uint4 dequantize_s4_to_fp16x2(uint32_t const& source)
{
#if defined(__CUDA_ARCH__) && __CUDA_ARCH__ < 750
  assert(false);
#else
    uint4 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;
    // Haotian: subtract {1024, 1024} instead, we do not need to map to [-8, 7]
    static constexpr uint32_t FP16_TOP_MAGIC_NUM = 0x64006400;
    // 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;
    // Haotian: Let's use {-64, -64}.
    static constexpr uint32_t NEG_64 = 0xd400d400;

    // 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_64));
    // 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_64));

    return result;
#endif
}

} // namespace awq
} // namespace vllm
