elementwise.cu

#include <stdio.h>
#include <stdlib.h>
#include <float.h>
#include <vector>
#include <algorithm>
#include <cuda_runtime.h>
#include <cuda_fp16.h>
#include <cuda_bf16.h>
#include <cuda_fp8.h>
#include <torch/types.h>
#include <torch/extension.h>

#define WARP_SIZE 32
#define INT4(value) (reinterpret_cast<int4*>(&(value))[0])
#define FLOAT4(value) (reinterpret_cast<float4*>(&(value))[0])
#define HALF2(value) (reinterpret_cast<half2*>(&(value))[0])
#define BFLOAT2(value) (reinterpret_cast<__nv_bfloat162*>(&(value))[0])
#define LDST128BITS(value) (reinterpret_cast<float4*>(&(value))[0])

// -------------------------------------- FP32 -------------------------------------- 
// ElementWise Add  
// grid(N/256), block(256)
// a: Nx1, b: Nx1, c: Nx1, c = elementwise_add(a, b)
__global__ void elementwise_add_f32_kernel(float* a, float* b, float* c, int N) {
  int idx = blockIdx.x * blockDim.x + threadIdx.x;
  if (idx < N) c[idx] = a[idx] + b[idx];
}

// ElementWise Add + Vec4
// grid(N/256), block(256/4)
// a: Nx1, b: Nx1, c: Nx1, c = elementwise_add(a, b)
__global__ void elementwise_add_f32x4_kernel(float* a, float* b, float* c, int N) {
  int idx = 4 * (blockIdx.x * blockDim.x + threadIdx.x);
  if (idx < N) {
    float4 reg_a = FLOAT4(a[idx]);
    float4 reg_b = FLOAT4(b[idx]);
    float4 reg_c;
    reg_c.x = reg_a.x + reg_b.x;
    reg_c.y = reg_a.y + reg_b.y;
    reg_c.z = reg_a.z + reg_b.z;
    reg_c.w = reg_a.w + reg_b.w;
    FLOAT4(c[idx]) = reg_c;
  }
}

// -------------------------------------- FP16 -------------------------------------- 
// ElementWise Add  
// grid(N/256), block(256)
// a: Nx1, b: Nx1, c: Nx1, c = elementwise_add(a, b)
__global__ void elementwise_add_f16_kernel(half* a, half* b, half* c, int N) {
  int idx = blockIdx.x * blockDim.x + threadIdx.x;
  if (idx < N) c[idx] = __hadd(a[idx], b[idx]);
}

// a: Nx1, b: Nx1, c: Nx1, c = elementwise_add(a, b)
__global__ void elementwise_add_f16x2_kernel(half* a, half* b, half* c, int N) {
  int idx = 2 * (blockIdx.x * blockDim.x + threadIdx.x);
  if (idx < N) {
    half2 reg_a = HALF2(a[idx]);
    half2 reg_b = HALF2(b[idx]);
    half2 reg_c;
    reg_c.x = __hadd(reg_a.x, reg_b.x);
    reg_c.y = __hadd(reg_a.y, reg_b.y);
    HALF2(c[idx]) = reg_c;
  }
}

__global__ void elementwise_add_f16x8_kernel(half* a, half* b, half* c, int N) {
  int idx = 8 * (blockIdx.x * blockDim.x + threadIdx.x);
  // manual unroll and improve L2 cache hit rate.
  // Only   L2 cache: load 32  bytes in 1 memory issue (default)
  // Enable L1 cache: load 128 bytes in 1 memory issue (-Xptxas -dlcm=ca)
  // why try fp16x8 within 1 threads? ref: https://zhuanlan.zhihu.com/p/641639133
  // 0. first, tid_0 load 32 bytes in 1 memory issue and cache data into L2 cache.
  // 1. then, tid_1,...,tid_3 hit L2 cache and load data from L2 cache directly.
  half2 reg_a_0 = HALF2(a[idx + 0]);
  half2 reg_a_1 = HALF2(a[idx + 2]);
  half2 reg_a_2 = HALF2(a[idx + 4]);
  half2 reg_a_3 = HALF2(a[idx + 6]);
  half2 reg_b_0 = HALF2(b[idx + 0]);
  half2 reg_b_1 = HALF2(b[idx + 2]);
  half2 reg_b_2 = HALF2(b[idx + 4]);
  half2 reg_b_3 = HALF2(b[idx + 6]);
  half2 reg_c_0, reg_c_1, reg_c_2, reg_c_3;
  reg_c_0.x = __hadd(reg_a_0.x, reg_b_0.x);
  reg_c_0.y = __hadd(reg_a_0.y, reg_b_0.y);
  reg_c_1.x = __hadd(reg_a_1.x, reg_b_1.x);
  reg_c_1.y = __hadd(reg_a_1.y, reg_b_1.y);
  reg_c_2.x = __hadd(reg_a_2.x, reg_b_2.x);
  reg_c_2.y = __hadd(reg_a_2.y, reg_b_2.y);
  reg_c_3.x = __hadd(reg_a_3.x, reg_b_3.x);
  reg_c_3.y = __hadd(reg_a_3.y, reg_b_3.y);
  if ((idx + 0) < N) { HALF2(c[idx + 0]) = reg_c_0; }
  if ((idx + 2) < N) { HALF2(c[idx + 2]) = reg_c_1; }
  if ((idx + 4) < N) { HALF2(c[idx + 4]) = reg_c_2; }
  if ((idx + 6) < N) { HALF2(c[idx + 6]) = reg_c_3; }
}

__global__ void elementwise_add_f16x8_pack_kernel(half* a, half* b, half* c, int N) {
  int idx = 8 * (blockIdx.x * blockDim.x + threadIdx.x);
  // temporary register(memory), .local space in ptx, addressable
  half pack_a[8], pack_b[8], pack_c[8]; // 8x16 bits=128 bits.
  // reinterpret as float4 and load 128 bits in 1 memory issue.
  LDST128BITS(pack_a[0]) = LDST128BITS(a[idx]); // load 128 bits
  LDST128BITS(pack_b[0]) = LDST128BITS(b[idx]); // load 128 bits

  #pragma unroll
  for (int i = 0; i < 8; i += 2) {
    // __hadd2 for half2 x 4
    HALF2(pack_c[i]) = __hadd2(HALF2(pack_a[i]), HALF2(pack_b[i]));
  }
  // reinterpret as float4 and store 128 bits in 1 memory issue.
  if ((idx + 7) < N) { LDST128BITS(c[idx]) = LDST128BITS(pack_c[0]); }
}


// --------------------- PyTorch bindings for custom kernel -----------------------
#define STRINGFY(str) #str
#define TORCH_BINDING_COMMON_EXTENSION(func) \
  m.def(STRINGFY(func), &func, STRINGFY(func));

#define CHECK_TORCH_TENSOR_DTYPE(T, th_type)                 \
if(((T).options().dtype() != (th_type))) {                   \
  std::cout << "Tensor Info:" << (T).options() << std::endl; \
  throw std::runtime_error("values must be "#th_type);       \
}

#define TORCH_BINDING_ELEM_ADD(packed_type, th_type, element_type, n_elements)   \
void elementwise_add_##packed_type(                                              \
  torch::Tensor a, torch::Tensor b, torch::Tensor c) {                           \
  CHECK_TORCH_TENSOR_DTYPE(a, (th_type))                                         \
  CHECK_TORCH_TENSOR_DTYPE(b, (th_type))                                         \
  CHECK_TORCH_TENSOR_DTYPE(c, (th_type))                                         \
  const int ndim = a.dim();                                                      \
  if (ndim != 2) {                                                               \
    int N = 1;                                                                   \
    for (int i = 0; i < ndim; ++i) { N *= a.size(i); }                           \
    dim3 block(256 / (n_elements));                                              \
    dim3 grid((N + 256 - 1) / 256);                                              \
    elementwise_add_##packed_type##_kernel<<<grid, block>>>(                     \
      reinterpret_cast<element_type*>(a.data_ptr()),                             \
      reinterpret_cast<element_type*>(b.data_ptr()),                             \
      reinterpret_cast<element_type*>(c.data_ptr()), N);                         \
  } else {                                                                       \
    const int S = a.size(0);                                                     \
    const int K = a.size(1);                                                     \
    const int N = S * K;                                                         \
    if ((K/(n_elements)) <= 1024) {                                              \
      dim3 block(K/(n_elements));                                                \
      dim3 grid(S);                                                              \
      elementwise_add_##packed_type##_kernel<<<grid, block>>>(                   \
        reinterpret_cast<element_type*>(a.data_ptr()),                           \
        reinterpret_cast<element_type*>(b.data_ptr()),                           \
        reinterpret_cast<element_type*>(c.data_ptr()), N);                       \
    } else {                                                                     \
      int N = 1;                                                                 \
      for (int i = 0; i < ndim; ++i) { N *= a.size(i); }                         \
      dim3 block(256 / (n_elements));                                            \
      dim3 grid((N + 256 - 1) / 256);                                            \
      elementwise_add_##packed_type##_kernel<<<grid, block>>>(                   \
        reinterpret_cast<element_type*>(a.data_ptr()),                           \
        reinterpret_cast<element_type*>(b.data_ptr()),                           \
        reinterpret_cast<element_type*>(c.data_ptr()), N);                       \
    }                                                                            \
  }                                                                              \
}


TORCH_BINDING_ELEM_ADD(f32,         torch::kFloat32,    float,    1)
TORCH_BINDING_ELEM_ADD(f32x4,       torch::kFloat32,    float,    4)
TORCH_BINDING_ELEM_ADD(f16,         torch::kHalf,       half,     1)
TORCH_BINDING_ELEM_ADD(f16x2,       torch::kHalf,       half,     2)
TORCH_BINDING_ELEM_ADD(f16x8,       torch::kHalf,       half,     8)
TORCH_BINDING_ELEM_ADD(f16x8_pack,  torch::kHalf,       half,     8)

PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
  TORCH_BINDING_COMMON_EXTENSION(elementwise_add_f32)
  TORCH_BINDING_COMMON_EXTENSION(elementwise_add_f32x4)
  TORCH_BINDING_COMMON_EXTENSION(elementwise_add_f16)
  TORCH_BINDING_COMMON_EXTENSION(elementwise_add_f16x2)
  TORCH_BINDING_COMMON_EXTENSION(elementwise_add_f16x8)
  TORCH_BINDING_COMMON_EXTENSION(elementwise_add_f16x8_pack)
}