cuda/rwkv5.cu

#include <stdio.h>
#include <assert.h>
#include "ATen/ATen.h"
typedef at::BFloat16 bf16;
typedef at::Half fp16;
typedef float fp32;

template <typename F>
__global__ void kernel_forward(const int B, const int T, const int C, const int H, float *__restrict__ _state,
                               const F *__restrict__ const _r, const F *__restrict__ const _k, const F *__restrict__ const _v, const float *__restrict__ _w, const F *__restrict__ _u,
                               F *__restrict__ const _y)
{
    const int b = blockIdx.x / H;
    const int h = blockIdx.x % H;
    const int i = threadIdx.x;
    _w += h*_N_;
    _u += h*_N_;
    _state += h*_N_*_N_ + i*_N_; // wrong if B > 1 !!!

    __shared__ float r[_N_], k[_N_], u[_N_], w[_N_];
    
    float state[_N_];
    #pragma unroll
    for (int j = 0; j < _N_; j++)
        state[j] = _state[j];
    
    __syncthreads();
    u[i] = float(_u[i]);
    w[i] = _w[i];
    __syncthreads();

    for (int t = b*T*C + h*_N_ + i; t < (b+1)*T*C + h*_N_ + i; t += C)
    {
        __syncthreads();
        r[i] = float(_r[t]);
        k[i] = float(_k[t]);
        __syncthreads();

        const float v = float(_v[t]);
        float y = 0;

        #pragma unroll
        for (int j = 0; j < _N_; j+=4)
        {
            const float4& r_ = (float4&)(r[j]);
            const float4& k_ = (float4&)(k[j]);
            const float4& w_ = (float4&)(w[j]);
            const float4& u_ = (float4&)(u[j]);
            float4& s = (float4&)(state[j]);
            float4 x;

            x.x = k_.x * v;
            x.y = k_.y * v;
            x.z = k_.z * v;
            x.w = k_.w * v;

            y += r_.x * (u_.x * x.x + s.x);
            y += r_.y * (u_.y * x.y + s.y);
            y += r_.z * (u_.z * x.z + s.z);
            y += r_.w * (u_.w * x.w + s.w);

            s.x = s.x * w_.x + x.x;
            s.y = s.y * w_.y + x.y;
            s.z = s.z * w_.z + x.z;
            s.w = s.w * w_.w + x.w;
        }
        _y[t] = F(y);
    }
    #pragma unroll
    for (int j = 0; j < _N_; j++)
        _state[j] = state[j];
}

void cuda_forward_bf16(int B, int T, int C, int H, float *state, bf16 *r, bf16 *k, bf16 *v, float *w, bf16 *u, bf16 *y)
{
    assert(H*_N_ == C);
    kernel_forward<<<dim3(B * H), dim3(_N_)>>>(B, T, C, H, state, r, k, v, w, u, y);
}
void cuda_forward_fp16(int B, int T, int C, int H, float *state, fp16 *r, fp16 *k, fp16 *v, float *w, fp16 *u, fp16 *y)
{
    assert(H*_N_ == C);
    kernel_forward<<<dim3(B * H), dim3(_N_)>>>(B, T, C, H, state, r, k, v, w, u, y);
}
void cuda_forward_fp32(int B, int T, int C, int H, float *state, fp32 *r, fp32 *k, fp32 *v, float *w, fp32 *u, fp32 *y)
{
    assert(H*_N_ == C);
    kernel_forward<<<dim3(B * H), dim3(_N_)>>>(B, T, C, H, state, r, k, v, w, u, y);
}