Files
xserv/csrc/embedding/rope.cu
Gahow Wang 4c3f914459 kernels/cuda: paged-attention kernel, dispatch, pinned host memory
CUDA layer for the paged-KV + swap work:
- csrc: new paged_attention.cu plus updates across attention/gemm/norm/
  activation/embedding/reduce kernels and common.cuh.
- xserv-kernels: new dispatch module and kernel-binding updates.
- xserv-cuda: cudaMallocHost/FreeHost bindings + PinnedBuffer (host swap
  pool backing) and offset-aware D2H/H2D copies used to move KV blocks
  between the GPU pool and pinned host memory.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-28 19:58:36 +08:00

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#include <cuda_bf16.h>
#include <math.h>
#include "../common.cuh"
// RoPE: Rotary Position Embedding, using the Qwen/Llama rotate_half layout.
// For each dimension i in the first half at position `pos`:
// y[i] = x[i] * cos - x[i + half_dim] * sin
// y[i + half_dim] = x[i + half_dim] * cos + x[i] * sin
// where cos/sin come from precomputed cos_cache/sin_cache.
//
// cos_cache[pos][i] = cos(pos * freq[i])
// sin_cache[pos][i] = sin(pos * freq[i])
// freq[i] = 1.0 / (theta ^ (2i / head_dim))
// Apply RoPE in-place to Q or K tensor.
// x shape: [num_tokens, num_heads, head_dim]
// cos_cache, sin_cache shape: [max_seq_len, head_dim/2]
// positions: [num_tokens] — the position index for each token
__global__ void rope_f32(
float* __restrict__ x, // [num_tokens, num_heads, head_dim]
const float* __restrict__ cos_cache, // [max_seq_len, half_dim]
const float* __restrict__ sin_cache, // [max_seq_len, half_dim]
const int* __restrict__ positions, // [num_tokens]
int num_heads, int head_dim
) {
int token_idx = blockIdx.x;
int head_idx = blockIdx.y;
int half_dim = head_dim / 2;
int pair_idx = threadIdx.x; // which pair (0..half_dim)
if (pair_idx >= half_dim) return;
int pos = positions[token_idx];
float cos_val = cos_cache[pos * half_dim + pair_idx];
float sin_val = sin_cache[pos * half_dim + pair_idx];
int base = (token_idx * num_heads + head_idx) * head_dim;
float x0 = x[base + pair_idx];
float x1 = x[base + pair_idx + half_dim];
x[base + pair_idx] = x0 * cos_val - x1 * sin_val;
x[base + pair_idx + half_dim] = x1 * cos_val + x0 * sin_val;
}
__global__ void rope_bf16(
__nv_bfloat16* __restrict__ x,
const float* __restrict__ cos_cache,
const float* __restrict__ sin_cache,
const int* __restrict__ positions,
int num_heads, int head_dim
) {
int token_idx = blockIdx.x;
int head_idx = blockIdx.y;
int half_dim = head_dim / 2;
int pair_idx = threadIdx.x;
if (pair_idx >= half_dim) return;
int pos = positions[token_idx];
float cos_val = cos_cache[pos * half_dim + pair_idx];
float sin_val = sin_cache[pos * half_dim + pair_idx];
int base = (token_idx * num_heads + head_idx) * head_dim;
float x0 = __bfloat162float(x[base + pair_idx]);
float x1 = __bfloat162float(x[base + pair_idx + half_dim]);
x[base + pair_idx] = __float2bfloat16(x0 * cos_val - x1 * sin_val);
x[base + pair_idx + half_dim] = __float2bfloat16(x1 * cos_val + x0 * sin_val);
}
// Precompute cos/sin cache on GPU
__global__ void compute_rope_cache(
float* __restrict__ cos_cache, // [max_seq_len, half_dim]
float* __restrict__ sin_cache,
int max_seq_len, int half_dim, float theta
) {
int pos = blockIdx.x;
int i = threadIdx.x;
if (i >= half_dim) return;
float freq = 1.0f / powf(theta, (float)(2 * i) / (float)(2 * half_dim));
float angle = (float)pos * freq;
cos_cache[pos * half_dim + i] = cosf(angle);
sin_cache[pos * half_dim + i] = sinf(angle);
}
extern "C" {
void launch_rope_f32(void* x, const void* cos_cache, const void* sin_cache,
const void* positions, int num_tokens, int num_heads,
int head_dim, void* stream) {
dim3 grid(num_tokens, num_heads);
int block = head_dim / 2;
rope_f32<<<grid, block, 0, (cudaStream_t)stream>>>(
(float*)x, (const float*)cos_cache, (const float*)sin_cache,
(const int*)positions, num_heads, head_dim);
CUDA_CHECK_LAST_ERROR();
}
void launch_rope_bf16(void* x, const void* cos_cache, const void* sin_cache,
const void* positions, int num_tokens, int num_heads,
int head_dim, void* stream) {
dim3 grid(num_tokens, num_heads);
int block = head_dim / 2;
rope_bf16<<<grid, block, 0, (cudaStream_t)stream>>>(
(__nv_bfloat16*)x, (const float*)cos_cache, (const float*)sin_cache,
(const int*)positions, num_heads, head_dim);
CUDA_CHECK_LAST_ERROR();
}
void launch_compute_rope_cache(void* cos_cache, void* sin_cache,
int max_seq_len, int half_dim, float theta,
void* stream) {
compute_rope_cache<<<max_seq_len, half_dim, 0, (cudaStream_t)stream>>>(
(float*)cos_cache, (float*)sin_cache, max_seq_len, half_dim, theta);
CUDA_CHECK_LAST_ERROR();
}
}