llama : add high-throughput mode (#14363)

* kv-cache : prepare K/V buffers for separation

ggml-ci

* batched-bench : fix oob write

ggml-ci

* llama : add "virtual sequences"

ggml-ci

* llama : use "stream" vs "virtual sequence"

ggml-ci

* graph : fix stream splitting when KV cache is not used

ggml-ci

* kv-cache : add multi-stream save/load support

ggml-ci

* llama : add "--attn-streams" flag

ggml-ci

* kv-cache : fix handling when find_slot fails

ggml-ci

* kv-cache : restore find_slot impl

ggml-ci

* kv-cache : add comments

* kv-cache : add bounds checks for sequence id

ggml-ci

* cont : add n_seq_max to batch allocr

ggml-ci

* kv-cache : perform stream copies lazily after llama_synchronize

ggml-ci

* kv-cache : avoid throwing exceptions across the C boundary

ggml-ci

* CUDA: 4D FlashAttention support (#14628)

* CUDA: 4D FlashAttention support

* CUDA: fix WMMA FA kernel

* llama : rename attn_streams -> kv_unified

ggml-ci

* common : rename kv_split -> kv_unified

ggml-ci

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
This commit is contained in:
Georgi Gerganov
2025-07-16 16:35:42 +03:00
committed by GitHub
parent ab14019821
commit 225e7a1438
30 changed files with 1080 additions and 460 deletions

View File

@@ -1224,8 +1224,10 @@ static __global__ void flash_attn_ext_f16(
const int ne13,
const int ne31,
const int ne32,
const int ne33,
const int nb31,
const int nb32,
const int nb33,
const int nb01,
const int nb02,
const int nb03,
@@ -1274,8 +1276,8 @@ static __global__ void flash_attn_ext_f16(
constexpr int kb_niter = FATTN_KQ_STRIDE / c::nbatch_fa; // Number of kernel iterations per assigned KQ slice.
// kbc == k block continuous, current index in continuous ijk space.
int kbc = (blockIdx.x + 0)*iter_k*iter_j*(ne02/ncols2) / gridDim.x;
const int kbc_stop = (blockIdx.x + 1)*iter_k*iter_j*(ne02/ncols2) / gridDim.x;
int kbc = (blockIdx.x + 0)*(iter_k*iter_j*(ne02/ncols2)*ne03) / gridDim.x;
const int kbc_stop = (blockIdx.x + 1)*(iter_k*iter_j*(ne02/ncols2)*ne03) / gridDim.x;
// If the seams of 2 CUDA blocks fall within an output tile their results need to be combined.
// For this we need to track both the block that starts the tile (needs_fixup) and the block that finishes the tile (is_fixup).
@@ -1285,18 +1287,19 @@ static __global__ void flash_attn_ext_f16(
int kb0_start = kbc % iter_k;
int kb0_stop = min(iter_k, kb0_start + kbc_stop - kbc);
while (kbc < kbc_stop && kb0_stop == iter_k) {
const int channel = kbc / (iter_k*iter_j);
const int jt = (kbc - channel*iter_k*iter_j) / iter_k; // j index of current tile.
const int sequence = kbc / (iter_k*iter_j*(ne02/ncols2));
const int head = (kbc - iter_k*iter_j*(ne02/ncols2)*sequence) / (iter_k*iter_j);
const int jt = (kbc - iter_k*iter_j*(ne02/ncols2)*sequence - iter_k*iter_j*head) / iter_k; // j index of current tile.
const float2 * Q_f2 = (const float2 *) (Q + nb02* channel*ncols2);
const half2 * K_h2 = (const half2 *) (K + nb12*(channel*ncols2 / gqa_ratio));
const float2 * Q_f2 = (const float2 *) (Q + nb03*sequence + nb02*(head*ncols2));
const half2 * K_h2 = (const half2 *) (K + nb13*sequence + nb12*(head*ncols2 / gqa_ratio));
const half2 * mask_h2 = ncols2 == 1 && !mask ? nullptr :
(const half2 *) (mask + nb32*(channel % ne32) + nb31*jt*ncols1);
float2 * dstk = ((float2 *) dst) + channel*(ncols2 * DV/2);
(const half2 *) (mask + nb33*(sequence % ne33) + nb31*jt*ncols1);
float2 * dstk = ((float2 *) dst) + (sequence*ne01*ne02 + head*ncols2) * (DV/2);
const half2 * V_h2 = mla ? K_h2 + (DKQ/2 - DV/2) : (const half2 *) (V + nb22*(channel*ncols2 / gqa_ratio));
const half2 * V_h2 = mla ? K_h2 + (DKQ/2 - DV/2) : (const half2 *) (V + nb23*sequence + nb22*(head*ncols2 / gqa_ratio));
const float slope = ncols2 == 1 ? get_alibi_slope(max_bias, channel, n_head_log2, m0, m1) : 1.0f;
const float slope = ncols2 == 1 ? get_alibi_slope(max_bias, head, n_head_log2, m0, m1) : 1.0f;
const int kb0_start_kernel = kb0_start * kb_niter;
const int kb0_stop_kernel = kb0_stop * kb_niter;
@@ -1325,18 +1328,19 @@ static __global__ void flash_attn_ext_f16(
return;
}
const int channel = kbc / (iter_k*iter_j);
const int jt = (kbc - channel*iter_k*iter_j) / iter_k; // j index of current tile.
const int sequence = kbc / (iter_k*iter_j*(ne02/ncols2));
const int head = (kbc - iter_k*iter_j*(ne02/ncols2)*sequence) / (iter_k*iter_j);
const int jt = (kbc - iter_k*iter_j*(ne02/ncols2)*sequence - iter_k*iter_j*head) / iter_k; // j index of current tile.
const float2 * Q_f2 = (const float2 *) (Q + nb02* channel*ncols2);
const half2 * K_h2 = (const half2 *) (K + nb12*(channel*ncols2 / gqa_ratio));
const float2 * Q_f2 = (const float2 *) (Q + nb03*sequence + nb02*(head*ncols2));
const half2 * K_h2 = (const half2 *) (K + nb13*sequence + nb12*(head*ncols2 / gqa_ratio));
const half2 * mask_h2 = ncols2 == 1 && !mask ? nullptr :
(const half2 *) (mask + nb32*(channel % ne32) + nb31*jt*ncols1);
float2 * dstk = ((float2 *) dst) + channel*(ncols2 * DV/2);
(const half2 *) (mask + nb33*(sequence % ne33) + nb31*jt*ncols1);
float2 * dstk = ((float2 *) dst) + (sequence*ne01*ne02 + head*ncols2) * (DV/2);
const half2 * V_h2 = mla ? K_h2 + (DKQ/2 - DV/2) : (const half2 *) (V + nb22*(channel*ncols2 / gqa_ratio));
const half2 * V_h2 = mla ? K_h2 + (DKQ/2 - DV/2) : (const half2 *) (V + nb23*sequence + nb22*(head*ncols2 / gqa_ratio));
const float slope = ncols2 == 1 ? get_alibi_slope(max_bias, channel, n_head_log2, m0, m1) : 1.0f;
const float slope = ncols2 == 1 ? get_alibi_slope(max_bias, head, n_head_log2, m0, m1) : 1.0f;
const int kb0_start_kernel = kb0_start * kb_niter;
const int kb0_stop_kernel = kb0_stop * kb_niter;