EngineX-Ascend/enginex-ascend-910-llama.cpp
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llama : add high-throughput mode (#14363)

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* 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
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23
ggml/src/ggml-cuda/fattn-vec-f16.cuh
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@@ -28,8 +28,10 @@ static __global__ void flash_attn_vec_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,
@@ -65,14 +67,16 @@ static __global__ void flash_attn_vec_ext_f16(
const int ic0 = blockIdx.x * ncols; // Index of the Q/QKV column to work on.
const int sequence = blockIdx.z / ne02;
const int head = blockIdx.z - sequence*ne02;
const int gqa_ratio = ne02 / ne12; // With grouped query attention there are > 1 Q matrices per K, V matrix.
Q += nb02* blockIdx.z + nb01*ic0;
K += nb12*(blockIdx.z / gqa_ratio);
V += nb22*(blockIdx.z / gqa_ratio);
Q += nb03*sequence + nb02* head + nb01*ic0;
K += nb13*sequence + nb12*(head / gqa_ratio);
V += nb23*sequence + nb22*(head / gqa_ratio);
const half * maskh = (const half *) (mask + nb32*(blockIdx.z % ne32) + nb31*ic0);
const half * maskh = (const half *) (mask + nb33*(sequence % ne33) + nb31*ic0);
const float slopef = get_alibi_slope(max_bias, blockIdx.z, n_head_log2, m0, m1);
const float slopef = get_alibi_slope(max_bias, head, n_head_log2, m0, m1);
const half slopeh = __float2half(slopef);
static_assert(D % (2*WARP_SIZE) == 0, "D not divisible by 2*WARP_SIZE == 64.");
@@ -330,12 +334,11 @@ static __global__ void flash_attn_vec_ext_f16(
if (gridDim.y == 1) {
dst_val /= kqsum[j_VKQ];
}
const int j_dst = (ic0 + j_VKQ)*gridDim.y + blockIdx.y;
dst[j_dst*D*gridDim.z + D*blockIdx.z + tid] = dst_val;
dst[(((sequence*ne01 + ic0 + j_VKQ)*ne02 + head)*gridDim.y + blockIdx.y)*D + tid] = dst_val;
}
if (gridDim.y != 1 && tid < ncols && (ncols <= 2 || ic0 + tid < ne01)) {
dst_meta[((ic0 + tid)*gridDim.z + blockIdx.z) * gridDim.y + blockIdx.y] = make_float2(kqmax[tid], kqsum[tid]);
dst_meta[((sequence*ne01 + ic0 + tid)*ne02 + head)*gridDim.y + blockIdx.y] = make_float2(kqmax[tid], kqsum[tid]);
}
#else
GGML_UNUSED(Q); GGML_UNUSED(K); GGML_UNUSED(V); GGML_UNUSED(mask);
@@ -344,8 +347,8 @@ static __global__ void flash_attn_vec_ext_f16(
GGML_UNUSED(n_head_log2); GGML_UNUSED(logit_softcap);
GGML_UNUSED(ne00); GGML_UNUSED(ne01); GGML_UNUSED(ne02);
GGML_UNUSED(ne03); GGML_UNUSED(ne10); GGML_UNUSED(ne11);
GGML_UNUSED(ne12); GGML_UNUSED(ne13); GGML_UNUSED(ne31); GGML_UNUSED(ne32);
GGML_UNUSED(nb31); GGML_UNUSED(nb32); GGML_UNUSED(nb01); GGML_UNUSED(nb02);
GGML_UNUSED(ne12); GGML_UNUSED(ne13); GGML_UNUSED(ne31); GGML_UNUSED(ne32); GGML_UNUSED(ne32);
GGML_UNUSED(nb31); GGML_UNUSED(nb32); GGML_UNUSED(nb33); GGML_UNUSED(nb01); GGML_UNUSED(nb02);
GGML_UNUSED(nb03); GGML_UNUSED(nb11); GGML_UNUSED(nb12);
GGML_UNUSED(nb13); GGML_UNUSED(nb21); GGML_UNUSED(nb22);
GGML_UNUSED(nb23); GGML_UNUSED(ne0); GGML_UNUSED(ne1);