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

@@ -191,6 +191,14 @@ struct llama_hparams {
// dimension of value embeddings across all k-v heads
uint32_t n_embd_v_gqa(uint32_t il = 0) const;
// true if any layer has a different n_embd_k_gqa/n_embd_v_gqa
bool is_n_embd_k_gqa_variable() const;
bool is_n_embd_v_gqa_variable() const;
// return the maximum n_embd_k_gqa/n_embd_v_gqa across all layers
uint32_t n_embd_k_gqa_max() const;
uint32_t n_embd_v_gqa_max() const;
// dimension of the rolling state embeddings
// corresponds to Mamba's conv_states size or RWKV's token_shift states size
uint32_t n_embd_r() const;