ikawrakow/ik_llama.cpp
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Slightly better graph parallel for Qwen3-Next (#1307)

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* Make sure we pick the reduced tensor from the right GPU

* Minor
This commit is contained in:
Kawrakow
2026-02-24 15:22:30 +01:00
committed by GitHub
parent cfb6747776
commit 7065488135
4 changed files with 30 additions and 10 deletions
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24
src/llama-build-context.cpp
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@@ -1986,9 +1986,12 @@ static ggml_tensor * build_output(llama_context & lctx, ggml_context * ctx, ggml
}
}
} else {
if (cur->op == GGML_OP_REDUCE && cur->src[lctx.model.main_gpu]) {
int idx = lctx.model.default_layer_device[lctx.model.hparams.n_layer];
int idx_out = ggml_backend_sched_get_backend_idx(lctx.sched, lctx.model.output->buffer);
if (idx_out >= 0) idx = idx_out;
if (cur->op == GGML_OP_REDUCE && cur->src[idx]) {
// avoid copy to main GPU
cur->view_src = cur->src[lctx.model.main_gpu];
cur->view_src = cur->src[idx];
}
if (output_norm) {
cur = llm_build_context::llm_build_norm(ctx, cur, lctx.model.hparams, output_norm, NULL, LLM_NORM_RMS, cb, -1);
@@ -4458,12 +4461,18 @@ ggml_cgraph * llm_build_context::build_qwen3next() {
if (hparams.is_recurrent(il)) {
if (inpL->op == GGML_OP_REDUCE && inpL->src[model.default_layer_device[il]]) {
inpL->view_src = inpL->src[model.default_layer_device[il]];
//printf("Using reduce result on device %d\n", model.default_layer_device[il]);
//inpL = inpL->src[model.default_layer_device[il]];
int idx = model.default_layer_device[il];
if (inpL->op == GGML_OP_REDUCE) {
if (kv_self.s_l[il]) {
// This shouldn't be necessary, but just in case.
int idx_s_l = ggml_backend_sched_get_backend_idx(lctx.sched, kv_self.s_l[il]->buffer);
if (idx_s_l >= 0) idx = idx_s_l;
}
if (inpL->src[idx]) {
inpL->view_src = inpL->src[idx];
}
}
auto norm = model.layers[il].attn_norm->extra ? ((ggml_split_tensor_t *)model.layers[il].attn_norm->extra)->splits[model.default_layer_device[il]] : model.layers[il].attn_norm;
auto norm = model.layers[il].attn_norm->extra ? ((ggml_split_tensor_t *)model.layers[il].attn_norm->extra)->splits[idx] : model.layers[il].attn_norm;
cur = llm_build_norm(ctx0, inpL, hparams, norm, nullptr, LLM_NORM_RMS, cb, il);
cb(cur, "attn_norm", il);
cur = delta.build_layer_attn_linear(ctx0, gf, cur, causal_mask, identity, diag_mask, il, cb);
@@ -4474,7 +4483,6 @@ ggml_cgraph * llm_build_context::build_qwen3next() {
cur = ggml_add(ctx0, cur, inpSA);
cb(cur, "attn_residual", il);
} else {
//cur = build_layer_attn(cur, inp_pos, KQ_mask, il);
cur = build_std_attention(gf, model.layers[il].attn_norm, inpL, inp_pos, il == n_layer - 1 ? inp_out_ids : nullptr, nullptr,
KQ_mask, nullptr, nullptr, KQ_scale, 0.0f, 0, il, true, false, true, false, false);
}