ggml-cpu: extend RVV quantization vec dot to higher VLENs

.devops/intel.Dockerfile

@@ -33,10 +33,10 @@ RUN mkdir -p /app/full \
 
 FROM intel/deep-learning-essentials:$ONEAPI_VERSION AS base
 
-ARG IGC_VERSION=v2.30.1
-ARG IGC_VERSION_FULL=2_2.30.1+20950
-ARG COMPUTE_RUNTIME_VERSION=26.09.37435.1
-ARG COMPUTE_RUNTIME_VERSION_FULL=26.09.37435.1-0
+ARG IGC_VERSION=v2.32.7
+ARG IGC_VERSION_FULL=2_2.32.7+21184
+ARG COMPUTE_RUNTIME_VERSION=26.14.37833.4
+ARG COMPUTE_RUNTIME_VERSION_FULL=26.14.37833.4-0
 ARG IGDGMM_VERSION=22.9.0
 RUN mkdir /tmp/neo/ && cd /tmp/neo/ \
   && wget https://github.com/intel/intel-graphics-compiler/releases/download/$IGC_VERSION/intel-igc-core-${IGC_VERSION_FULL}_amd64.deb \

.devops/nix/package.nix

@@ -103,6 +103,7 @@ let
     vulkan-headers
     vulkan-loader
     shaderc
+    spirv-headers
   ];
 in
 
@@ -146,7 +147,6 @@ effectiveStdenv.mkDerivation (finalAttrs: {
       ninja
       pkg-config
       git
-      spirv-headers
     ]
     ++ optionals useCuda [
       cudaPackages.cuda_nvcc

.github/workflows/build-virtgpu.yml

@@ -0,0 +1,50 @@
+name: CI (virtgpu)
+
+on:
+  workflow_dispatch: # allows manual triggering
+  push:
+    branches:
+      - master
+    paths: [
+      '.github/workflows/build-virtgpu.yml',
+      '**/CMakeLists.txt',
+      '**/.cmake',
+      '**/*.h',
+      '**/*.hpp',
+      '**/*.c',
+      '**/*.cpp'
+    ]
+
+  pull_request:
+    types: [opened, synchronize, reopened]
+    paths: [
+      '.github/workflows/build-virtgpu.yml',
+      'ggml/src/ggml-virtgpu/**'
+    ]
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref && github.ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  ubuntu-24-virtgpu:
+    runs-on: ${{ 'ubuntu-24.04-arm' || 'ubuntu-24.04' }}
+
+    steps:
+      - name: Clone
+        id: checkout
+        uses: actions/checkout@v6
+
+      - name: Dependencies
+        id: depends
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y build-essential libdrm-dev pkg-config libssl-dev
+
+      - name: Build
+        id: cmake_build
+        run: |
+          cmake -B build \
+            -DGGML_VIRTGPU=ON \
+            -DGGML_VIRTGPU_BACKEND=ON
+          cmake --build build --config Release -j $(nproc)

.github/workflows/python-type-check.yml

@@ -31,7 +31,7 @@ jobs:
         uses: actions/setup-python@v6
         with:
           python-version: "3.11"
-          pip-install: -r requirements/requirements-all.txt ty==0.0.33
+          pip-install: -r requirements/requirements-all.txt ty==0.0.35
       # - name: Type-check with Pyright
       #   uses: jakebailey/pyright-action@v2
       #   with:

.gitignore

@@ -110,6 +110,7 @@ uv.lock
 
 # Nix
 
+flake.lock
 /result
 
 # Test binaries

CODEOWNERS

@@ -76,6 +76,7 @@
 /ggml/src/ggml-vulkan/                  @ggml-org/ggml-vulkan
 /ggml/src/ggml-webgpu/                  @ggml-org/ggml-webgpu
 /ggml/src/ggml-zdnn/                    @ggml-org/ggml-zdnn @Andreas-Krebbel @AlekseiNikiforovIBM
+/ggml/src/ggml-zendnn/                  @avinashcpandey @Jiten1parmar @z-vishal
 /ggml/src/ggml.c                        @ggerganov
 /ggml/src/ggml.cpp                      @ggerganov
 /ggml/src/gguf.cpp                      @JohannesGaessler @Green-Sky

README.md

@@ -529,6 +529,7 @@ To learn more about model quantization, [read this documentation](tools/quantize
 - [How to build](docs/build.md)
 - [Running on Docker](docs/docker.md)
 - [Build on Android](docs/android.md)
+- [Multi-GPU usage](docs/multi-gpu.md)
 - [Performance troubleshooting](docs/development/token_generation_performance_tips.md)
 - [GGML tips & tricks](https://github.com/ggml-org/llama.cpp/wiki/GGML-Tips-&-Tricks)
 

common/arg.cpp

@@ -622,10 +622,6 @@ static bool common_params_parse_ex(int argc, char ** argv, common_params_context
         for (auto & seq_breaker : params.sampling.dry_sequence_breakers) {
             string_process_escapes(seq_breaker);
         }
-        for (auto & pair : params.speculative.draft.replacements) {
-            string_process_escapes(pair.first);
-            string_process_escapes(pair.second);
-        }
     }
 
     if (!params.kv_overrides.empty()) {
@@ -3518,13 +3514,6 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
             params.speculative.draft.p_min = std::stof(value);
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_P_MIN"));
-    add_opt(common_arg(
-        {"--spec-draft-ctx-size", "-cd", "--ctx-size-draft"}, "N",
-        string_format("size of the prompt context for the draft model (default: %d, 0 = loaded from model)", params.speculative.draft.n_ctx),
-        [](common_params & params, int value) {
-            params.speculative.draft.n_ctx = value;
-        }
-    ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_CTX_SIZE"));
     add_opt(common_arg(
         {"--spec-draft-device", "-devd", "--device-draft"}, "<dev1,dev2,..>",
         "comma-separated list of devices to use for offloading the draft model (none = don't offload)\n"
@@ -3561,32 +3550,12 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_DRAFT_MODEL"));
     add_opt(common_arg(
-        {"--spec-draft-replace", "--spec-replace"}, "TARGET", "DRAFT",
-        "translate the string in TARGET into DRAFT if the draft model and main model are not compatible",
-        [](common_params & params, const std::string & tgt, const std::string & dft) {
-            params.speculative.draft.replacements.push_back({ tgt, dft });
-        }
-    ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}));
-    add_opt(common_arg(
-        {"--spec-type"}, "[none|ngram-cache|ngram-simple|ngram-map-k|ngram-map-k4v|ngram-mod]",
+        {"--spec-type"}, common_speculative_all_types_str(),
         string_format("type of speculative decoding to use when no draft model is provided (default: %s)\n",
-            common_speculative_type_to_str(params.speculative.type).c_str()),
+            common_speculative_type_name_str(params.speculative.types).c_str()),
         [](common_params & params, const std::string & value) {
-            if (value == "none") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NONE;
-            } else if (value == "ngram-cache") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_CACHE;
-            } else if (value == "ngram-simple") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_SIMPLE;
-            } else if (value == "ngram-map-k") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K;
-            } else if (value == "ngram-map-k4v") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MAP_K4V;
-            } else if (value == "ngram-mod") {
-                params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MOD;
-            } else {
-                throw std::invalid_argument("unknown speculative decoding type without draft model");
-            }
+            const auto enabled_types = string_split<std::string>(value, ',');
+            params.speculative.types = common_speculative_types_from_names(enabled_types);
         }
     ).set_spec().set_examples({LLAMA_EXAMPLE_SPECULATIVE, LLAMA_EXAMPLE_SERVER, LLAMA_EXAMPLE_CLI}).set_env("LLAMA_ARG_SPEC_TYPE"));
     add_opt(common_arg(
@@ -4075,7 +4044,7 @@ common_params_context common_params_parser_init(common_params & params, llama_ex
         {"--spec-default"},
         string_format("enable default speculative decoding config"),
         [](common_params & params) {
-            params.speculative.type = COMMON_SPECULATIVE_TYPE_NGRAM_MOD;
+            params.speculative.types = { COMMON_SPECULATIVE_TYPE_NGRAM_MOD };
             params.speculative.ngram_mod.n_match = 24;
             params.speculative.ngram_mod.n_min = 48;
             params.speculative.ngram_mod.n_max = 64;

common/chat-auto-parser-generator.cpp

@@ -369,9 +369,7 @@ common_peg_parser analyze_tools::build_tool_parser_tag_tagged(parser_build_conte
                                            arguments.name_suffix) +
                            arguments.value_prefix +
                            (schema_info.resolves_to_string(param_schema) ?
-                                p.tool_arg_string_value(p.schema(until_suffix,
-                                                                 "tool-" + name + "-arg-" + param_name + "-schema",
-                                                                 param_schema, true)) :
+                                p.tool_arg_string_value(until_suffix) :
                                 p.tool_arg_json_value(p.schema(
                                     p.json(), "tool-" + name + "-arg-" + param_name + "-schema", param_schema, false)) +
                                     p.space()) +

common/chat.cpp

@@ -80,7 +80,7 @@ json common_chat_msg::to_json_oaicompat(bool concat_typed_text) const {
     if (!content.empty()) {
         jmsg["content"] = content;
     } else if (!content_parts.empty()) {
-        if (concat_typed_text) {
+        if (concat_typed_text || contains_media()) {
             std::string text;
             bool last_was_media_marker = false;
             // join parts with newline, do not add newline before or after media markers

common/chat.h

@@ -94,6 +94,15 @@ struct common_chat_msg {
                tool_name.empty() && tool_call_id.empty();
     }
 
+    bool contains_media() const {
+        for (const auto & part : content_parts) {
+            if (part.type == "media_marker") {
+                return true;
+            }
+        }
+        return false;
+    }
+
     void set_tool_call_ids(std::vector<std::string> &           ids_cache,
                            const std::function<std::string()> & gen_tool_call_id) {
         for (auto i = 0u; i < tool_calls.size(); i++) {

common/common.cpp

@@ -1422,7 +1422,7 @@ common_context_seq_rm_type common_context_can_seq_rm(llama_context * ctx) {
 
     // try to remove the last tokens
     if (!llama_memory_seq_rm(mem, 0, 1, -1)) {
-        LOG_WRN("%s: the target context does not support partial sequence removal\n", __func__);
+        LOG_WRN("%s: the context does not support partial sequence removal\n", __func__);
         res = COMMON_CONTEXT_SEQ_RM_TYPE_FULL;
         goto done;
     }
@@ -1960,3 +1960,102 @@ bool common_prompt_batch_decode(
 
     return true;
 }
+
+size_t common_prompt_checkpoint::size() const {
+    return data_tgt.size() + data_dft.size();
+}
+
+bool common_prompt_checkpoint::empty() const {
+    return data_tgt.empty();
+}
+
+void common_prompt_checkpoint::clear() {
+    n_tokens = 0;
+
+    pos_min = 0;
+    pos_max = 0;
+
+    data_tgt.clear();
+    data_dft.clear();
+}
+
+void common_prompt_checkpoint::update_pos(
+        int64_t n_tokens,
+        llama_pos pos_min,
+        llama_pos pos_max) {
+    this->n_tokens = n_tokens;
+    this->pos_min  = pos_min;
+    this->pos_max  = pos_max;
+}
+
+void common_prompt_checkpoint::update_tgt(
+        llama_context * ctx,
+        llama_seq_id seq_id,
+        llama_state_seq_flags flags) {
+    if (ctx == nullptr) {
+        return;
+    }
+
+    const size_t ckpt_size = llama_state_seq_get_size_ext(ctx, seq_id, flags);
+
+    data_tgt.resize(ckpt_size);
+
+    const size_t n = llama_state_seq_get_data_ext(ctx, data_tgt.data(), ckpt_size, seq_id, flags);
+    if (n != ckpt_size) {
+        GGML_ABORT("checkpoint size mismatch: expected %zu, got %zu\n", ckpt_size, n);
+    }
+}
+
+void common_prompt_checkpoint::update_dft(
+        llama_context * ctx,
+        llama_seq_id seq_id,
+        llama_state_seq_flags flags) {
+    if (ctx == nullptr) {
+        return;
+    }
+
+    const size_t ckpt_size = llama_state_seq_get_size_ext(ctx, seq_id, flags);
+
+    data_dft.resize(ckpt_size);
+
+    const size_t n = llama_state_seq_get_data_ext(ctx, data_dft.data(), ckpt_size, seq_id, flags);
+    if (n != ckpt_size) {
+        GGML_ABORT("checkpoint size mismatch: expected %zu, got %zu\n", ckpt_size, n);
+    }
+}
+
+void common_prompt_checkpoint::load_tgt(
+        llama_context * ctx,
+        llama_seq_id seq_id,
+        llama_state_seq_flags flags) const {
+    if (ctx == nullptr) {
+        return;
+    }
+
+    if (data_tgt.empty()) {
+        return;
+    }
+
+    const size_t n = llama_state_seq_set_data_ext(ctx, data_tgt.data(), data_tgt.size(), seq_id, flags);
+    if (n != data_tgt.size()) {
+        GGML_ABORT("checkpoint size mismatch: expected %zu, got %zu\n", data_tgt.size(), n);
+    }
+}
+
+void common_prompt_checkpoint::load_dft(
+        llama_context * ctx,
+        llama_seq_id seq_id,
+        llama_state_seq_flags flags) const {
+    if (ctx == nullptr) {
+        return;
+    }
+
+    if (data_dft.empty()) {
+        return;
+    }
+
+    const size_t n = llama_state_seq_set_data_ext(ctx, data_dft.data(), data_dft.size(), seq_id, flags);
+    if (n != data_dft.size()) {
+        GGML_ABORT("checkpoint size mismatch: expected %zu, got %zu\n", data_dft.size(), n);
+    }
+}