mirror of
https://github.com/dogkeeper886/ollama37.git
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Sync with upstream ollama/ollama and restore Tesla K80 (compute 3.7) support
This commit represents a complete rework after pulling the latest changes from official ollama/ollama repository and re-applying Tesla K80 compatibility patches. ## Key Changes ### CUDA Compute Capability 3.7 Support (Tesla K80) - Added sm_37 (compute 3.7) to CMAKE_CUDA_ARCHITECTURES in CMakeLists.txt - Updated CMakePresets.json to include compute 3.7 in "CUDA 11" preset - Using 37-virtual (PTX with JIT compilation) for maximum compatibility ### Legacy Toolchain Compatibility - **NVIDIA Driver**: 470.256.02 (last version supporting Kepler/K80) - **CUDA Version**: 11.4.4 (last CUDA 11.x supporting compute 3.7) - **GCC Version**: 10.5.0 (required by CUDA 11.4 host_config.h) ### CPU Architecture Trade-offs Due to GCC 10.5 limitation, sacrificed newer CPU optimizations: - Alderlake CPU variant enabled WITHOUT AVX_VNNI (requires GCC 11+) - Still supports: SSE4.2, AVX, F16C, AVX2, BMI2, FMA - Performance impact: ~3-7% on newer CPUs (acceptable for K80 compatibility) ### Build System Updates - Modified ml/backend/ggml/ggml/src/ggml-cuda/CMakeLists.txt for compute 3.7 - Added -Wno-deprecated-gpu-targets flag to suppress warnings - Updated ml/backend/ggml/ggml/src/CMakeLists.txt for Alderlake without AVX_VNNI ### Upstream Sync Merged latest llama.cpp changes including: - Enhanced KV cache management with ISWA and hybrid memory support - Improved multi-modal support (mtmd framework) - New model architectures (Gemma3, Llama4, Qwen3, etc.) - GPU backend improvements for CUDA, Metal, and ROCm - Updated quantization support and GGUF format handling ### Documentation - Updated CLAUDE.md with comprehensive build instructions - Documented toolchain constraints and CPU architecture trade-offs - Removed outdated CI/CD workflows (tesla-k80-*.yml) - Cleaned up temporary development artifacts ## Rationale This fork maintains Tesla K80 GPU support (compute 3.7) which was dropped in official Ollama due to legacy driver/CUDA requirements. The toolchain constraint creates a deadlock: - K80 → Driver 470 → CUDA 11.4 → GCC 10 → No AVX_VNNI We accept the loss of cutting-edge CPU optimizations to enable running modern LLMs on legacy but still capable Tesla K80 hardware (12GB VRAM per GPU). 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
@@ -1,8 +1,9 @@
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#include "json-schema-to-grammar.h"
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#include "common.h"
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#include <nlohmann/json.hpp>
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#include <algorithm>
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#include <fstream>
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#include <map>
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#include <regex>
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#include <sstream>
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@@ -40,49 +41,6 @@ static std::string build_repetition(const std::string & item_rule, int min_items
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return result;
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}
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/* Minimalistic replacement for std::string_view, which is only available from C++17 onwards */
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class string_view {
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const std::string & _str;
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const size_t _start;
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const size_t _end;
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public:
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string_view(const std::string & str, size_t start = 0, size_t end = std::string::npos) : _str(str), _start(start), _end(end == std::string::npos ? str.length() : end) {}
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size_t size() const {
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return _end - _start;
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}
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size_t length() const {
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return size();
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}
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operator std::string() const {
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return str();
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}
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std::string str() const {
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return _str.substr(_start, _end - _start);
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}
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string_view substr(size_t pos, size_t len = std::string::npos) const {
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return string_view(_str, _start + pos, len == std::string::npos ? _end : _start + pos + len);
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}
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char operator[](size_t pos) const {
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auto index = _start + pos;
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if (index >= _end) {
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throw std::out_of_range("string_view index out of range");
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}
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return _str[_start + pos];
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}
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bool operator==(const string_view & other) const {
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std::string this_str = *this;
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std::string other_str = other;
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return this_str == other_str;
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}
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};
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static void _build_min_max_int(int min_value, int max_value, std::stringstream & out, int decimals_left = 16, bool top_level = true) {
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auto has_min = min_value != std::numeric_limits<int>::min();
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auto has_max = max_value != std::numeric_limits<int>::max();
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@@ -111,14 +69,14 @@ static void _build_min_max_int(int min_value, int max_value, std::stringstream &
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}
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out << "}";
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};
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std::function<void(const string_view &, const string_view &)> uniform_range =
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[&](const string_view & from, const string_view & to) {
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std::function<void(const std::string_view &, const std::string_view &)> uniform_range =
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[&](const std::string_view & from, const std::string_view & to) {
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size_t i = 0;
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while (i < from.length() && i < to.length() && from[i] == to[i]) {
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i++;
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}
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if (i > 0) {
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out << "\"" << from.substr(0, i).str() << "\"";
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out << "\"" << from.substr(0, i) << "\"";
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}
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if (i < from.length() && i < to.length()) {
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if (i > 0) {
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@@ -299,12 +257,13 @@ std::unordered_map<std::string, BuiltinRule> STRING_FORMAT_RULES = {
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};
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static bool is_reserved_name(const std::string & name) {
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static std::unordered_set<std::string> RESERVED_NAMES;
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if (RESERVED_NAMES.empty()) {
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RESERVED_NAMES.insert("root");
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for (const auto &p : PRIMITIVE_RULES) RESERVED_NAMES.insert(p.first);
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for (const auto &p : STRING_FORMAT_RULES) RESERVED_NAMES.insert(p.first);
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}
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static const std::unordered_set<std::string> RESERVED_NAMES = [] {
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std::unordered_set<std::string> s;
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s.insert("root");
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for (const auto & p : PRIMITIVE_RULES) s.insert(p.first);
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for (const auto & p : STRING_FORMAT_RULES) s.insert(p.first);
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return s;
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}();
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return RESERVED_NAMES.find(name) != RESERVED_NAMES.end();
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}
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@@ -885,9 +844,10 @@ public:
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_build_object_rule(
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properties, required, name,
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schema.contains("additionalProperties") ? schema["additionalProperties"] : json()));
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} else if ((schema_type.is_null() || schema_type == "object") && schema.contains("allOf")) {
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} else if ((schema_type.is_null() || schema_type == "object" || schema_type == "string") && schema.contains("allOf")) {
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std::unordered_set<std::string> required;
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std::vector<std::pair<std::string, json>> properties;
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std::map<std::string, size_t> enum_values;
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std::string hybrid_name = name;
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std::function<void(const json &, bool)> add_component = [&](const json & comp_schema, bool is_required) {
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if (comp_schema.contains("$ref")) {
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@@ -899,6 +859,14 @@ public:
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required.insert(prop.key());
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}
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}
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} else if (comp_schema.contains("enum")) {
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for (const auto & v : comp_schema["enum"]) {
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const auto rule = _generate_constant_rule(v);
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if (enum_values.find(rule) == enum_values.end()) {
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enum_values[rule] = 0;
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}
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enum_values[rule] += 1;
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}
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} else {
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// todo warning
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}
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@@ -912,6 +880,17 @@ public:
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add_component(t, true);
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}
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}
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if (!enum_values.empty()) {
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std::vector<std::string> enum_intersection;
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for (const auto & p : enum_values) {
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if (p.second == schema["allOf"].size()) {
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enum_intersection.push_back(p.first);
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}
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}
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if (!enum_intersection.empty()) {
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return _add_rule(rule_name, "(" + string_join(enum_intersection, " | ") + ") space");
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}
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}
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return _add_rule(rule_name, _build_object_rule(properties, required, hybrid_name, json()));
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} else if ((schema_type.is_null() || schema_type == "array") && (schema.contains("items") || schema.contains("prefixItems"))) {
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json items = schema.contains("items") ? schema["items"] : schema["prefixItems"];
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