mirror of
https://github.com/dogkeeper886/ollama37.git
synced 2025-12-18 03:37:09 +00:00
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with comprehensive build instructions - Documented toolchain constraints and CPU architecture trade-offs - Removed outdated CI/CD workflows (tesla-k80-*.yml) - Cleaned up temporary development artifacts ## Rationale This fork maintains Tesla K80 GPU support (compute 3.7) which was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>
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@@ -148,7 +148,12 @@ func Parse(s string) (*Template, error) {
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}
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t := Template{Template: tmpl, raw: s}
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if vars := t.Vars(); !slices.Contains(vars, "messages") && !slices.Contains(vars, "response") {
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vars, err := t.Vars()
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if err != nil {
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return nil, err
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}
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if !slices.Contains(vars, "messages") && !slices.Contains(vars, "response") {
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// touch up the template and append {{ .Response }}
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tmpl.Tree.Root.Nodes = append(tmpl.Tree.Root.Nodes, &response)
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}
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@@ -160,11 +165,15 @@ func (t *Template) String() string {
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return t.raw
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}
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func (t *Template) Vars() []string {
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func (t *Template) Vars() ([]string, error) {
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var vars []string
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for _, tt := range t.Templates() {
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for _, n := range tt.Root.Nodes {
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vars = append(vars, Identifiers(n)...)
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v, err := Identifiers(n)
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if err != nil {
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return vars, err
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}
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vars = append(vars, v...)
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}
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}
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@@ -173,7 +182,7 @@ func (t *Template) Vars() []string {
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set[strings.ToLower(n)] = struct{}{}
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}
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return slices.Sorted(maps.Keys(set))
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return slices.Sorted(maps.Keys(set)), nil
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}
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func (t *Template) Contains(s string) bool {
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@@ -244,6 +253,10 @@ func (t *Template) Subtree(fn func(parse.Node) bool) *template.Template {
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func (t *Template) Execute(w io.Writer, v Values) error {
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system, messages := collate(v.Messages)
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vars, err := t.Vars()
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if err != nil {
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return err
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}
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if v.Prompt != "" && v.Suffix != "" {
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return t.Template.Execute(w, map[string]any{
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"Prompt": v.Prompt,
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@@ -253,7 +266,7 @@ func (t *Template) Execute(w io.Writer, v Values) error {
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"ThinkLevel": v.ThinkLevel,
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"IsThinkSet": v.IsThinkSet,
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})
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} else if !v.forceLegacy && slices.Contains(t.Vars(), "messages") {
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} else if !v.forceLegacy && slices.Contains(vars, "messages") {
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return t.Template.Execute(w, map[string]any{
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"System": system,
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"Messages": messages,
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@@ -329,7 +342,7 @@ func (t *Template) Execute(w io.Writer, v Values) error {
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return err
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}
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_, err := io.Copy(w, &b)
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_, err = io.Copy(w, &b)
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return err
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}
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@@ -358,27 +371,47 @@ func collate(msgs []api.Message) (string, []*api.Message) {
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}
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// Identifiers walks the node tree returning any identifiers it finds along the way
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func Identifiers(n parse.Node) []string {
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func Identifiers(n parse.Node) ([]string, error) {
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switch n := n.(type) {
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case *parse.ListNode:
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var names []string
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for _, n := range n.Nodes {
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names = append(names, Identifiers(n)...)
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i, err := Identifiers(n)
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if err != nil {
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return names, err
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}
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names = append(names, i...)
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}
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return names
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return names, nil
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case *parse.TemplateNode:
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if n.Pipe == nil {
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return nil, errors.New("undefined template specified")
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}
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return Identifiers(n.Pipe)
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case *parse.ActionNode:
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if n.Pipe == nil {
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return nil, errors.New("undefined action in template")
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}
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return Identifiers(n.Pipe)
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case *parse.BranchNode:
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names := Identifiers(n.Pipe)
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if n.Pipe == nil {
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return nil, errors.New("undefined branch")
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}
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names, err := Identifiers(n.Pipe)
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if err != nil {
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return names, err
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}
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for _, n := range []*parse.ListNode{n.List, n.ElseList} {
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if n != nil {
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names = append(names, Identifiers(n)...)
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i, err := Identifiers(n)
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if err != nil {
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return names, err
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}
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names = append(names, i...)
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}
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}
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return names
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return names, nil
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case *parse.IfNode:
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return Identifiers(&n.BranchNode)
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case *parse.RangeNode:
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@@ -389,17 +422,21 @@ func Identifiers(n parse.Node) []string {
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var names []string
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for _, c := range n.Cmds {
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for _, a := range c.Args {
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names = append(names, Identifiers(a)...)
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i, err := Identifiers(a)
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if err != nil {
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return names, err
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}
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names = append(names, i...)
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}
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}
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return names
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return names, nil
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case *parse.FieldNode:
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return n.Ident
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return n.Ident, nil
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case *parse.VariableNode:
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return n.Ident
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return n.Ident, nil
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}
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return nil
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return nil, nil
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}
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// deleteNode walks the node list and deletes nodes that match the predicate
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