mirror of
https://github.com/dogkeeper886/ollama37.git
synced 2025-12-10 15:57:04 +00:00
ef14fb5b26
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with comprehensive build instructions - Documented toolchain constraints and CPU architecture trade-offs - Removed outdated CI/CD workflows (tesla-k80-*.yml) - Cleaned up temporary development artifacts ## Rationale This fork maintains Tesla K80 GPU support (compute 3.7) which was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>
47 lines
1.4 KiB
Diff
47 lines
1.4 KiB
Diff
From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
|
|
From: Gabe Goodhart <ghart@us.ibm.com>
|
|
Date: Tue, 24 Jun 2025 16:55:31 -0600
|
|
Subject: [PATCH] add C API for mtmd_input_text
|
|
|
|
Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
|
|
---
|
|
tools/mtmd/mtmd.cpp | 10 ++++++++++
|
|
tools/mtmd/mtmd.h | 3 +++
|
|
2 files changed, 13 insertions(+)
|
|
|
|
diff --git a/tools/mtmd/mtmd.cpp b/tools/mtmd/mtmd.cpp
|
|
index 4d487581..35a0d25e 100644
|
|
--- a/tools/mtmd/mtmd.cpp
|
|
+++ b/tools/mtmd/mtmd.cpp
|
|
@@ -79,6 +79,16 @@ enum mtmd_slice_tmpl {
|
|
MTMD_SLICE_TMPL_IDEFICS3,
|
|
};
|
|
|
|
+mtmd_input_text* mtmd_input_text_init(const char * text, bool add_special, bool parse_special) {
|
|
+ return new mtmd_input_text{text, add_special, parse_special};
|
|
+}
|
|
+
|
|
+void mtmd_input_text_free(mtmd_input_text* input_text) {
|
|
+ if (input_text) {
|
|
+ delete input_text;
|
|
+ }
|
|
+}
|
|
+
|
|
const char * mtmd_default_marker() {
|
|
return "<__media__>";
|
|
}
|
|
diff --git a/tools/mtmd/mtmd.h b/tools/mtmd/mtmd.h
|
|
index f4ea07d3..cf287224 100644
|
|
--- a/tools/mtmd/mtmd.h
|
|
+++ b/tools/mtmd/mtmd.h
|
|
@@ -75,6 +75,9 @@ typedef struct mtmd_input_chunk mtmd_input_chunk;
|
|
typedef struct mtmd_input_chunks mtmd_input_chunks;
|
|
typedef struct mtmd_input_text mtmd_input_text;
|
|
|
|
+MTMD_API mtmd_input_text* mtmd_input_text_init(const char * text, bool add_special, bool parse_special);
|
|
+MTMD_API void mtmd_input_text_free(mtmd_input_text* input_text);
|
|
+
|
|
struct mtmd_context_params {
|
|
bool use_gpu;
|
|
bool print_timings;
|