feat: integrate xrip/llama.cpp-avx1-numa-sm75 fork with NCCL & NUMA optimizations

scripts/start-server.sh

@@ -1,7 +1,7 @@
 #!/bin/bash
 # llama-server launcher for Qwen3.8-27B on 3x Turing GPUs (RTX 2060 12GB + 2x CMP 50HX 10GB)
 # Built with NVIDIA NCCL for hardware-accelerated multi-GPU tensor parallelism.
-export LD_LIBRARY_PATH=/opt/llama.cpp/build-nccl/bin:/opt/minicpm-venv/lib/python3.13/site-packages/nvidia/nccl/lib:/lib/x86_64-linux-gnu
+export LD_LIBRARY_PATH=/opt/llama.cpp-xrip/build-nccl/bin:/opt/minicpm-venv/lib/python3.13/site-packages/nvidia/nccl/lib:/lib/x86_64-linux-gnu
 
 # Low-Latency NCCL & CUDA Driver Pipeline Optimizations
 export CUDA_DEVICE_MAX_CONNECTIONS=1
@@ -11,10 +11,11 @@ export NCCL_P2P_DISABLE=0
 export NCCL_ALGO=RING
 export NCCL_PROTO=SIMPLE
 
-exec /opt/llama.cpp/build-nccl/bin/llama-server \
+exec /opt/llama.cpp-xrip/build-nccl/bin/llama-server \
   -m /opt/models/gguf/Qwen3.8-27B-Uncensored-HauhauCS-Aggressive-Q4_K_P.gguf \
   --spec-type draft-mtp \
   --spec-draft-n-max 2 \
+  --numa split \
   -ngl 99 \
   -c 262144 \
   --parallel 1 \