Update README with new LLM frameworks

Author: jrhemstad

README.md

@@ -511,8 +511,11 @@ Does your project use CCCL? [Open a PR to add your project to this list!](https:
 - [Qiskit](https://github.com/Qiskit/qiskit-aer) - High performance simulator for quantum circuits
 - [QUDA](https://github.com/lattice/quda) - Lattice quantum chromodynamics (QCD) computations
 - [RAFT](https://github.com/rapidsai/raft) - Algorithms and primitives for machine learning
+- [SGLang](https://github.com/sgl-project/sglang) - LLM serving framework 
 - [TensorFlow](https://github.com/tensorflow/tensorflow) - End-to-end platform for machine learning
 - [TensorRT](https://github.com/NVIDIA/TensorRT) - Deep learning inference
+- [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM) - Optimized LLM inference
 - [tsne-cuda](https://github.com/CannyLab/tsne-cuda) - Stochastic Neighborhood Embedding library
 - [Visualization Toolkit (VTK)](https://gitlab.kitware.com/vtk/vtk) - Rendering and visualization library
+- [vLLM](https://github.com/vllm-project/vllm) - LLM inference and serving
 - [XGBoost](https://github.com/dmlc/xgboost) - Gradient boosting machine learning algorithms