I. INTRODUCTION  
II. BASIC CONCEPTS  
A. The lifecycle of the foundation model system  
B. Transformer for foundation models  
III. MODEL TRAINING  
A. Advanced Techniques in Parallel Computing  
B. GPU Memory Optimization In Training  
C. Communication Optimization  
IV. MODEL SERVING  
A. Batch Processing Optimization  
B. Sparse Acceleration Techniques  
C. Resource Scheduling Optimization  
D. GPU Memory Optimization In Inference  
E. Multi-Model Inference  
V. CHALLENGES AND FUTURE DIRECTIONS  
VI. CONCLUSION