Cloud outsourcing has become critical for computing vast amounts of data for emerging applications, such as machine learning, bio-medical analysis, private information retrieval, etc. However, sharing data to the cloud may leak sensitive information, leading to various societal issues, including identity theft, financial loss, reputational damage, and legal consequences. Fully homomorphic encryption (FHE) is a post-quantum cryptography framework that supports computations directly on encrypted data, providing strong protection for sensitive data that remains encrypted during data transmission and cloud services. Despite the benefits, adopting FHE in real-world applications is challenging in (1) transforming application data and operations into encrypted ciphertexts and operations with restricted formats using various complex algorithmic schemes and (2) porting and optimizing on different computing hardware platforms that are critical for ensuring a practical runtime. The project's broader significance and importance are: (1) boosting the development and development of FHE to advance the national welfare by protecting data privacy in broader domains, and (2) promoting the progress of computer science and engineering to improve the availability and performance of privacy-preserving data sharing and analytics. This project develops a novel programming and compilation framework for exploiting FHE in general privacy-preserving applications on real systems. This project's nove