Hardware Acceleration for Fully Homomorphic Encryption

The hardware acceleration of fully homomorphic encryption (FHE) is of paramount importance in advancing the field of secure computing and data privacy. FHE allows computations to be performed on encrypted data without the need for decryption, thereby ensuring end-to-end confidentiality. However, the computational overhead associated with FHE has historically been a bottleneck, hindering its practical implementation. Hardware acceleration addresses this challenge by optimizing the performance of FHE algorithms, enabling faster and more efficient computations on encrypted data along with optimized memory utilization. This acceleration is crucial in various applications, ranging from secure cloud computing and confidential data sharing to privacy-preserving machine learning. As the demand for robust data protection increases, the significance of hardware acceleration in making FHE viable for real-world scenarios becomes increasingly evident, promoting the adoption of secure and privacy-preserving technologies in the digital age. I am currently working with AMD and couple of research fellows to develop hardware acceleration for FHE using commercial architectural synthesis tools like Synopsys ASIP Designer.