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Taiyi: A High-Performance CKKS Accelerator for Practical Fully Homomorphic Encryption


Core Concepts
Optimizing performance for KLSS-based FHE applications through algorithmic derivation and hardware design.
Abstract
The article discusses the challenges faced by existing accelerators in executing FHE applications optimized with the KLSS method. It introduces Taiyi, a new accelerator designed to enhance performance by optimizing components such as NTT, BConv, and IP operations. The focus is on reducing computational overhead and improving efficiency for KeySwitch operations. Taiyi integrates specialized components like HP-IP for parallel IP operations and E-Key Buffer for storing evaluation keys. Dataflow optimization is crucial to streamline batch-level processing and reduce redundant NTT operations. Compiler-assisted optimization helps dynamically select optimal α values for different multiplicative levels in FHE applications.
Stats
The bottleneck of FHE applications shifts from NTT to the inner-product operation. Average performance improvement of 1.5× with Taiyi compared to previous designs. Area overhead reduced by 15.7% with Taiyi.
Quotes
"The bottleneck of the FHE application has shifted from the NTT operation to the IP operation." "Taiyi integrates specialized components like HP-IP for parallel IP operations and E-Key Buffer for storing evaluation keys."

Key Insights Distilled From

by Shengyu Fan,... at arxiv.org 03-18-2024

https://arxiv.org/pdf/2403.10188.pdf
Taiyi

Deeper Inquiries

How can domain-specific accelerators like Taiyi contribute to making FHE a practical reality

Domain-specific accelerators like Taiyi can contribute to making FHE a practical reality by optimizing the performance of FHE applications. By designing specialized hardware components and refining data flow, accelerators like Taiyi can significantly enhance the efficiency of key operations in FHE algorithms, such as Inner Product (IP) and Basis Conversion (BConv). This optimization leads to improved execution times for FHE applications, bringing them closer to real-world applicability. Additionally, by incorporating dynamic parameter selection schemes and compiler-assisted optimizations, domain-specific accelerators ensure that FHE applications run efficiently across various multiplicative levels. Overall, these advancements help bridge the gap between theoretical cryptographic concepts and practical implementation in real-world scenarios.

What are potential drawbacks or limitations of optimizing FHE accelerators based on specific algorithms like KLSS

One potential drawback or limitation of optimizing FHE accelerators based on specific algorithms like KLSS is the need for continuous adaptation to evolving cryptographic techniques. While KLSS may offer significant performance improvements for certain aspects of FHE operations, it also introduces new challenges that require dedicated hardware design and algorithmic optimizations. As cryptography continues to advance rapidly with new algorithm-level optimizations being developed regularly, there is a risk that specialized accelerators optimized for specific algorithms may become less effective over time if they are not easily adaptable to changing encryption methods. Therefore, constant updates and modifications may be necessary to ensure that these accelerators remain efficient and relevant in an ever-evolving cryptographic landscape.

How can advancements in cryptography impact the design and optimization of future FHE accelerators

Advancements in cryptography have a profound impact on the design and optimization of future FHE accelerators by influencing key aspects such as algorithm selection, parameter tuning, and security considerations. As new cryptographic techniques emerge or existing ones are refined, future FHE accelerators must be able to adapt quickly to incorporate these advancements effectively. For example: Algorithm Selection: Cryptographic breakthroughs often lead to more efficient encryption schemes or protocols that can improve overall performance in homomorphic encryption tasks. Parameter Tuning: Changes in security requirements or computational complexity due to advances in cryptography may necessitate adjustments in parameters used by FHE algorithms within accelerator designs. Security Considerations: Enhanced security measures introduced through novel cryptographic methods must be integrated into accelerator architectures to uphold data privacy standards while maintaining high-performance capabilities. By staying abreast of developments in cryptography and aligning their designs with cutting-edge encryption technologies, future FHE accelerators can continue pushing boundaries towards making fully homomorphic encryption a practical reality across diverse application domains.
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