Download or read book XeHE an Intel GPU Accelerated Fully Homomorphic Encryption Library A SYCL Sparkler Making the Most of C and SYCL written by Alexander Lyashevsky and published by James Reinders. This book was released on 2023-04-02 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: This installment of a "SYCL Sparkler" explores in depth a way to implement a reasonably efficient implementation for Homomorphic Encryption using modern C++ with SYCL. As a result of their work, the authors learned some valuable optimization techniques and insights that the they have taken time to share in this very interesting and detailed piece. A key value of using C++ with SYCL, is the ability to be portable while supporting the ability to optimize at a lower level when it is deemed worth the effort. This work helps illustrate how the authors isolated that optimization work, and their thought process on how to pick what to optimize. The code for this implementation is available open source online. None of the performance numbers shown are intended to provide guidance on hardware selection. The authors offer their results and observations to illustrate the magnitude of changes that may correspond to the optimizations being discussed. Readers will find the information valuable to motivate their own optimization work on their applications using some of the techniques highlighted by these authors. Key Insights shared include: pros/cons of a hand-tuned vISA, memory allocation overheads, multi-tile scaling, event-based profiling, algorithm tuning, measuring of device throughput, developing with 'dualities' to increase portability and performance portability.

Download or read book XeHE an Intel GPU Accelerated Fully Homomorphic Encryption Library written by Alexander Lyashevsky and published by Codeplay Software Printing. This book was released on 2023-04-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book CPU and GPU Accelerated Fully Homomorphic Encryption written by Md Toufique Morshed Tamal and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully Homomorphic Encryption (FHE) is one of the most promising technologies for privacy protection as it allows an arbitrary number of function computations over encrypted data. However, the computational cost of these FHE systems limits their widespread applications. In this thesis, our objective is to improve the performance of FHE schemes by designing efficient parallel frameworks. In particular, we choose Torus Fully Homomorphic Encryption (TFHE) as it offers exact results for an infinite number of boolean gate (e.g., AND, XOR) evaluations. We first extend the gate operations to algebraic circuits such as addition, multiplication, and their vector and matrix equivalents. Secondly, we consider the multi-core CPUs to improve the efficiency of both the gate and the arithmetic operations. Finally, we port the TFHE to the Graphics Processing Units (GPU) and device novel optimizations for boolean and arithmetic circuits employing the multitude of cores. We also experimentally analyze both the CPU and GPU parallel frameworks for different numeric representations (16 to 32-bit). Our GPU implementation outperforms the existing techniques, and it achieves a speedup of 20x for any 32-bit boolean operation and 14.5x for multiplications.

Download or read book Accelerating Secure Computations Under Fully Homomorphic Encryption written by Alhassan Khedr and published by . This book was released on 2017 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully homomorphic encryption (FHE) systems enable computations on encrypted data without decrypting and without knowledge of the secret key. In this thesis, we describe an optimized RLWE-based and NTRU-based variants of the FHE system recently proposed by Gentry, Sahai and Waters (GSW). Although the GSW system was widely believed to be less efficient than its contemporaries due to the dimensionality of its ciphertext, we demonstrate quite the opposite behavior. We first highlight and carefully exploit the algebraic features of the system to achieve significant speedup over the state-of-the-art FHE implementations, namely the IBM homomorphic encryption library (HElib) and DARPA's SIPHER implementation. We introduce several optimizations on top of our HE implementation, and use the resulting scheme to construct numerous secure applications. We introduce the first high performance Homomorphic Processing Unit (HPU) hardware accelerator. A carefully crafted parallel GPU implementation of our RLWE scheme running on an NVIDIA GeForce GTX980 achieved a speedup factor of 89,700x compared to DARPA's SIPHER v01 baseline implementation. Our single-staged homomorphic processing unit (HPU) hardware accelerator achieved a speedup factor of 57x compared to our GPU implementation. Our NTRU scheme is mathematically 4x more efficient than our RLWE scheme. In total, our NTRU scheme running on one single-staged HPU unit managed to achieve a combined speedup factor of 2x10^7 compared to DARPA's SIPHER v01 baseline implementation, which is twice the performance target originally set by DARPA's PROCEED program to accelerate fully homomorphic encryption. An additional 4.47x speedup can be achieved by implementing a log(n)-staged HPU unit at the cost of 3x the die area. Finally, by exploiting the computational independence in our FHE schemes and applications, a speedup factor of 10^9 can be achieved by distributing independent computations on 50 single-staged HPU units.