Design of microprocessor-based hardware for number theoretic transform implementation

Number Theoretic Transforms (NTTs) are defined in a finite ring of integers Z (_M), where M is the modulus. All the arithmetic operations are carried out modulo M. NTTs are similar in structure to DFTs, hence fast FFT type algorithms may be used to compute NTTs efficiently. A major advantage of the NTT is that it can be used to compute error free convolutions, unlike the FFT it is not subject to round off and truncation errors. In 1976 Winograd proposed a set of short length DFT algorithms using a fewer number of multiplications and approximately the same number of additions as the Cooley-Tukey FFT algorithm. This saving is accomplished at the expense of increased algorithm complexity. These short length DFT algorithms may be combined to perform longer transforms. The Winograd Fourier Transform Algorithm (WFTA) was implemented on a TMS9900 microprocessor to compute NTTs. Since multiplication conducted modulo M is very time consuming a special purpose external hardware modular multiplier was designed, constructed and interfaced with the TMS9900 microprocessor. This external hardware modular multiplier allowed an improvement in the transform execution time. Computation time may further be reduced by employing several microprocessors. Taking advantage of the inherent parallelism of the WFTA, a dedicated parallel microprocessor system was designed and constructed to implement a 15-point WFTA in parallel. Benchmark programs were written to choose a suitable microprocessor for the parallel microprocessor system. A master or a host microprocessor is used to control the parallel microprocessor system and provides an interface to the outside world. An analogue to digital (A/D) and a digital to analogue (D/A) converter allows real time digital signal processing

Hardware Architectures for Post-Quantum Cryptography

The rapid development of quantum computers poses severe threats to many commonly-used cryptographic algorithms that are embedded in different hardware devices to ensure the security and privacy of data and communication. Seeking for new solutions that are potentially resistant against attacks from quantum computers, a new research field called Post-Quantum Cryptography (PQC) has emerged, that is, cryptosystems deployed in classical computers conjectured to be secure against attacks utilizing large-scale quantum computers. In order to secure data during storage or communication, and many other applications in the future, this dissertation focuses on the design, implementation, and evaluation of efficient PQC schemes in hardware. Four PQC algorithms, each from a different family, are studied in this dissertation. The first hardware architecture presented in this dissertation is focused on the code-based scheme Classic McEliece. The research presented in this dissertation is the first that builds the hardware architecture for the Classic McEliece cryptosystem. This research successfully demonstrated that complex code-based PQC algorithm can be run efficiently on hardware. Furthermore, this dissertation shows that implementation of this scheme on hardware can be easily tuned to different configurations by implementing support for flexible choices of security parameters as well as configurable hardware performance parameters. The successful prototype of the Classic McEliece scheme on hardware increased confidence in this scheme, and helped Classic McEliece to get recognized as one of seven finalists in the third round of the NIST PQC standardization process. While Classic McEliece serves as a ready-to-use candidate for many high-end applications, PQC solutions are also needed for low-end embedded devices. Embedded devices play an important role in our daily life. Despite their typically constrained resources, these devices require strong security measures to protect them against cyber attacks. Towards securing this type of devices, the second research presented in this dissertation focuses on the hash-based digital signature scheme XMSS. This research is the first that explores and presents practical hardware based XMSS solution for low-end embedded devices. In the design of XMSS hardware, a heterogenous software-hardware co-design approach was adopted, which combined the flexibility of the soft core with the acceleration from the hard core. The practicability and efficiency of the XMSS software-hardware co-design is further demonstrated by providing a hardware prototype on an open-source RISC-V based System-on-a-Chip (SoC) platform. The third research direction covered in this dissertation focuses on lattice-based cryptography, which represents one of the most promising and popular alternatives to today\u27s widely adopted public key solutions. Prior research has presented hardware designs targeting the computing blocks that are necessary for the implementation of lattice-based systems. However, a recurrent issue in most existing designs is that these hardware designs are not fully scalable or parameterized, hence limited to specific cryptographic primitives and security parameter sets. The research presented in this dissertation is the first that develops hardware accelerators that are designed to be fully parameterized to support different lattice-based schemes and parameters. Further, these accelerators are utilized to realize the first software-harware co-design of provably-secure instances of qTESLA, which is a lattice-based digital signature scheme. This dissertation demonstrates that even demanding, provably-secure schemes can be realized efficiently with proper use of software-hardware co-design. The final research presented in this dissertation is focused on the isogeny-based scheme SIKE, which recently made it to the final round of the PQC standardization process. This research shows that hardware accelerators can be designed to offload compute-intensive elliptic curve and isogeny computations to hardware in a versatile fashion. These hardware accelerators are designed to be fully parameterized to support different security parameter sets of SIKE as well as flexible hardware configurations targeting different user applications. This research is the first that presents versatile hardware accelerators for SIKE that can be mapped efficiently to both FPGA and ASIC platforms. Based on these accelerators, an efficient software-hardwareco-design is constructed for speeding up SIKE. In the end, this dissertation demonstrates that, despite being embedded with expensive arithmetic, the isogeny-based SIKE scheme can be run efficiently by exploiting specialized hardware. These four research directions combined demonstrate the practicability of building efficient hardware architectures for complex PQC algorithms. The exploration of efficient PQC solutions for different hardware platforms will eventually help migrate high-end servers and low-end embedded devices towards the post-quantum era

Number theoretic techniques applied to algorithms and architectures for digital signal processing

Many of the techniques for the computation of a two-dimensional convolution of a small fixed window with a picture are reviewed. It is demonstrated that Winograd's cyclic convolution and Fourier Transform Algorithms, together with Nussbaumer's two-dimensional cyclic convolution algorithms, have a common general form. Many of these algorithms use the theoretical minimum number of general multiplications. A novel implementation of these algorithms is proposed which is based upon one-bit systolic arrays. These systolic arrays are networks of identical cells with each cell sharing a common control and timing function. Each cell is only connected to its nearest neighbours. These are all attractive features for implementation using Very Large Scale Integration (VLSI). The throughput rate is only limited by the time to perform a one-bit full addition. In order to assess the usefulness to these systolic arrays a 'cost function' is developed to compare them with more conventional techniques, such as the Cooley-Tukey radix-2 Fast Fourier Transform (FFT). The cost function shows that these systolic arrays offer a good way of implementing the Discrete Fourier Transform for transforms up to about 30 points in length. The cost function is a general tool and allows comparisons to be made between different implementations of the same algorithm and between dissimilar algorithms. Finally a technique is developed for the derivation of Discrete Cosine Transform (DCT) algorithms from the Winograd Fourier Transform Algorithm. These DCT algorithms may be implemented by modified versions of the systolic arrays proposed earlier, but requiring half the number of cells

The 1991 3rd NASA Symposium on VLSI Design

Papers from the symposium are presented from the following sessions: (1) featured presentations 1; (2) very large scale integration (VLSI) circuit design; (3) VLSI architecture 1; (4) featured presentations 2; (5) neural networks; (6) VLSI architectures 2; (7) featured presentations 3; (8) verification 1; (9) analog design; (10) verification 2; (11) design innovations 1; (12) asynchronous design; and (13) design innovations 2

The Telecommunications and Data Acquisition Report

This publication, one of a series formerly titled The Deep Space Network Progress Report, documents DSN progress in flight project support, tracking and data acquisition research and technology, network engineering, hardware and software implementation, and operations. In addition, developments in Earth-based radio technology as applied to geodynamics, astrophysics and the radio search for extraterrestrial intelligence are reported

A Study of High Performance Multiple Precision Arithmetic on Graphics Processing Units

Multiple precision (MP) arithmetic is a core building block of a wide variety of algorithms in computational mathematics and computer science. In mathematics MP is used in computational number theory, geometric computation, experimental mathematics, and in some random matrix problems. In computer science, MP arithmetic is primarily used in cryptographic algorithms: securing communications, digital signatures, and code breaking. In most of these application areas, the factor that limits performance is the MP arithmetic. The focus of our research is to build and analyze highly optimized libraries that allow the MP operations to be offloaded from the CPU to the GPU. Our goal is to achieve an order of magnitude improvement over the CPU in three key metrics: operations per second per socket, operations per watt, and operation per second per dollar. What we find is that the SIMD design and balance of compute, cache, and bandwidth resources on the GPU is quite different from the CPU, so libraries such as GMP cannot simply be ported to the GPU. New approaches and algorithms are required to achieve high performance and high utilization of GPU resources. Further, we find that low-level ISA differences between GPU generations means that an approach that works well on one generation might not run well on the next. Here we report on our progress towards MP arithmetic libraries on the GPU in four areas: (1) large integer addition, subtraction, and multiplication; (2) high performance modular multiplication and modular exponentiation (the key operations for cryptographic algorithms) across generations of GPUs; (3) high precision floating point addition, subtraction, multiplication, division, and square root; (4) parallel short division, which we prove is asymptotically optimal on EREW and CREW PRAMs

GPU and ASIC Acceleration of Elliptic Curve Scalar Point Multiplication

As public information is increasingly communicated across public networks such as the internet, the use of public key cryptography to provide security services such as authentication, data integrity, and non-repudiation is ever-growing. Elliptic curve cryptography is being used now more than ever to fulfill the need for public key cryptography, as it provides security equivalent in strength to the entrenched RSA cryptography algorithm, but with much smaller key sizes and reduced computational cost. All elliptic curve cryptography operations rely on elliptic curve scalar point multiplication. In turn, scalar point multiplication depends heavily on finite field multiplication. In this dissertation, two major approaches are taken to accelerate the performance of scalar point multiplication. First, a series of very high performance finite field multiplier architectures have been implemented using domino logic in a CMOS process. Simulation results show that the proposed implementations are more efficient than similar designs in the literature when considering area and delay as performance metrics. The proposed implementations are suitable for integration with a CPU in order to provide a special-purpose finite field multiplication instruction useful for accelerating scalar point multiplication. The next major part of this thesis focuses on the use of consumer computer graphics cards to directly accelerate scalar point multiplication. A number of finite field multiplication algorithms suitable for graphics cards are developed, along with algorithms for finite field addition, subtraction, squaring, and inversion. The proposed graphics-card finite field arithmetic library is used to accelerate elliptic curve scalar point multiplication. The operation throughput and latency performance of the proposed implementation is characterized by a series of tests, and results are compared to the state of the art. Finally, it is shown that graphics cards can be used to significantly increase the operation throughput of scalar point multiplication operations, which makes their use viable for improving elliptic curve cryptography performance in a high-demand server environment

The Telecommunications and Data Acquisition Report

Tracking and ground-based navigation; communications, spacecraft-ground; station control and system technology; capabilities for new projects; networks consolidation program; and network sustaining are described

The Deep Space Network

Deep Space Network progress in flight project support, tracking and data acquisition, research and technology, network engineering, hardware and software implementation, and operations is cited. Topics covered include: tracking and ground based navigation; spacecraft/ground communication; station control and operations technology; ground communications; and deep space stations