Automated Design Space Exploration and Datapath Synthesis for Finite Field Arithmetic with Applications to Lightweight Cryptography

Today, emerging technologies are reaching astronomical proportions. For example, the Internet of Things has numerous applications and consists of countless different devices using different technologies with different capabilities. But the one invariant is their connectivity. Consequently, secure communications, and cryptographic hardware as a means of providing them, are faced with new challenges. Cryptographic algorithms intended for hardware implementations must be designed with a good trade-off between implementation efficiency and sufficient cryptographic strength. Finite fields are widely used in cryptography. Examples of algorithm design choices related to finite field arithmetic are the field size, which arithmetic operations to use, how to represent the field elements, etc. As there are many parameters to be considered and analyzed, an automation framework is needed. This thesis proposes a framework for automated design, implementation and verification of finite field arithmetic hardware. The underlying motif throughout this work is “math meets hardware”. The automation framework is designed to bring the awareness of underlying mathematical structures to the hardware design flow. It is implemented in GAP, an open source computer algebra system that can work with finite fields and has symbolic computation capabilities. The framework is roughly divided into two phases, the architectural decisions and the automated design genera- tion. The architectural decisions phase supports parameter search and produces a list of candidates. The automated design generation phase is invoked for each candidate, and the generated VHDL files are passed on to conventional synthesis tools. The candidates and their implementation results form the design space, and the framework allows rapid design space exploration in a systematic way. In this thesis, design space exploration is focused on finite field arithmetic. Three distinctive features of the proposed framework are the structure of finite fields, tower field support, and on the fly submodule generation. Each finite field used in the design is represented as both a field and its corresponding vector space. It is easy for a designer to switch between fields and vector spaces, but strict distinction of the two is necessary for hierarchical designs. When an expression is defined over an extension field, the top-level module contains element signals and submodules for arithmetic operations on those signals. The submodules are generated with corresponding vector signals and the arithmetic operations are now performed on the coordinates. For tower fields, the submodules are generated for the subfield operations, and the design is generated in a top-down fashion. The binding of expressions to the appropriate finite fields or vector spaces and a set of customized methods allow the on the fly generation of expressions for implementation of arithmetic operations, and hence submodule generation. In the light of NIST Lightweight Cryptography Project (LWC), this work focuses mainly on small finite fields. The thesis illustrates the impact of hardware implementation results during the design process of WAGE, a Round 2 candidate in the NIST LWC standardization competition. WAGE is a hardware oriented authenticated encryption scheme. The parameter selection for WAGE was aimed at balancing the security and hardware implementation area, using hardware implementation results for many design decisions, for example field size, representation of field elements, etc. In the proposed framework, the components of WAGE are used as an example to illustrate different automation flows and demonstrate the design space exploration on a real-world algorithm

A portable platform for accelerated PIC codes and its application to GPUs using OpenACC

We present a portable platform, called PIC_ENGINE, for accelerating Particle-In-Cell (PIC) codes on heterogeneous many-core architectures such as Graphic Processing Units (GPUs). The aim of this development is efficient simulations on future exascale systems by allowing different parallelization strategies depending on the application problem and the specific architecture. To this end, this platform contains the basic steps of the PIC algorithm and has been designed as a test bed for different algorithmic options and data structures. Among the architectures that this engine can explore, particular attention is given here to systems equipped with GPUs. The study demonstrates that our portable PIC implementation based on the OpenACC programming model can achieve performance closely matching theoretical predictions. Using the Cray XC30 system, Piz Daint, at the Swiss National Supercomputing Centre (CSCS), we show that PIC_ENGINE running on an NVIDIA Kepler K20X GPU can outperform the one on an Intel Sandybridge 8-core CPU by a factor of 3.4

Comparing Tag Scheme Variations Using an Abstract Machine Generator

In this paper we study, in the context of a WAM-based abstract machine for Prolog, how variations in the encoding of type information in tagged words and in their associated basic operations impact performance and memory usage. We use a high-level language to specify encodings and the associated operations. An automatic generator constructs both the abstract machine using this encoding and the associated Prolog-to-byte code compiler. Annotations in this language make it possible to impose constraints on the final representation of tagged words, such as the effectively addressable space (fixing, for example, the word size of the target processor /architecture), the layout of the tag and value bits inside the tagged word, and how the basic operations are implemented. We evaluate large number of combinations of the different parameters in two scenarios: a) trying to obtain an optimal general-purpose abstract machine and b) automatically generating a specially-tuned abstract machine for a particular program. We conclude that we are able to automatically generate code featuring all the optimizations present in a hand-written, highly-optimized abstract machine and we canal so obtain emulators with larger addressable space and better performance

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Janus II: a new generation application-driven computer for spin-system simulations

This paper describes the architecture, the development and the implementation of Janus II, a new generation application-driven number cruncher optimized for Monte Carlo simulations of spin systems (mainly spin glasses). This domain of computational physics is a recognized grand challenge of high-performance computing: the resources necessary to study in detail theoretical models that can make contact with experimental data are by far beyond those available using commodity computer systems. On the other hand, several specific features of the associated algorithms suggest that unconventional computer architectures, which can be implemented with available electronics technologies, may lead to order of magnitude increases in performance, reducing to acceptable values on human scales the time needed to carry out simulation campaigns that would take centuries on commercially available machines. Janus II is one such machine, recently developed and commissioned, that builds upon and improves on the successful JANUS machine, which has been used for physics since 2008 and is still in operation today. This paper describes in detail the motivations behind the project, the computational requirements, the architecture and the implementation of this new machine and compares its expected performances with those of currently available commercial systems.Comment: 28 pages, 6 figure

Efficient software implementation of elliptic curves and bilinear pairings

Orientador: Júlio César Lopez HernándezTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: O advento da criptografia assimétrica ou de chave pública possibilitou a aplicação de criptografia em novos cenários, como assinaturas digitais e comércio eletrônico, tornando-a componente vital para o fornecimento de confidencialidade e autenticação em meios de comunicação. Dentre os métodos mais eficientes de criptografia assimétrica, a criptografia de curvas elípticas destaca-se pelos baixos requisitos de armazenamento para chaves e custo computacional para execução. A descoberta relativamente recente da criptografia baseada em emparelhamentos bilineares sobre curvas elípticas permitiu ainda sua flexibilização e a construção de sistemas criptográficos com propriedades inovadoras, como sistemas baseados em identidades e suas variantes. Porém, o custo computacional de criptossistemas baseados em emparelhamentos ainda permanece significativamente maior do que os assimétricos tradicionais, representando um obstáculo para sua adoção, especialmente em dispositivos com recursos limitados. As contribuições deste trabalho objetivam aprimorar o desempenho de criptossistemas baseados em curvas elípticas e emparelhamentos bilineares e consistem em: (i) implementação eficiente de corpos binários em arquiteturas embutidas de 8 bits (microcontroladores presentes em sensores sem fio); (ii) formulação eficiente de aritmética em corpos binários para conjuntos vetoriais de arquiteturas de 64 bits e famílias mais recentes de processadores desktop dotadas de suporte nativo à multiplicação em corpos binários; (iii) técnicas para implementação serial e paralela de curvas elípticas binárias e emparelhamentos bilineares simétricos e assimétricos definidos sobre corpos primos ou binários. Estas contribuições permitiram obter significativos ganhos de desempenho e, conseqüentemente, uma série de recordes de velocidade para o cálculo de diversos algoritmos criptográficos relevantes em arquiteturas modernas que vão de sistemas embarcados de 8 bits a processadores com 8 coresAbstract: The development of asymmetric or public key cryptography made possible new applications of cryptography such as digital signatures and electronic commerce. Cryptography is now a vital component for providing confidentiality and authentication in communication infra-structures. Elliptic Curve Cryptography is among the most efficient public-key methods because of its low storage and computational requirements. The relatively recent advent of Pairing-Based Cryptography allowed the further construction of flexible and innovative cryptographic solutions like Identity-Based Cryptography and variants. However, the computational cost of pairing-based cryptosystems remains significantly higher than traditional public key cryptosystems and thus an important obstacle for adoption, specially in resource-constrained devices. The main contributions of this work aim to improve the performance of curve-based cryptosystems, consisting of: (i) efficient implementation of binary fields in 8-bit microcontrollers embedded in sensor network nodes; (ii) efficient formulation of binary field arithmetic in terms of vector instructions present in 64-bit architectures, and on the recently-introduced native support for binary field multiplication in the latest Intel microarchitecture families; (iii) techniques for serial and parallel implementation of binary elliptic curves and symmetric and asymmetric pairings defined over prime and binary fields. These contributions produced important performance improvements and, consequently, several speed records for computing relevant cryptographic algorithms in modern computer architectures ranging from embedded 8-bit microcontrollers to 8-core processorsDoutoradoCiência da ComputaçãoDoutor em Ciência da Computaçã