Hardware/Software Co-design for Multicore Architectures

Siirretty Doriast

Semantic-Preserving Transformations for Stream Program Orchestration on Multicore Architectures

Because the demand for high performance with big data processing and distributed computing is increasing, the stream programming paradigm has been revisited for its abundance of parallelism in virtue of independent actors that communicate via data channels. The synchronous data-flow (SDF) programming model is frequently adopted with stream programming languages for its convenience to express stream programs as a set of nodes connected by data channels. Static data-rates of SDF programming model enable program transformations that greatly improve the performance of SDF programs on multicore architectures. The major application domain is for SDF programs are digital signal processing, audio, video, graphics kernels, networking, and security. This thesis makes the following three contributions that improve the performance of SDF programs: First, a new intermediate representation (IR) called LaminarIR is introduced. LaminarIR replaces FIFO queues with direct memory accesses to reduce the data communication overhead and explicates data dependencies between producer and consumer nodes. We provide transformations and their formal semantics to convert conventional, FIFO-queue based program representations to LaminarIR. Second, a compiler framework to perform sound and semantics-preserving program transformations from FIFO semantics to LaminarIR. We employ static program analysis to resolve token positions in FIFO queues and replace them by direct memory accesses. Third, a communication-cost-aware program orchestration method to establish a foundation of LaminarIR parallelization on multicore architectures. The LaminarIR framework, which consists of the aforementioned contributions together with the benchmarks that we used with the experimental evaluation, has been open-sourced to advocate further research on improving the performance of stream programming languages

System-on-chip Computing and Interconnection Architectures for Telecommunications and Signal Processing

This dissertation proposes novel architectures and design techniques targeting SoC building blocks for telecommunications and signal processing applications. Hardware implementation of Low-Density Parity-Check decoders is approached at both the algorithmic and the architecture level. Low-Density Parity-Check codes are a promising coding scheme for future communication standards due to their outstanding error correction performance. This work proposes a methodology for analyzing effects of finite precision arithmetic on error correction performance and hardware complexity. The methodology is throughout employed for co-designing the decoder. First, a low-complexity check node based on the P-output decoding principle is designed and characterized on a CMOS standard-cells library. Results demonstrate implementation loss below 0.2 dB down to BER of 10^{-8} and a saving in complexity up to 59% with respect to other works in recent literature. High-throughput and low-latency issues are addressed with modified single-phase decoding schedules. A new "memory-aware" schedule is proposed requiring down to 20% of memory with respect to the traditional two-phase flooding decoding. Additionally, throughput is doubled and logic complexity reduced of 12%. These advantages are traded-off with error correction performance, thus making the solution attractive only for long codes, as those adopted in the DVB-S2 standard. The "layered decoding" principle is extended to those codes not specifically conceived for this technique. Proposed architectures exhibit complexity savings in the order of 40% for both area and power consumption figures, while implementation loss is smaller than 0.05 dB. Most modern communication standards employ Orthogonal Frequency Division Multiplexing as part of their physical layer. The core of OFDM is the Fast Fourier Transform and its inverse in charge of symbols (de)modulation. Requirements on throughput and energy efficiency call for FFT hardware implementation, while ubiquity of FFT suggests the design of parametric, re-configurable and re-usable IP hardware macrocells. In this context, this thesis describes an FFT/IFFT core compiler particularly suited for implementation of OFDM communication systems. The tool employs an accuracy-driven configuration engine which automatically profiles the internal arithmetic and generates a core with minimum operands bit-width and thus minimum circuit complexity. The engine performs a closed-loop optimization over three different internal arithmetic models (fixed-point, block floating-point and convergent block floating-point) using the numerical accuracy budget given by the user as a reference point. The flexibility and re-usability of the proposed macrocell are illustrated through several case studies which encompass all current state-of-the-art OFDM communications standards (WLAN, WMAN, xDSL, DVB-T/H, DAB and UWB). Implementations results are presented for two deep sub-micron standard-cells libraries (65 and 90 nm) and commercially available FPGA devices. Compared with other FFT core compilers, the proposed environment produces macrocells with lower circuit complexity and same system level performance (throughput, transform size and numerical accuracy). The final part of this dissertation focuses on the Network-on-Chip design paradigm whose goal is building scalable communication infrastructures connecting hundreds of core. A low-complexity link architecture for mesochronous on-chip communication is discussed. The link enables skew constraint looseness in the clock tree synthesis, frequency speed-up, power consumption reduction and faster back-end turnarounds. The proposed architecture reaches a maximum clock frequency of 1 GHz on 65 nm low-leakage CMOS standard-cells library. In a complex test case with a full-blown NoC infrastructure, the link overhead is only 3% of chip area and 0.5% of leakage power consumption. Finally, a new methodology, named metacoding, is proposed. Metacoding generates correct-by-construction technology independent RTL codebases for NoC building blocks. The RTL coding phase is abstracted and modeled with an Object Oriented framework, integrated within a commercial tool for IP packaging (Synopsys CoreTools suite). Compared with traditional coding styles based on pre-processor directives, metacoding produces 65% smaller codebases and reduces the configurations to verify up to three orders of magnitude

Selected Papers from IEEE ICASI 2019

The 5th IEEE International Conference on Applied System Innovation 2019 (IEEE ICASI 2019, https://2019.icasi-conf.net/), which was held in Fukuoka, Japan, on 11–15 April, 2019, provided a unified communication platform for a wide range of topics. This Special Issue entitled “Selected Papers from IEEE ICASI 2019” collected nine excellent papers presented on the applied sciences topic during the conference. Mechanical engineering and design innovations are academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering designs. Technological innovation by mechanical engineering includes information technology (IT)-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology. These new technologies that implant intelligence in machine systems represent an interdisciplinary area that combines conventional mechanical technology and new IT. The main goal of this Special Issue is to provide new scientific knowledge relevant to IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology

Cycle-accurate modeling of multicore processors on FPGAs

Thesis (Ph. D.)--Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (pages 169-176).We present a novel modeling methodology which enables the generation of a high-performance, cycle-accurate simulator from a cycle-level specification of the target design. We describe Arete, a full-system multicore processor simulator, developed using our modeling methodology. We provide details on Arete's resource-efficient and high-performance implementation on multiple FPGA platforms, and the architectural experiments performed using it. We present clear evidence that the use of simplified models in architectural studies can lead to wrong conclusions. Through two experiments performed using both cycle-accurate and simplified models, we show that on one hand there are substantial quantitative and qualitative differences in results, and on the other, the results match quite well.by Asif Imtiaz Khan.Ph.D

Dynamically reconfigurable asynchronous processor

The main design requirements for today's mobile applications are: · high throughput performance. · high energy efficiency. · high programmability. Until now, the choice of platform has often been limited to Application-Specific Integrated Circuits (ASICs), due to their best-of-breed performance and power consumption. The economies of scale possible with these high-volume markets have traditionally been able to hide the high Non-Recurring Engineering (NRE) costs required for designing and fabricating new ASICs. However, with the NREs and design time escalating with each generation of mobile applications, this practice may be reaching its limit. Designers today are looking at programmable solutions, so that they can respond more rapidly to changes in the market and spread costs over several generations of mobile applications. However, there have been few feasible alternatives to ASICs: Digital Signals Processors (DSPs) and microprocessors cannot meet the throughput requirements, whereas Field-Programmable Gate Arrays (FPGAs) require too much area and power. Coarse-grained dynamically reconfigurable architectures offer better solutions for high throughput applications, when power and area considerations are taken into account. One promising example is the Reconfigurable Instruction Cell Array (RICA). RICA consists of an array of cells with an interconnect that can be dynamically reconfigured on every cycle. This allows quite complex datapaths to be rendered onto the fabric and executed in a single configuration - making these architectures particularly suitable to stream processing. Furthermore, RICA can be programmed from C, making it a good fit with existing design methodologies. However the RICA architecture has a drawback: poor scalability in terms of area and power. As the core gets bigger, the number of sequential elements in the array must be increased significantly to maintain the ability to achieve high throughputs through pipelining. As a result, a larger clock tree is required to synchronise the increased number of sequential elements. The clock tree therefore takes up a larger percentage of the area and power consumption of the core. This thesis presents a novel Dynamically Reconfigurable Asynchronous Processor (DRAP), aimed at high-throughput mobile applications. DRAP is based on the RICA architecture, but uses asynchronous design techniques - methods of designing digital systems without clocks. The absence of a global clock signal makes DRAP more scalable in terms of power and area overhead than its synchronous counterpart. The DRAP architecture maintains most of the benefits of custom asynchronous design, whilst also providing programmability via conventional high-level languages. Results show that the DRAP processor delivers considerably lower power consumption when compared to a market-leading Very Long Instruction Word (VLIW) processor and a low-power ARM processor. For example, DRAP resulted in a reduction in power consumption of 20 times compared to the ARM7 processor, and 29 times compared to the TIC64x VLIW, when running the same benchmark capped to the same throughput and for the same process technology (0.13μm). When compared to an equivalent RICA design, DRAP was up to 22% larger than RICA but resulted in a power reduction of up to 1.9 times. It was also capable of achieving up to 2.8 times higher throughputs than RICA for the same benchmarks

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

Novel load identification techniques and a steady state self-tuning prototype for switching mode power supplies

Control of Switched Mode Power Supplies (SMPS) has been traditionally achieved through analog means with dedicated integrated circuits (ICs). However, as power systems are becoming increasingly complex, the classical concept of control has gradually evolved into the more general problem of power management, demanding functionalities that are hardly achievable in analog controllers. The high flexibility offered by digital controllers and their capability to implement sophisticated control strategies, together with the programmability of controller parameters, make digital control very attractive as an option for improving the features of dcdc converters. On the other side, digital controllers find their major weak point in the achievable dynamic performances of the closed loop system. Indeed, analogto-digital conversion times, computational delays and sampling-related delays strongly limit the small signal closed loop bandwidth of a digitally controlled SMPS. Quantization effects set other severe constraints not known to analog solutions. For these reasons, intensive scientific research activity is addressing the problem of making digital compensator stronger competitors against their analog counterparts in terms of achievable performances. In a wide range of applications, dcdc converters with high efficiency over the whole range of their load values are required. Integrated digital controllers for Switching Mode Power Supplies are gaining growing interest, since it has been shown the feasibility of digital controller ICs specifically developed for high frequency switching converters. One very interesting potential benefit is the use of autotuning of controller parameters (on-line controllers), so that the dynamic response can be set at the software level, independently of output capacitor filters, component variations and ageing. These kind of algorithms are able to identify the output filter configuration (system identification) and then automatically compute the best compensator gains to adjust system margins and bandwidth. In order to be an interesting solution, however, the self-tuning should satisfy two important requirements: it should not heavily affect converter operation under nominal condition and it should be based on a simple and robust algorithm whose complexity does not require a significant increase of the silicon area of the IC controller. The first issue is avoided performing the system identification (SI) with the system open loop configuration, where perturbations can be induced in the system before the start up. Much more challenging is to satisfy this requirement during steady state operations, where perturbations on the output voltage are limited by the regular operations of the converter. The main advantage of steady state SI methods, is the detection of possible non-idealities occurring during the converter operations. In this way, the system dynamics can be consequently adjusted with the compensator parameters tuning. The resource saving issue, requires the development of äd-hocßelf-tuning techniques specifically tailored for integrated digitally controlled converters. Considering the flexibility of digital control, self-tuning algorithms can be studied and easily integrated at hardware level into closed loop SMPS reducing development time and R & D costs. The work of this dissertation finds its origin in this context. Smart power management is accomplished by tuning the controller parameters accordingly to the identified converter configuration. Themain difficult for self-tuning techniques is the identification of the converter output filter configuration. Two novel system identification techniques have been validated in this dissertation. The open loop SI method is based on the system step response, while dithering amplification effects are exploited for the steady state SI method. The open loop method can be used as autotunig approach during or before the system start up, a step evolving reference voltage has been used as system perturbation and to obtain the output filter information with the Power Spectral Density (PSD) computation of the system step response. The use of ¢§ modulator is largely increasing in digital control feedback. During the steady state, the finite resolution introduces quantization effects on the signal path causing low frequency contributes of the digital control word. Through oversampling-dithering capabilities of ¢§ modulators, resolution improvements are obtained. The presented steady state identification techniques demonstrates that, amplifying the dithering effects on the signal path, the output filter information can be obtained on the digital side by processing with the PSD computation the perturbed output voltage. The amount of noise added on the output voltage does not affect the converter operations, mathematical considerations have been addressed and then justified both with a Matlab/Simulink fixed-point and a FPGA-based closed loop system. The load output filter identification of both algorithms, refer to the frequency domain. When the respective perturbations occurs, the system response is observed on the digital side and processed with the PSD computation. The extracted parameters are the resonant frequency ans the possible ESR (Effective Series Resistance) contributes,which can be detected as maximumin the PSD output. The SI methods have been validated for different configurations of buck converters on a fixed-point closed loop model, however, they can be easily applied to further converter configurations. The steady state method has been successfully integrated into a FPGA-based prototype for digitally controlled buck converters, that integrates a PSD computer needed for the load parameters identification. At this purpose, a novel VHDL-coded full-scalable hybrid processor for Constant Geometry FFT (CG-FFT) computation has been designed and integrated into the PSD computation system. The processor is based on a variation of the conventional algorithm used for FFT, which is the Constant-Geometry FFT (CG-FFT).Hybrid CORDIC-LUT scalable architectures, has been introduced as alternative approach for the twiddle factors (phase factors) computation needed during the FFT algorithms execution. The shared core architecture uses a single phase rotator to satisfy all TF requests. It can achieve improved logic saving by trading off with computational speed. The pipelined architecture is composed of a number of stages equal to the number of PEs and achieves the highest possible throughput, at the expense of more hardware usage