Vector processing-aware advanced clock-gating techniques for low-power fused multiply-add

The need for power efficiency is driving a rethink of design decisions in processor architectures. While vector processors succeeded in the high-performance market in the past, they need a retailoring for the mobile market that they are entering now. Floating-point (FP) fused multiply-add (FMA), being a functional unit with high power consumption, deserves special attention. Although clock gating is a well-known method to reduce switching power in synchronous designs, there are unexplored opportunities for its application to vector processors, especially when considering active operating mode. In this research, we comprehensively identify, propose, and evaluate the most suitable clock-gating techniques for vector FMA units (VFUs). These techniques ensure power savings without jeopardizing the timing. We evaluate the proposed techniques using both synthetic and “real-world” application-based benchmarking. Using vector masking and vector multilane-aware clock gating, we report power reductions of up to 52%, assuming active VFU operating at the peak performance. Among other findings, we observe that vector instruction-based clock-gating techniques achieve power savings for all vector FP instructions. Finally, when evaluating all techniques together, using “real-world” benchmarking, the power reductions are up to 80%. Additionally, in accordance with processor design trends, we perform this research in a fully parameterizable and automated fashion.The research leading to these results has received funding from the RoMoL ERC Advanced Grant GA 321253 and is supported in part by the European Union (FEDER funds) under contract TTIN2015-65316-P. The work of I. Ratkovic was supported by a FPU research grant from the Spanish MECD.Peer ReviewedPostprint (author's final draft

Power-Aware Design Methodologies for FPGA-Based Implementation of Video Processing Systems

The increasing capacity and capabilities of FPGA devices in recent years provide an attractive option for performance-hungry applications in the image and video processing domain. FPGA devices are often used as implementation platforms for image and video processing algorithms for real-time applications due to their programmable structure that can exploit inherent spatial and temporal parallelism. While performance and area remain as two main design criteria, power consumption has become an important design goal especially for mobile devices. Reduction in power consumption can be achieved by reducing the supply voltage, capacitances, clock frequency and switching activities in a circuit. Switching activities can be reduced by architectural optimization of the processing cores such as adders, multipliers, multiply and accumulators (MACS), etc. This dissertation research focuses on reducing the switching activities in digital circuits by considering data dependencies in bit level, word level and block level neighborhoods in a video frame. The bit level data neighborhood dependency consideration for power reduction is illustrated in the design of pipelined array, Booth and log-based multipliers. For an array multiplier, operands of the multipliers are partitioned into higher and lower parts so that the probability of the higher order parts being zero or one increases. The gating technique for the pipelined approach deactivates part(s) of the multiplier when the above special values are detected. For the Booth multiplier, the partitioning and gating technique is integrated into the Booth recoding scheme. In addition, a delay correction strategy is developed for the Booth multiplier to reduce the switching activities of the sign extension part in the partial products. A novel architecture design for the computation of log and inverse-log functions for the reduction of power consumption in arithmetic circuits is also presented. This also utilizes the proposed partitioning and gating technique for further dynamic power reduction by reducing the switching activities. The word level and block level data dependencies for reducing the dynamic power consumption are illustrated by presenting the design of a 2-D convolution architecture. Here the similarities of the neighboring pixels in window-based operations of image and video processing algorithms are considered for reduced switching activities. A partitioning and detection mechanism is developed to deactivate the parallel architecture for window-based operations if higher order parts of the pixel values are the same. A neighborhood dependent approach (NDA) is incorporated with different window buffering schemes. Consideration of the symmetry property in filter kernels is also applied with the NDA method for further reduction of switching activities. The proposed design methodologies are implemented and evaluated in a FPGA environment. It is observed that the dynamic power consumption in FPGA-based circuit implementations is significantly reduced in bit level, data level and block level architectures when compared to state-of-the-art design techniques. A specific application for the design of a real-time video processing system incorporating the proposed design methodologies for low power consumption is also presented. An image enhancement application is considered and the proposed partitioning and gating, and NDA methods are utilized in the design of the enhancement system. Experimental results show that the proposed multi-level power aware methodology achieves considerable power reduction. Research work is progressing In utilizing the data dependencies in subsequent frames in a video stream for the reduction of circuit switching activities and thereby the dynamic power consumption

Multiple bit error correcting architectures over finite fields

This thesis proposes techniques to mitigate multiple bit errors in GF arithmetic circuits. As GF arithmetic circuits such as multipliers constitute the complex and important functional unit of a crypto-processor, making them fault tolerant will improve the reliability of circuits that are employed in safety applications and the errors may cause catastrophe if not mitigated. Firstly, a thorough literature review has been carried out. The merits of efficient schemes are carefully analyzed to study the space for improvement in error correction, area and power consumption. Proposed error correction schemes include bit parallel ones using optimized BCH codes that are useful in applications where power and area are not prime concerns. The scheme is also extended to dynamically correcting scheme to reduce decoder delay. Other method that suits low power and area applications such as RFIDs and smart cards using cross parity codes is also proposed. The experimental evaluation shows that the proposed techniques can mitigate single and multiple bit errors with wider error coverage compared to existing methods with lesser area and power consumption. The proposed scheme is used to mask the errors appearing at the output of the circuit irrespective of their cause. This thesis also investigates the error mitigation schemes in emerging technologies (QCA, CNTFET) to compare area, power and delay with existing CMOS equivalent. Though the proposed novel multiple error correcting techniques can not ensure 100% error mitigation, inclusion of these techniques to actual design can improve the reliability of the circuits or increase the difficulty in hacking crypto-devices. Proposed schemes can also be extended to non GF digital circuits

Versatile Montgomery Multiplier Architectures

Several algorithms for Public Key Cryptography (PKC), such as RSA, Diffie-Hellman, and Elliptic Curve Cryptography, require modular multiplication of very large operands (sizes from 160 to 4096 bits) as their core arithmetic operation. To perform this operation reasonably fast, general purpose processors are not always the best choice. This is why specialized hardware, in the form of cryptographic co-processors, become more attractive. Based upon the analysis of recent publications on hardware design for modular multiplication, this M.S. thesis presents a new architecture that is scalable with respect to word size and pipelining depth. To our knowledge, this is the first time a word based algorithm for Montgomery\u27s method is realized using high-radix bit-parallel multipliers working with two different types of finite fields (unified architecture for GF(p) and GF(2n)). Previous approaches have relied mostly on bit serial multiplication in combination with massive pipelining, or Radix-8 multiplication with the limitation to a single type of finite field. Our approach is centered around the notion that the optimal delay in bit-parallel multipliers grows with logarithmic complexity with respect to the operand size n, O(log3/2 n), while the delay of bit serial implementations grows with linear complexity O(n). Our design has been implemented in VHDL, simulated and synthesized in 0.5μ CMOS technology. The synthesized net list has been verified in back-annotated timing simulations and analyzed in terms of performance and area consumption

Energy Aware Design and Analysis for Synchronous and Asynchronous Circuits

Power dissipation has become a major concern for IC designers. Various low power design techniques have been developed for synchronous circuits. Asynchronous circuits, however. have gained more interests recently due to their benefits in lower noise, easy timing control, etc. But few publications on energy reduction techniques for asynchronous logic are available. Power awareness indicates the ability of the system power to scale with changing conditions and quality requirements. Scalability is an important figure-of-merit since it allows the end user to implement operational policy. just like the user of mobile multimedia equipment needs to select between better quality and longer battery operation time. This dissertation discusses power/energy optimization and performs analysis on both synchronous and asynchronous logic. The major contributions of this dissertation include: 1 ) A 2-Dimensional Pipeline Gating technique for synchronous pipelined circuits to improve their power awareness has been proposed. This technique gates the corresponding clock lines connected to registers in both vertical direction (the data flow direction) and horizontal direction (registers within each pipeline stage) based on current input precision. 2) Two energy reduction techniques, Signal Bypassing & Insertion and Zero Insertion. have been developed for NCL circuits. Both techniques use Nulls to replace redundant Data 0\u27s based on current input precision in order to reduce the switching activity while Signal Bypassing & Insertion is for non-pipelined NCI, circuits and Zero Insertion is for pipelined counterparts. A dynamic active-bit detection scheme is also developed as an expansion. 3) Two energy estimation techniques, Equivalent Inverter Modeling based on Input Mapping in transistor-level and Switching Activity Modeling in gate-level, have been proposed. The former one is for CMOS gates with feedbacks and the latter one is for NCL circuits

Reclaiming Fault Resilience and Energy Efficiency With Enhanced Performance in Low Power Architectures

Rapid developments of the AI domain has revolutionized the computing industry by the introduction of state-of-art AI architectures. This growth is also accompanied by a massive increase in the power consumption. Near-Theshold Computing (NTC) has emerged as a viable solution by offering significant savings in power consumption paving the way for an energy efficient design paradigm. However, these benefits are accompanied by a deterioration in performance due to the severe process variation and slower transistor switching at Near-Threshold operation. These problems severely restrict the usage of Near-Threshold operation in commercial applications. In this work, a novel AI architecture, Tensor Processing Unit, operating at NTC is thoroughly investigated to tackle the issues hindering system performance. Research problems are demonstrated in a scientific manner and unique opportunities are explored to propose novel design methodologies

Low-Power, Low-Cost, & High-Performance Digital Designs : Multi-bit Signed Multiplier design using 32nm CMOS Technology

Binary multipliers are ubiquitous in digital hardware. Digital multipliers along with the adders play a major role in computing, communicating, and controlling devices. Multipliers are used majorly in the areas of digital signal and image processing, central processing unit (CPU) of the computers, high-performance and parallel scientific computing, machine learning, physical layer design of the communication equipment, etc. The predominant presence and increasing demand for low-power, low-cost, and high-performance digital hardware led to this work of developing optimized multiplier designs. Two optimized designs are proposed in this work. One is an optimized 8 x 8 Booth multiplier architecture which is implemented using 32nm CMOS technology. Synthesis (pre-layout) and post-layout results show that the delay is reduced by 24.7% and 25.6% respectively, the area is reduced by 5.5% and 15% respectively, the power consumption is reduced by 21.5% and 26.6% respectively, and the area-delay-product is reduced by 28.8% and 36.8% respectively when compared to the performance results obtained for the state-of-the-art 8 x 8 Booth multiplier designed using 32nm CMOS technology with 1.05 V supply voltage at 500 MHz input frequency. Another is a novel radix-8 structure with 3-bit grouping to reduce the number of partial products along with the effective partial product reduction schemes for 8 x 8, 16 x 16, 32 x 32, and 64 x 64 signed multipliers. Comparing the performance results of the (synthesized, post-layout) designs of sizes 32 x 32, and 64 x 64 based on the simple novel radix-8 structure with the estimated performance measurements for the optimized Booth multiplier design presented in this work, reduction in delay by (2.64%, 0.47%) and (2.74%, 18.04%) respectively, and reduction in area-delay-product by (12.12%, -5.17%) and (17.82%, 12.91%) respectively can be observed. With the use of the higher radix structure, delay, area, and power consumption can be further reduced. Appropriate adder deployment, further exploring the optimized grouping or compression strategies, and applying more low-power design techniques such as power-gating, multi-Vt MOS transistor utilization, multi-VDD domain creation, etc., help, along with the higher radix structures, realizing the more efficient multiplier designs

Efficient Computation and FPGA implementation of Fully Homomorphic Encryption with Cloud Computing Significance

Homomorphic Encryption provides unique security solution for cloud computing. It ensures not only that data in cloud have confidentiality but also that data processing by cloud server does not compromise data privacy. The Fully Homomorphic Encryption (FHE) scheme proposed by Lopez-Alt, Tromer, and Vaikuntanathan (LTV), also known as NTRU(Nth degree truncated polynomial ring) based method, is considered one of the most important FHE methods suitable for practical implementation. In this thesis, an efficient algorithm and architecture for LTV Fully Homomorphic Encryption is proposed. Conventional linear feedback shift register (LFSR) structure is expanded and modified for performing the truncated polynomial ring multiplication in LTV scheme in parallel. Novel and efficient modular multiplier, modular adder and modular subtractor are proposed to support high speed processing of LFSR operations. In addition, a family of special moduli are selected for high speed computation of modular operations. Though the area keeps the complexity of O(Nn^2) with no advantage in circuit level. The proposed architecture effectively reduces the time complexity from O(N log N) to linear time, O(N), compared to the best existing works. An FPGA implementation of the proposed architecture for LTV FHE is achieved and demonstrated. An elaborate comparison of the existing methods and the proposed work is presented, which shows the proposed work gains significant speed up over existing works