Transistor-Level Synthesis of Pipeline Analog-to-Digital Converters Using a Design-Space Reduction Algorithm

A novel transistor-level synthesis procedure for pipeline ADCs is presented. This procedure is able to directly map high-level converter specifications onto transistor sizes and biasing conditions. It is based on the combination of behavioral models for performance evaluation, optimization routines to minimize the power and area consumption of the circuit solution, and an algorithm to efficiently constraint the converter design space. This algorithm precludes the cost of lengthy bottom-up verifications and speeds up the synthesis task. The approach is herein demonstrated via the design of a 0.13 μm CMOS 10 bits@60 MS/s pipeline ADC with energy consumption per conversion of only 0.54 pJ@1 MHz, making it one of the most energy-efficient 10-bit video-rate pipeline ADCs reported to date. The computational cost of this design is of only 25 min of CPU time, and includes the evaluation of 13 different pipeline architectures potentially feasible for the targeted specifications. The optimum design derived from the synthesis procedure has been fine tuned to support PVT variations, laid out together with other auxiliary blocks, and fabricated. The experimental results show a power consumption of 23 [email protected] V and an effective resolution of 9.47-bit@1 MHz. Bearing in mind that no specific power reduction strategy has been applied; the mentioned results confirm the reliability of the proposed approach.Ministerio de Ciencia e Innovación TEC2009-08447Junta de Andalucía TIC-0281

Adaptive Latency Insensitive Protocols andElastic Circuits with Early Evaluation: A Comparative Analysis

AbstractLatency Insensitive Protocols (LIP) and Elastic Circuits (EC) solve the same problem of rendering a design tolerant to additional latencies caused by wires or computational elements. They are performance-limited by a firing semantics that enforces coherency through a lazy evaluation rule: Computation is enabled if all inputs to a block are simultaneously available. Adaptive LIP's (ALIP) and EC with early evaluation (ECEE) increase the performance by relaxing the evaluation rule: Computation is enabled as soon as the subset of inputs needed at a given time is available. Their difference in terms of implementation and behavior in selected cases justifies the need for the comparative analysis reported in this paper. Results have been obtained through simple examples, a single representative case-study already used in the context of both LIP's and EC and through extensive simulations over a suite of benchmarks

Bit-level pipelined digit-serial array processors

A new architecture for high performance digit-serial vector inner product (VIP) which can be pipelined to the bit-level is introduced. The design of the digit-serial vector inner product is based on a new systematic design methodology using radix-2n arithmetic. The proposed architecture allows a high level of bit-level pipelining to increase the throughput rate with minimum initial delay and minimum area. This will give designers greater flexibility in finding the best tradeoff between hardware cost and throughput rate. It is shown that sub-digit pipelined digit-serial structure can achieve a higher throughput rate with much less area consumption than an equivalent bit-parallel structure. A twin-pipe architecture to double the throughput rate of digit-serial multipliers and consequently that of the digit-serial vector inner product is also presented. The effect of the number of pipelining levels and the twin-pipe architecture on the throughput rate and hardware cost are discussed. A two's complement digit-serial architecture which can operate on both negative and positive numbers is also presented

Pipeline-Based Power Reduction in FPGA Applications

This paper shows how temporal parallelism has an important role in the power dissipation reduction in the FPGA field. Glitches propagation is blocked by the flip-flops or registers in the pipeline. Several multiplication structures are implemented over modern FPGAs, StratixII and Virtex4, comparing their results with and without pipeline and hardware duplication

Memory-Based High-Level Synthesis Optimizations Security Exploration on the Power Side-Channel

High-level synthesis (HLS) allows hardware designers to think algorithmically and not worry about low-level, cycle-by-cycle details. This provides the ability to quickly explore the architectural design space and tradeoffs between resource utilization and performance. Unfortunately, security evaluation is not a standard part of the HLS design flow. In this article, we aim to understand the effects of memory-based HLS optimizations on power side-channel leakage. We use Xilinx Vivado HLS to develop different cryptographic cores, implement them on a Spartan-6 FPGA, and collect power traces. We evaluate the designs with respect to resource utilization, performance, and information leakage through power consumption. We have two important observations and contributions. First, the choice of resource optimization directive results in different levels of side-channel vulnerabilities. Second, the partitioning optimization directive can greatly compromise the hardware cryptographic system through power side-channel leakage due to the deployment of memory control logic. We describe an evaluation procedure for power side-channel leakage and use it to make best-effort recommendations about how to design more secure architectures in the cryptographic domain

Transformations of High-Level Synthesis Codes for High-Performance Computing

Specialized hardware architectures promise a major step in performance and energy efficiency over the traditional load/store devices currently employed in large scale computing systems. The adoption of high-level synthesis (HLS) from languages such as C/C++ and OpenCL has greatly increased programmer productivity when designing for such platforms. While this has enabled a wider audience to target specialized hardware, the optimization principles known from traditional software design are no longer sufficient to implement high-performance codes. Fast and efficient codes for reconfigurable platforms are thus still challenging to design. To alleviate this, we present a set of optimizing transformations for HLS, targeting scalable and efficient architectures for high-performance computing (HPC) applications. Our work provides a toolbox for developers, where we systematically identify classes of transformations, the characteristics of their effect on the HLS code and the resulting hardware (e.g., increases data reuse or resource consumption), and the objectives that each transformation can target (e.g., resolve interface contention, or increase parallelism). We show how these can be used to efficiently exploit pipelining, on-chip distributed fast memory, and on-chip streaming dataflow, allowing for massively parallel architectures. To quantify the effect of our transformations, we use them to optimize a set of throughput-oriented FPGA kernels, demonstrating that our enhancements are sufficient to scale up parallelism within the hardware constraints. With the transformations covered, we hope to establish a common framework for performance engineers, compiler developers, and hardware developers, to tap into the performance potential offered by specialized hardware architectures using HLS

Square-rich fixed point polynomial evaluation on FPGAs

Polynomial evaluation is important across a wide range of application domains, so significant work has been done on accelerating its computation. The conventional algorithm, referred to as Horner's rule, involves the least number of steps but can lead to increased latency due to serial computation. Parallel evaluation algorithms such as Estrin's method have shorter latency than Horner's rule, but achieve this at the expense of large hardware overhead. This paper presents an efficient polynomial evaluation algorithm, which reforms the evaluation process to include an increased number of squaring steps. By using a squarer design that is more efficient than general multiplication, this can result in polynomial evaluation with a 57.9% latency reduction over Horner's rule and 14.6% over Estrin's method, while consuming less area than Horner's rule, when implemented on a Xilinx Virtex 6 FPGA. When applied in fixed point function evaluation, where precision requirements limit the rounding of operands, it still achieves a 52.4% performance gain compared to Horner's rule with only a 4% area overhead in evaluating 5th degree polynomials