An Experimental Study of Reduced-Voltage Operation in Modern FPGAs for Neural Network Acceleration

We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Network (CNN) accelerators mapped to Field Programmable Gate Arrays (FPGAs). Undervolting below a safe voltage level can lead to timing faults due to excessive circuit latency increase. We evaluate the reliability-power trade-off for such accelerators. Specifically, we experimentally study the reduced-voltage operation of multiple components of real FPGAs, characterize the corresponding reliability behavior of CNN accelerators, propose techniques to minimize the drawbacks of reduced-voltage operation, and combine undervolting with architectural CNN optimization techniques, i.e., quantization and pruning. We investigate the effect of environmental temperature on the reliability-power trade-off of such accelerators. We perform experiments on three identical samples of modern Xilinx ZCU102 FPGA platforms with five state-of-the-art image classification CNN benchmarks. This approach allows us to study the effects of our undervolting technique for both software and hardware variability. We achieve more than 3X power-efficiency (GOPs/W) gain via undervolting. 2.6X of this gain is the result of eliminating the voltage guardband region, i.e., the safe voltage region below the nominal level that is set by FPGA vendor to ensure correct functionality in worst-case environmental and circuit conditions. 43% of the power-efficiency gain is due to further undervolting below the guardband, which comes at the cost of accuracy loss in the CNN accelerator. We evaluate an effective frequency underscaling technique that prevents this accuracy loss, and find that it reduces the power-efficiency gain from 43% to 25%.Comment: To appear at the DSN 2020 conferenc

FPGA Energy Efficiency by Leveraging Thermal Margin

Cutting edge FPGAs are not energy efficient as conventionally presumed to be, and therefore, aggressive power-saving techniques have become imperative. The clock rate of an FPGA-mapped design is set based on worst-case conditions to ensure reliable operation under all circumstances. This usually leaves a considerable timing margin that can be exploited to reduce power consumption by scaling voltage without lowering clock frequency. There are hurdles for such opportunistic voltage scaling in FPGAs because (a) critical paths change with designs, making timing evaluation difficult as voltage changes, (b) each FPGA resource has particular power-delay trade-off with voltage, (c) data corruption of configuration cells and memory blocks further hampers voltage scaling. In this paper, we propose a systematical approach to leverage the available thermal headroom of FPGA-mapped designs for power and energy improvement. By comprehensively analyzing the timing and power consumption of FPGA building blocks under varying temperatures and voltages, we propose a thermal-aware voltage scaling flow that effectively utilizes the thermal margin to reduce power consumption without degrading performance. We show the proposed flow can be employed for energy optimization as well, whereby power consumption and delay are compromised to accomplish the tasks with minimum energy. Lastly, we propose a simulation framework to be able to examine the efficiency of the proposed method for other applications that are inherently tolerant to a certain amount of error, granting further power saving opportunity. Experimental results over a set of industrial benchmarks indicate up to 36% power reduction with the same performance, and 66% total energy saving when energy is the optimization target.Comment: Accepted in IEEE International Conference on Computer Design (ICCD) 201

Degradation in FPGAs: Monitoring, Modeling and Mitigation

This dissertation targets the transistor aging degradation as well as the associated thermal challenges in FPGAs (since there is an exponential relation between aging and chip temperature). The main objectives are to perform experimentation, analysis and device-level model abstraction for modeling the degradation in FPGAs, then to monitor the FPGA to keep track of aging rates and ultimately to propose an aging-aware FPGA design flow to mitigate the aging

Choose-Your-Own Adventure: A Lightweight, High-Performance Approach To Defect And Variation Mitigation In Reconfigurable Logic

For field-programmable gate arrays (FPGAs), fine-grained pre-computed alternative configurations, combined with simple test-based selection, produce limited per-chip specialization to counter yield loss, increased delay, and increased energy costs that come from fabrication defects and variation. This lightweight approach achieves much of the benefit of knowledge-based full specialization while reducing to practical, palatable levels the computational, testing, and load-time costs that obstruct the application of the knowledge-based approach. In practice this may more than double the power-limited computational capabilities of dies fabricated with 22nm technologies. Contributions of this work: • Choose-Your-own-Adventure (CYA), a novel, lightweight, scalable methodology to achieve defect and variation mitigation • Implementation of CYA, including preparatory components (generation of diverse alternative paths) and FPGA load-time components • Detailed performance characterization of CYA – Comparison to conventional loading and dynamic frequency and voltage scaling (DFVS) – Limit studies to characterize the quality of the CYA implementation and identify potential areas for further optimizatio

Dynamic Partial Reconfiguration for Dependable Systems

Moore’s law has served as goal and motivation for consumer electronics manufacturers in the last decades. The results in terms of processing power increase in the consumer electronics devices have been mainly achieved due to cost reduction and technology shrinking. However, reducing physical geometries mainly affects the electronic devices’ dependability, making them more sensitive to soft-errors like Single Event Transient (SET) of Single Event Upset (SEU) and hard (permanent) faults, e.g. due to aging effects. Accordingly, safety critical systems often rely on the adoption of old technology nodes, even if they introduce longer design time w.r.t. consumer electronics. In fact, functional safety requirements are increasingly pushing industry in developing innovative methodologies to design high-dependable systems with the required diagnostic coverage. On the other hand commercial off-the-shelf (COTS) devices adoption began to be considered for safety-related systems due to real-time requirements, the need for the implementation of computationally hungry algorithms and lower design costs. In this field FPGA market share is constantly increased, thanks to their flexibility and low non-recurrent engineering costs, making them suitable for a set of safety critical applications with low production volumes. The works presented in this thesis tries to face new dependability issues in modern reconfigurable systems, exploiting their special features to take proper counteractions with low impacton performances, namely Dynamic Partial Reconfiguration

Digital Circuit Design Using Floating Gate Transistors

Floating gate (flash) transistors are used exclusively for memory applications today. These applications include SD cards of various form factors, USB flash drives and SSDs. In this thesis, we explore the use of flash transistors to implement digital logic circuits. Since the threshold voltage of flash transistors can be modified at a fine granularity during programming, several advantages are obtained by our flash-based digital circuit design approach. For one, speed binning at the factory can be controlled with precision. Secondly, an IC can be re-programmed in the field, to negate effects such as aging, which has been a significant problem in recent times, particularly for mission-critical applications. Thirdly, unlike a regular MOSFET, which has one threshold voltage level, a flash transistor can have multiple threshold voltage levels. The benefit of having multiple threshold voltage levels in a flash transistor is that it allows the ability to encode more symbols in each device, unlike a regular MOSFET. This allows us to implement multi-valued logic functions natively. In this thesis, we evaluate different flash-based digital circuit design approaches and compare their performance with a traditional CMOS standard cell-based design approach. We begin by evaluating our design approach at the cell level to optimize the design’s delay, power energy and physical area characteristics. The flash-based approach is demonstrated to be better than the CMOS standard cell approach, for these performance metrics. Afterwards, we present the performance of our design approach at the block level. We describe a synthesis flow to decompose a circuit block into a network of interconnected flash-based circuit cells. We also describe techniques to optimize the resulting network of flash-based circuit cells using don’t cares. Our optimization approach distinguishes itself from other optimization techniques that use don’t cares, since it a) targets a flash-based design flow, b) optimizes clusters of logic nodes at once instead of one node at a time, c) attempts to reduce the number of cubes instead of reducing the number of literals in each cube and d) performs optimization on the post-technology mapped netlist which results in a direct improvement in result quality, as compared to pre-technology mapping logic optimization that is typically done in the literature. The resulting network characteristics (delay, power, energy and physical area) are presented. These results are compared with a standard cell-based realization of the same block (obtained using commercial tools) and we demonstrate significant improvements in all the design metrics. We also study flash-based FPGA designs (both static and dynamic), and present the tradeoff of delay, power dissipation and energy consumption of the various designs. Our work differs from previously proposed flash-based FPGAs, since we embed the flash transistors (which store the configuration bits) directly within the logic and interconnect fabrics. We also present a detailed description of how the programming of the configuration bits is accomplished, for all the proposed designs

Digital Circuit Design Using Floating Gate Transistors

Floating gate (flash) transistors are used exclusively for memory applications today. These applications include SD cards of various form factors, USB flash drives and SSDs. In this thesis, we explore the use of flash transistors to implement digital logic circuits. Since the threshold voltage of flash transistors can be modified at a fine granularity during programming, several advantages are obtained by our flash-based digital circuit design approach. For one, speed binning at the factory can be controlled with precision. Secondly, an IC can be re-programmed in the field, to negate effects such as aging, which has been a significant problem in recent times, particularly for mission-critical applications. Thirdly, unlike a regular MOSFET, which has one threshold voltage level, a flash transistor can have multiple threshold voltage levels. The benefit of having multiple threshold voltage levels in a flash transistor is that it allows the ability to encode more symbols in each device, unlike a regular MOSFET. This allows us to implement multi-valued logic functions natively. In this thesis, we evaluate different flash-based digital circuit design approaches and compare their performance with a traditional CMOS standard cell-based design approach. We begin by evaluating our design approach at the cell level to optimize the design’s delay, power energy and physical area characteristics. The flash-based approach is demonstrated to be better than the CMOS standard cell approach, for these performance metrics. Afterwards, we present the performance of our design approach at the block level. We describe a synthesis flow to decompose a circuit block into a network of interconnected flash-based circuit cells. We also describe techniques to optimize the resulting network of flash-based circuit cells using don’t cares. Our optimization approach distinguishes itself from other optimization techniques that use don’t cares, since it a) targets a flash-based design flow, b) optimizes clusters of logic nodes at once instead of one node at a time, c) attempts to reduce the number of cubes instead of reducing the number of literals in each cube and d) performs optimization on the post-technology mapped netlist which results in a direct improvement in result quality, as compared to pre-technology mapping logic optimization that is typically done in the literature. The resulting network characteristics (delay, power, energy and physical area) are presented. These results are compared with a standard cell-based realization of the same block (obtained using commercial tools) and we demonstrate significant improvements in all the design metrics. We also study flash-based FPGA designs (both static and dynamic), and present the tradeoff of delay, power dissipation and energy consumption of the various designs. Our work differs from previously proposed flash-based FPGAs, since we embed the flash transistors (which store the configuration bits) directly within the logic and interconnect fabrics. We also present a detailed description of how the programming of the configuration bits is accomplished, for all the proposed designs

An experimental study of reduced-voltage operation in modern FPGAs for neural network acceleration

We empirically evaluate an undervolting technique, i.e., underscaling the circuit supply voltage below the nominal level, to improve the power-efficiency of Convolutional Neural Network (CNN) accelerators mapped to Field Programmable Gate Arrays (FPGAs). Undervolting below a safe voltage level can lead to timing faults due to excessive circuit latency increase. We evaluate the reliability-power trade-off for such accelerators. Specifically, we experimentally study the reduced-voltage operation of multiple components of real FPGAs, characterize the corresponding reliability behavior of CNN accelerators, propose techniques to minimize the drawbacks of reduced-voltage operation, and combine undervolting with architectural CNN optimization techniques, i.e., quantization and pruning. We investigate the effect ofenvironmental temperature on the reliability-power trade-off of such accelerators. We perform experiments on three identical samples of modern Xilinx ZCU102 FPGA platforms with five state-of-the-art image classification CNN benchmarks. This approach allows us to study the effects of our undervolting technique for both software and hardware variability. We achieve more than 3X power-efficiency (GOPs/W ) gain via undervolting. 2.6X of this gain is the result of eliminating the voltage guardband region, i.e., the safe voltage region below the nominal level that is set by FPGA vendor to ensure correct functionality in worst-case environmental and circuit conditions. 43% of the power-efficiency gain is due to further undervolting below the guardband, which comes at the cost of accuracy loss in the CNN accelerator. We evaluate an effective frequency underscaling technique that prevents this accuracy loss, and find that it reduces the power-efficiency gain from 43% to 25%.The work done for this paper was partially supported by a HiPEAC Collaboration Grant funded by the H2020 HiPEAC Project under grant agreement No. 779656. The research leading to these results has received funding from the European Union’s Horizon 2020 Programme under the LEGaTO Project (www.legato-project.eu), grant agreement No. 780681.Peer ReviewedPostprint (author's final draft

Ingress of threshold voltage-triggered hardware trojan in the modern FPGA fabric–detection methodology and mitigation

The ageing phenomenon of negative bias temperature instability (NBTI) continues to challenge the dynamic thermal management of modern FPGAs. Increased transistor density leads to thermal accumulation and propagates higher and non-uniform temperature variations across the FPGA. This aggravates the impact of NBTI on key PMOS transistor parameters such as threshold voltage and drain current. Where it ages the transistors, with a successive reduction in FPGA lifetime and reliability, it also challenges its security. The ingress of threshold voltage-triggered hardware Trojan, a stealthy and malicious electronic circuit, in the modern FPGA, is one such potential threat that could exploit NBTI and severely affect its performance. The development of an effective and efficient countermeasure against it is, therefore, highly critical. Accordingly, we present a comprehensive FPGA security scheme, comprising novel elements of hardware Trojan infection, detection, and mitigation, to protect FPGA applications against the hardware Trojan. Built around the threat model of a naval warship’s integrated self-protection system (ISPS), we propose a threshold voltage-triggered hardware Trojan that operates in a threshold voltage region of 0.45V to 0.998V, consuming ultra-low power (10.5nW), and remaining stealthy with an area overhead as low as 1.5% for a 28 nm technology node. The hardware Trojan detection sub-scheme provides a unique lightweight threshold voltage-aware sensor with a detection sensitivity of 0.251mV/nA. With fixed and dynamic ring oscillator-based sensor segments, the precise measurement of frequency and delay variations in response to shifts in the threshold voltage of a PMOS transistor is also proposed. Finally, the FPGA security scheme is reinforced with an online transistor dynamic scaling (OTDS) to mitigate the impact of hardware Trojan through run-time tolerant circuitry capable of identifying critical gates with worst-case drain current degradation