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

Towards a Secure and Reliable System

Abstract. In this article we describe a system based on a 32-bit processor, Leon, complete with security features offered by a specific cryptographic AES IP. Hardening is done not only on the principal hardware components but on the operating system as well, with attention for possible interaction between the different levels. The cryptographic IP is protected too to offer good resistance against, for example, fault-based attacks

The Design of A High Capacity and Energy Efficient Phase Change Main Memory

Higher energy-efficiency has become essential in servers for a variety of reasons that range from heavy power and thermal constraints, environmental issues and financial savings. With main memory responsible for at least 30% of the energy consumed by a server, a low power main memory is fundamental to achieving this energy efficiency DRAM has been the technology of choice for main memory for the last three decades primarily because it traditionally combined relatively low power, high performance, low cost and high density. However, with DRAM nearing its density limit, alternative low-power memory technologies, such as Phase-change memory (PCM), have become a feasible replacement. PCM limitations, such as limited endurance and low write performance, preclude simple drop-in replacement and require new architectures and algorithms to be developed. A PCM main memory architecture (PMMA) is introduced in this dissertation, utilizing both DRAM and PCM, to create an energy-efficient main memory that is able to replace a DRAM-only memory. PMMA utilizes a number of techniques and architectural changes to achieve a level of performance that is par with DRAM. PMMA achieves gains in energy-delay of up to 65%, with less than 5% of performance loss and extremely high energy gains. To address the other major shortcoming of PCM, namely limited endurance, a novel, low- overhead wear-leveling algorithm that builds on PMMA is proposed that increases the lifetime of PMMA to match the expected server lifetime so that both server and memory subsystems become obsolete at about the same time. We also study how to better use the excess capacity, traditionally available on PCM devices, to obtain the highest lifetime possible. We show that under specific endurance distributions, the naive choice does not achieve the highest lifetime. We devise rules that empower the designer to select algorithms and parameters to achieve higher lifetime or simplify the design knowing the impact on the lifetime. The techniques presented also apply to other storage class memories (SCM) memories that suffer from limited endurance

Signal Processing for Caching Networks and Non-volatile Memories

The recent information explosion has created a pressing need for faster and more reliable data storage and transmission schemes. This thesis focuses on two systems: caching networks and non-volatile storage systems. It proposes network protocols to improve the efficiency of information delivery and signal processing schemes to reduce errors at the physical layer as well. This thesis first investigates caching and delivery strategies for content delivery networks. Caching has been investigated as a useful technique to reduce the network burden by prefetching some contents during o˙-peak hours. Coded caching [1] proposed by Maddah-Ali and Niesen is the foundation of our algorithms and it has been shown to be a useful technique which can reduce peak traffic rates by encoding transmissions so that different users can extract different information from the same packet. Content delivery networks store information distributed across multiple servers, so as to balance the load and avoid unrecoverable losses in case of node or disk failures. On one hand, distributed storage limits the capability of combining content from different servers into a single message, causing performance losses in coded caching schemes. But, on the other hand, the inherent redundancy existing in distributed storage systems can be used to improve the performance of those schemes through parallelism. This thesis proposes a scheme combining distributed storage of the content in multiple servers and an efficient coded caching algorithm for delivery to the users. This scheme is shown to reduce the peak transmission rate below that of state-of-the-art algorithms

Resilience of an embedded architecture using hardware redundancy

In the last decade the dominance of the general computing systems market has being replaced by embedded systems with billions of units manufactured every year. Embedded systems appear in contexts where continuous operation is of utmost importance and failure can be profound. Nowadays, radiation poses a serious threat to the reliable operation of safety-critical systems. Fault avoidance techniques, such as radiation hardening, have been commonly used in space applications. However, these components are expensive, lag behind commercial components with regards to performance and do not provide 100% fault elimination. Without fault tolerant mechanisms, many of these faults can become errors at the application or system level, which in turn, can result in catastrophic failures. In this work we study the concepts of fault tolerance and dependability and extend these concepts providing our own definition of resilience. We analyse the physics of radiation-induced faults, the damage mechanisms of particles and the process that leads to computing failures. We provide extensive taxonomies of 1) existing fault tolerant techniques and of 2) the effects of radiation in state-of-the-art electronics, analysing and comparing their characteristics. We propose a detailed model of faults and provide a classification of the different types of faults at various levels. We introduce an algorithm of fault tolerance and define the system states and actions necessary to implement it. We introduce novel hardware and system software techniques that provide a more efficient combination of reliability, performance and power consumption than existing techniques. We propose a new element of the system called syndrome that is the core of a resilient architecture whose software and hardware can adapt to reliable and unreliable environments. We implement a software simulator and disassembler and introduce a testing framework in combination with ERA’s assembler and commercial hardware simulators

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

Fault Tolerant Cryptographic Primitives for Space Applications

Spacecrafts are extensively used by public and private sectors to support a variety of services. Considering the cost and the strategic importance of these spacecrafts, there has been an increasing demand to utilize strong cryptographic primitives to assure their security. Moreover, it is of utmost importance to consider fault tolerance in their designs due to the harsh environment found in space, while keeping low area and power consumption. The problem of recovering spacecrafts from failures or attacks, and bringing them back to an operational and safe state is crucial for reliability. Despite the recent interest in incorporating on-board security, there is limited research in this area. This research proposes a trusted hardware module approach for recovering the spacecrafts subsystems and their cryptographic capabilities after an attack or a major failure has happened. The proposed fault tolerant trusted modules are capable of performing platform restoration as well as recovering the cryptographic capabilities of the spacecraft. This research also proposes efficient fault tolerant architectures for the secure hash (SHA-2) and message authentication code (HMAC) algorithms. The proposed architectures are the first in the literature to detect and correct errors by using Hamming codes to protect the main registers. Furthermore, a quantitative analysis of the probability of failure of the proposed fault tolerance mechanisms is introduced. Based upon an extensive set of experimental results along with probability of failure analysis, it was possible to show that the proposed fault tolerant scheme based on information redundancy leads to a better implementation and provides better SEU resistance than the traditional Triple Modular Redundancy (TMR). The fault tolerant cryptographic primitives introduced in this research are of crucial importance for the implementation of on-board security in spacecrafts

Robust design of deep-submicron digital circuits

Avec l'augmentation de la probabilité de fautes dans les circuits numériques, les systèmes développés pour les environnements critiques comme les centrales nucléaires, les avions et les applications spatiales doivent être certifies selon des normes industrielles. Cette thèse est un résultat d'une cooperation CIFRE entre l'entreprise Électricité de France (EDF) R&D et Télécom Paristech. EDF est l'un des plus gros producteurs d'énergie au monde et possède de nombreuses centrales nucléaires. Les systèmes de contrôle-commande utilisé dans les centrales sont basés sur des dispositifs électroniques, qui doivent être certifiés selon des normes industrielles comme la CEI 62566, la CEI 60987 et la CEI 61513 à cause de la criticité de l'environnement nucléaire. En particulier, l'utilisation des dispositifs programmables comme les FPGAs peut être considérée comme un défi du fait que la fonctionnalité du dispositif est définie par le concepteur seulement après sa conception physique. Le travail présenté dans ce mémoire porte sur la conception de nouvelles méthodes d'analyse de la fiabilité aussi bien que des méthodes d'amélioration de la fiabilité d'un circuit numérique.The design of circuits to operate at critical environments, such as those used in control-command systems at nuclear power plants, is becoming a great challenge with the technology scaling. These circuits have to pass through a number of tests and analysis procedures in order to be qualified to operate. In case of nuclear power plants, safety is considered as a very high priority constraint, and circuits designed to operate under such critical environment must be in accordance with several technical standards such as the IEC 62566, the IEC 60987, and the IEC 61513. In such standards, reliability is treated as a main consideration, and methods to analyze and improve the circuit reliability are highly required. The present dissertation introduces some methods to analyze and to improve the reliability of circuits in order to facilitate their qualification according to the aforementioned technical standards. Concerning reliability analysis, we first present a fault-injection based tool used to assess the reliability of digital circuits. Next, we introduce a method to evaluate the reliability of circuits taking into account the ability of a given application to tolerate errors. Concerning reliability improvement techniques, first two different strategies to selectively harden a circuit are proposed. Finally, a method to automatically partition a TMR design based on a given reliability requirement is introduced.PARIS-Télécom ParisTech (751132302) / SudocSudocFranceF