399 research outputs found

    Automating defects simulation and fault modeling for SRAMs

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    The continues improvement in manufacturing process density for very deep sub micron technologies constantly leads to new classes of defects in memory devices. Exploring the effect of fabrication defects in future technologies, and identifying new classes of realistic functional fault models with their corresponding test sequences, is a time consuming task up to now mainly performed by hand. This paper proposes a new approach to automate this procedure. The proposed method exploits the capabilities of evolutionary algorithms to automatically identify faulty behaviors into defective memories and to define the corresponding fault models and relevant test sequences. Target defects are modeled at the electrical level in order to optimize the results to the specific technology and memory architecture

    Effects of cosmic rays on single event upsets

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    Assistance was provided to the Brookhaven Single Event Upset (SEU) Test Facility. Computer codes were developed for fragmentation and secondary radiation affecting Very Large Scale Integration (VLSI) in space. A computer controlled CV (HP4192) test was developed for Terman analysis. Also developed were high speed parametric tests which are independent of operator judgment and a charge pumping technique for measurement of D(sub it) (E). The X-ray secondary effects, and parametric degradation as a function of dose rate were simulated. The SPICE simulation of static RAMs with various resistor filters was tested

    Integration of a Digital Built-in Self-Test for On-Chip Memories

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    The ability of testing on-chip circuitry is extremely essential to ASIC implemen- tations today. However, providing functional tests and verification for on-chip (embedded) memories always poses a huge number of challenges to the designer. Therefore, a co-existing automated built-in self-test block with the Design Under Test (DUT) seems crucial to provide comprehensive, efficient and robust testing features. The target DUT of this thesis project is the state-of-the-arts Ultra Low Power (ULP) dual-port SRAMs designed in ASIC group of EIT department at Lund University. This thesis starts from system RTL modeling and verification from an earlier project, and then goes through ASIC design phase in 28 nm FD-SOI technology from ST-Microelectronics. All scripts during the ASIC design phase are developed in TCL. This design is implemented with multiple power domains (using CPF approach and introducing level-shifters at crossing-points between domains) and multiple clock sources in order to make it possible to perform various measurements with a high reliability on different flavours of a dual-port SRAM.This design is able to reduce dramatically the complexity of verification and measurement to integrated memories. This digital integrated circuit (IC) is developed as an application-specific IC (ASIC) chip for functional verification of integrated memories and measuring them in different aspects such as power consumption. The design is automated and capable of being reconfigured easily in terms of required actions and data for testing on-chip memories. Put it in other words, this design has automated and optimized the generation of what data to be stored on which location on memories as well as how they have been treated and interpreted later on. For instance, it refreshes and delivers different operation modes and working patterns to the entire test system in order to fully utilize integrated memories, of which such an automation is instructed by the stimuli to the chip. Besides, the pattern generation of the stimuli is implemented on MATLAB in an automated way. Due to constant advancements in chip manufacturing technology, more devices are squeezed into the same silicon area. Meaning that in order to monitor more internal signals introduced by the increased complexity of the circuits, more dedicated input/output ports (the physical interface between the chip internal signals and outside world) are required, that makes the chip bonding and testing in the future difficult and time-consuming. Additionally, memories usually have a bigger number of pins for signal reactions than other circuit blocks do, the method of dealing with so many pins should also be taken into account. Thus, a few techniques are adopted in this system to assist the designers deal with all mentioned issues. Once the ASIC chip has been fabricated (manufactured) and bonded, the on-chip memories can be tested directly on a printed circuit board in a simple and flexible way: Once test instruction input is loaded into the chip, the system starts to update the system settings and then to generate the internal configurations(parameters) so that all different operations, modes or instructions related to memory testing are automatically processed

    Non-invasive Techniques Towards Recovering Highly Secure Unclonable Cryptographic Keys and Detecting Counterfeit Memory Chips

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    Due to the ubiquitous presence of memory components in all electronic computing systems, memory-based signatures are considered low-cost alternatives to generate unique device identifiers (IDs) and cryptographic keys. On the one hand, this unique device ID can potentially be used to identify major types of device counterfeitings such as remarked, overproduced, and cloned. On the other hand, memory-based cryptographic keys are commercially used in many cryptographic applications such as securing software IP, encrypting key vault, anchoring device root of trust, and device authentication for could services. As memory components generate this signature in runtime rather than storing them in memory, an attacker cannot clone/copy the signature and reuse them in malicious activity. However, to ensure the desired level of security, signatures generated from two different memory chips should be completely random and uncorrelated from each other. Traditionally, memory-based signatures are considered unique and uncorrelated due to the random variation in the manufacturing process. Unfortunately, in previous studies, many deterministic components of the manufacturing process, such as memory architecture, layout, systematic process variation, device package, are ignored. This dissertation shows that these deterministic factors can significantly correlate two memory signatures if those two memory chips share the same manufacturing resources (i.e., manufacturing facility, specification set, design file, etc.). We demonstrate that this signature correlation can be used to detect major counterfeit types in a non-invasive and low-cost manner. Furthermore, we use this signature correlation as side-channel information to attack memory-based cryptographic keys. We validate our contribution by collecting data from several commercially available off-the-shelf (COTS) memory chips/modules and considering different usage-case scenarios

    TuRaN: True Random Number Generation Using Supply Voltage Underscaling in SRAMs

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    Prior works propose SRAM-based TRNGs that extract entropy from SRAM arrays. SRAM arrays are widely used in a majority of specialized or general-purpose chips that perform the computation to store data inside the chip. Thus, SRAM-based TRNGs present a low-cost alternative to dedicated hardware TRNGs. However, existing SRAM-based TRNGs suffer from 1) low TRNG throughput, 2) high energy consumption, 3) high TRNG latency, and 4) the inability to generate true random numbers continuously, which limits the application space of SRAM-based TRNGs. Our goal in this paper is to design an SRAM-based TRNG that overcomes these four key limitations and thus, extends the application space of SRAM-based TRNGs. To this end, we propose TuRaN, a new high-throughput, energy-efficient, and low-latency SRAM-based TRNG that can sustain continuous operation. TuRaN leverages the key observation that accessing SRAM cells results in random access failures when the supply voltage is reduced below the manufacturer-recommended supply voltage. TuRaN generates random numbers at high throughput by repeatedly accessing SRAM cells with reduced supply voltage and post-processing the resulting random faults using the SHA-256 hash function. To demonstrate the feasibility of TuRaN, we conduct SPICE simulations on different process nodes and analyze the potential of access failure for use as an entropy source. We verify and support our simulation results by conducting real-world experiments on two commercial off-the-shelf FPGA boards. We evaluate the quality of the random numbers generated by TuRaN using the widely-adopted NIST standard randomness tests and observe that TuRaN passes all tests. TuRaN generates true random numbers with (i) an average (maximum) throughput of 1.6Gbps (1.812Gbps), (ii) 0.11nJ/bit energy consumption, and (iii) 278.46us latency

    On the Evaluation of SEEs on Open-Source Embedded Static RAMs

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    3Static RAM modules are widely adopted in high performance systems. Single Event Effects (SEEs) resilient memories are required in many embedded systems applied in automotive and aerospace applications to increase their overall resiliency against SEEs. The current SEE resilient SRAM modules are obtained by applying radiation-hardened by design solutions which leads to elevated area overhead and difficulty to tune the resiliency capability with respect to the particle’s radiation profile. To overcome these limitations, we propose a methodology for the analysis and mitigation of embedded SRAMs generated by the OpenRAM memory compiler. A technology-oriented radiation analysis tool is presented to support the interaction of the charged radiation particles with the SRAM layout and depict the sensitive transistors of the SRAM memory. A selective duplication of the sensitive transistors has been applied to the 6T-SRAM cell designed at the layout level. The designed cell is included in the OpenRAM compiler and used to generate a mitigated 8Kb SRAM-bank. We evaluated the SEEs sensitivity by comparative simulation-based radiation analysis observing a reduction more than 6 times with respect to the original 6T-SRAM cell for the SEE sensitivity at high energy heavy ions particles, with negligible degradation of operations margins and power consumption and area overhead of less than ̴4%.partially_openopenAzimi, Sarah; De Sio, Corrado; Sterpone, LucaAzimi, Sarah; De Sio, Corrado; Sterpone, Luc

    Low-power and application-specific SRAM design for energy-efficient motion estimation

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 181-189).Video content is expected to account for 70% of total mobile data traffic in 2015. High efficiency video coding, in this context, is crucial for lowering the transmission and storage costs for portable electronics. However, modern video coding standards impose a large hardware complexity. Hence, energy-efficiency of these hardware blocks is becoming more critical than ever before for mobile devices. SRAMs are critical components in almost all SoCs affecting the overall energy-efficiency. This thesis focuses on algorithm and architecture development as well as low-power and application-specific SRAM design targeting motion estimation. First, a motion estimation design is considered for the next generation video standard, HEVC. Hardware cost and coding efficiency trade-offs are quantified and an optimum design choice between hardware complexity and coding efficiency is proposed. Hardware-efficient search algorithm, shared search range across CU engines and pixel pre-fetching algorithms provide 4.3x area, 56x on-chip bandwidth and 151 x off-chip bandwidth reduction. Second, a highly-parallel motion estimation design targeting ultra-low voltage operation and supporting AVC/H.264 and VC-1 standards are considered. Hardware reconfigurability along with frame and macro-block parallel processing are implemented for this engine to maximize hardware sharing between multiple standards and to meet throughput constraints. Third, in the context of low-power SRAMs, a 6T and an 8T SRAM are designed in 28nm and 45nm CMOS technologies targeting low voltage operation. The 6T design achieves operation down to 0.6V and the 8T design achieves operation down to 0.5V providing ~ 2.8x and ~ 4.8x reduction in energy/access respectively. Finally, an application-specific SRAM design targeted for motion estimation is developed. Utilizing the correlation of pixel data to reduce bit-line switching activity, this SRAM achieves up to 1.9x energy savings compared to a similar conventional 8T design. These savings demonstrate that application-specific SRAM design can introduce a new dimension and can be combined with voltage scaling to maximize energy-efficiency.by Mahmut Ersin Sinangil.Ph.D
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