8 research outputs found

    A thermally aware performance analysis of quantum cellular automata logic gates

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    The high-performance digital circuits can be constructed at high operating frequency, reduced power dissipation, portability, and large density. Using conventional complementary-metal-oxide-semiconductor (CMOS) design process, it is quite difficult to achieve ultra-high-speed circuits due to scaling problems. Recently quantum dot cellular automata (QCA) are prosed to develop logic circuits at atomic level. In this paper, we analyzed the performance of QCA circuits under different temperature effects and observed that polarization of the cells is highly sensitive to temperature. In case of the 3-input majority gate the cell polarization drops to 50% with an increase in the temperature of 18 K and for 5 input majority gate the cell polarization drops more quickly than the 3-input majority. Further, the performance of majority gates also compared in terms of area and power dissipation. It has been noticed that the proposed logic gates can also be used for developing simple and complex and memory circuits

    MFPA: Mixed-Signal Field Programmable Array for Energy-Aware Compressive Signal Processing

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    Compressive Sensing (CS) is a signal processing technique which reduces the number of samples taken per frame to decrease energy, storage, and data transmission overheads, as well as reducing time taken for data acquisition in time-critical applications. The tradeoff in such an approach is increased complexity of signal reconstruction. While several algorithms have been developed for CS signal reconstruction, hardware implementation of these algorithms is still an area of active research. Prior work has sought to utilize parallelism available in reconstruction algorithms to minimize hardware overheads; however, such approaches are limited by the underlying limitations in CMOS technology. Herein, the MFPA (Mixed-signal Field Programmable Array) approach is presented as a hybrid spin-CMOS reconfigurable fabric specifically designed for implementation of CS data sampling and signal reconstruction. The resulting fabric consists of 1) slice-organized analog blocks providing amplifiers, transistors, capacitors, and Magnetic Tunnel Junctions (MTJs) which are configurable to achieving square/square root operations required for calculating vector norms, 2) digital functional blocks which feature 6-input clockless lookup tables for computation of matrix inverse, and 3) an MRAM-based nonvolatile crossbar array for carrying out low-energy matrix-vector multiplication operations. The various functional blocks are connected via a global interconnect and spin-based analog-to-digital converters. Simulation results demonstrate significant energy and area benefits compared to equivalent CMOS digital implementations for each of the functional blocks used: this includes an 80% reduction in energy and 97% reduction in transistor count for the nonvolatile crossbar array, 80% standby power reduction and 25% reduced area footprint for the clockless lookup tables, and roughly 97% reduction in transistor count for a multiplier built using components from the analog blocks. Moreover, the proposed fabric yields 77% energy reduction compared to CMOS when used to implement CS reconstruction, in addition to latency improvements

    Architectural Solutions for NanoMagnet Logic

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    The successful era of CMOS technology is coming to an end. The limit on minimum fabrication dimensions of transistors and the increasing leakage power hinder the technological scaling that has characterized the last decades. In several different ways, this problem has been addressed changing the architectures implemented in CMOS, adopting parallel processors and thus increasing the throughput at the same operating frequency. However, architectural alternatives cannot be the definitive answer to a continuous increase in performance dictated by Moore’s law. This problem must be addressed from a technological point of view. Several alternative technologies that could substitute CMOS in next years are currently under study. Among them, magnetic technologies such as NanoMagnet Logic (NML) are interesting because they do not dissipate any leakage power. More- over, magnets have memory capability, so it is possible to merge logic and memory in the same device. However, magnetic circuits, and NML in this specific research, have also some important drawbacks that need to be addressed: first, the circuit clock frequency is limited to 100 MHz, to avoid errors in data propagation; second, there is a connection between circuit layout and timing, and in particular, longer wires will have longer latency. These drawbacks are intrinsic to the technology and for this reason they cannot be avoided. The only chance is to limit their impact from an architectural point of view. The first step followed in the research path of this thesis is indeed the choice and optimization of architectures able to deal with the problems of NML. Systolic Ar- rays are identified as an ideal solution for this technology, because they are regular structures with local interconnections that limit the long latency of wires; more- over they are composed of several Processing Elements that work in parallel, thus exploit parallelization to increase throughput (limiting the impact of the low clock frequency). Through the analysis of Systolic Arrays for NML, several possible im- provements have been identified and addressed: 1) it has been defined a rigorous way to increase throughput with interleaving, providing equations that allow to esti- mate the number of operations to be interleaved and the rules to provide inputs; 2) a latency insensitive circuit has been designed, that exploits a data communication protocol between processing elements to avoid data synchronization problems. This feature has been exploited to design a latency insensitive Systolic Array that is able to execute the Floyd-Steinberg dithering algorithm. All the improvements presented in this framework apply to Systolic Arrays implemented in any technology. So, they can also be exploited to increase performance of today’s CMOS parallel circuits. This research path is presented in Chapter 3. While Systolic Arrays are an interesting solution for NML, their usage could be quite limited because they are normally application-specific. The second re- search path addresses this problem. A Reconfigurable Systolic Array is presented, that can be programmed to execute several algorithms. This architecture has been tested implementing many algorithms, including FIR and IIR filters, Discrete Cosine Transform and Matrix Multiplication. This research path is presented in Chapter 4. In common Von Neumann architectures, the logic part of the circuit and the memory one are separated. Today bus communication between logic and memory represents the bottleneck of the system. This problem is addressed presenting Logic- In-Memory (LIM), an architecture where memory elements are merged in logic ones. This research path aims at defining a real LIM architectures. This has been done in two steps. The first step is represented by an architecture composed of three layers: memory, routing and logic. In the second step instead the routing plane is no more present, and its features are inherited by the memory plane. In this solution, a pyramidal memory model is used, where memories near logic elements contain the most probably used data, and other memory layers contain the remaining data and instruction set. This circuit has been tested with odd-even sort algorithms and it has been benchmarked against GPUs and ASIC. This research path is presented in Chapter 5. MagnetoElastic NML (ME-NML) is a technological improvement of the NML principle, proposed by researchers of Politecnico di Torino, where the clock system is based on the induced stretch of a piezoelectric substrate when a voltage is ap- plied to its boundaries. The main advantage of this solution is that it consumes much less power than the classic clock implementation. This technology has not yet been investigated from an architectural point of view and considering complex circuits. In this research field, a standard methodology for the design of ME-NML circuits has been proposed. It is based on a Standard Cell Library and an enhanced VHDL model. The effectiveness of this methodology has been proved designing a Galois Field Multiplier. Moreover the serial-parallel trade-off in ME-NML has been investigated, designing three different solutions for the Multiply and Accumulate structure. This research path is presented in Chapter 6. While ME-NML is an extremely interesting technology, it needs to be combined with other faster technologies to have a real competitive system. Signal interfaces between NML and other technologies (mainly CMOS) have been rarely presented in literature. A mixed-technology multiplexer is designed and presented as the basis for a CMOS to NML interface. The reverse interface (from ME-NML to CMOS) is instead based on a sensing circuit for the Faraday effect: a change in the polarization of a magnet induces an electric field that can be used to generate an input signal for a CMOS circuit. This research path is presented in Chapter 7. The research work presented in this thesis represents a fundamental milestone in the path towards nanotechnologies. The most important achievement is the de- sign and simulation of complex circuits with NML, benchmarking this technology with real application examples. The characterization of a technology considering complex functions is a major step to be performed and that has not yet been ad- dressed in literature for NML. Indeed, only in this way it is possible to intercept in advance any weakness of NanoMagnet Logic that cannot be discovered consid- ering only small circuits. Moreover, the architectural improvements introduced in this thesis, although technology-driven, can be actually applied to any technology. We have demonstrated the advantages that can derive applying them to CMOS cir- cuits. This thesis represents therefore a major step in two directions: the first is the enhancement of NML technology; the second is a general improvement of parallel architectures and the development of the new Logic-In-Memory paradigm

    Survey of FPGA applications in the period 2000 – 2015 (Technical Report)

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    Romoth J, Porrmann M, Rückert U. Survey of FPGA applications in the period 2000 – 2015 (Technical Report).; 2017.Since their introduction, FPGAs can be seen in more and more different fields of applications. The key advantage is the combination of software-like flexibility with the performance otherwise common to hardware. Nevertheless, every application field introduces special requirements to the used computational architecture. This paper provides an overview of the different topics FPGAs have been used for in the last 15 years of research and why they have been chosen over other processing units like e.g. CPUs

    Soft-Error Resilience Framework For Reliable and Energy-Efficient CMOS Logic and Spintronic Memory Architectures

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    The revolution in chip manufacturing processes spanning five decades has proliferated high performance and energy-efficient nano-electronic devices across all aspects of daily life. In recent years, CMOS technology scaling has realized billions of transistors within large-scale VLSI chips to elevate performance. However, these advancements have also continually augmented the impact of Single-Event Transient (SET) and Single-Event Upset (SEU) occurrences which precipitate a range of Soft-Error (SE) dependability issues. Consequently, soft-error mitigation techniques have become essential to improve systems\u27 reliability. Herein, first, we proposed optimized soft-error resilience designs to improve robustness of sub-micron computing systems. The proposed approaches were developed to deliver energy-efficiency and tolerate double/multiple errors simultaneously while incurring acceptable speed performance degradation compared to the prior work. Secondly, the impact of Process Variation (PV) at the Near-Threshold Voltage (NTV) region on redundancy-based SE-mitigation approaches for High-Performance Computing (HPC) systems was investigated to highlight the approach that can realize favorable attributes, such as reduced critical datapath delay variation and low speed degradation. Finally, recently, spin-based devices have been widely used to design Non-Volatile (NV) elements such as NV latches and flip-flops, which can be leveraged in normally-off computing architectures for Internet-of-Things (IoT) and energy-harvesting-powered applications. Thus, in the last portion of this dissertation, we design and evaluate for soft-error resilience NV-latching circuits that can achieve intriguing features, such as low energy consumption, high computing performance, and superior soft errors tolerance, i.e., concurrently able to tolerate Multiple Node Upset (MNU), to potentially become a mainstream solution for the aerospace and avionic nanoelectronics. Together, these objectives cooperate to increase energy-efficiency and soft errors mitigation resiliency of larger-scale emerging NV latching circuits within iso-energy constraints. In summary, addressing these reliability concerns is paramount to successful deployment of future reliable and energy-efficient CMOS logic and spintronic memory architectures with deeply-scaled devices operating at low-voltages

    Design of large polyphase filters in the Quadratic Residue Number System

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    Temperature aware power optimization for multicore floating-point units

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    Understanding Quantum Technologies 2022

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    Understanding Quantum Technologies 2022 is a creative-commons ebook that provides a unique 360 degrees overview of quantum technologies from science and technology to geopolitical and societal issues. It covers quantum physics history, quantum physics 101, gate-based quantum computing, quantum computing engineering (including quantum error corrections and quantum computing energetics), quantum computing hardware (all qubit types, including quantum annealing and quantum simulation paradigms, history, science, research, implementation and vendors), quantum enabling technologies (cryogenics, control electronics, photonics, components fabs, raw materials), quantum computing algorithms, software development tools and use cases, unconventional computing (potential alternatives to quantum and classical computing), quantum telecommunications and cryptography, quantum sensing, quantum technologies around the world, quantum technologies societal impact and even quantum fake sciences. The main audience are computer science engineers, developers and IT specialists as well as quantum scientists and students who want to acquire a global view of how quantum technologies work, and particularly quantum computing. This version is an extensive update to the 2021 edition published in October 2021.Comment: 1132 pages, 920 figures, Letter forma
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