Biosequences analysis on NanoMagnet Logic

Wang, J.; Vacca, Marco; Graziano, Mariagrazia; Roch, Massimo Ruo; Zamboni, Maurizio

doi:10.1109/icicdt.2013.6563320

Cited by 15 publications

(15 citation statements)

References 13 publications

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“…Nevertheless, we can summarize that in CMOS it is possible to achieve a speed-up of 2:5Â without affecting area or power requirements significantly. Moreover a NML implementation has been proposed in [52]. The article shows how it is possible to interleave data also in the case of NML to increase throughput without changing the hardware structure.…”

Section: Case Study: Protein Alignment Systolic Arraymentioning

confidence: 99%

“…As described before, this allows to avoid retiming (that must take into account also the physical layout of the circuit) and yet obtain improvements using interleaving only. In [52] results show that CMOS circuit can operate at 370 MHz consuming 0:72 mW , while for NML the operating frequency is given by the technology and is 100 MHz and power consumption in the case of Magnetoelastic implementation is of 10 mW only. It is important to highlight that in NML without applying interleaving there must be a delay of 209 clock cycles between one input and the successive one, while with interleaving it is possible to provide one input at every clock cycle as it is in CMOS: this therefore proves the benefits that derive from the adoption of pipeline interleaving in this technology.…”

Section: Case Study: Protein Alignment Systolic Arraymentioning

confidence: 99%

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Interleaving in Systolic-Arrays: A Throughput Breakthrough

Causapruno

Vacca

Graziano

et al. 2015

IEEE Trans. Comput.

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In past years the most common way to improve computers performance was to increase the clock frequency. In recent years this approach suffered the limits of technology scaling, therefore computers architectures are shifting toward the direction of parallel computing to further improve circuits performance. Not only GPU based architectures are spreading in consideration, but also Systolic Arrays are particularly suited for certain classes of algorithms. An important point in favor of Systolic Arrays is that, due to the regularity of their circuit layout, they are appealing when applied to many emerging and very promising technologies, like Quantum-dot Cellular Automata and nanoarrays based on Silicon NanoWire or on Carbon nanotube Field Effect Transistors. In this work we present a systematic method to improve Systolic Arrays performance exploiting Pipelining and Input Data Interleaving. We tackle the problem from a theoretical point of view first, and then we apply it to both CMOS technology and emerging technologies. On CMOS we demonstrate that it is possible to vastly improve the overall throughput of the circuit. By applying this technique to emerging technologies we show that it is possible to overcome some of their limitations greatly improving the throughput, making a considerable step forward toward the post-CMOS era.Index Terms-Systolic arrays, CMOS, QCA, molecular QCA, nanoMagnet logic, NanoWire field effect transistor, interleaving Ç The authors are with the

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Section: Case Study: Protein Alignment Systolic Arraymentioning

confidence: 99%

Section: Case Study: Protein Alignment Systolic Arraymentioning

confidence: 99%

Interleaving in Systolic-Arrays: A Throughput Breakthrough

Causapruno

Vacca

Graziano

et al. 2015

IEEE Trans. Comput.

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“…Furthermore it is resistant to radiations and heat, being as a consequence a perfect candidate for military and space applications. Even more notably, it has also a potential very low power consumption with respect to stateof-the-art CMOS technology [15], confirming thus to be the possible candidate to solve those power issues that are the designer nightmares when dealing with forthcoming scaled CMOS technology nodes [16] [17].…”

Section: Introductionmentioning

confidence: 99%

“…CONTRIBUTIONS. After a short introduction on NML circuit layout and a discussion on the timing issues here mentioned in Section II, 1) we introduce in Section III the test architecture we implemented based on a complex systolic array circuit for Biosequence analysis [15]. This architecture represents itself a novelty for the state of the art in NML, because it is completely designed at the layout level and because it respects all the technological constraints, without relying on unrealistic assumptions.…”

Section: Introductionmentioning

confidence: 99%

Feedbacks in QCA: A Quantitative Approach

Vacca

Wang

Graziano

et al. 2015

IEEE Trans. VLSI Syst.

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In the post-CMOS scenario a primary role is played by Quantum dot Cellular Automata (QCA) technology. Irrespective of the specific implementation principle (e.g. either molecular, magnetic or semi-conductive in current scenario) the intrinsic deep-level pipelined behavior is the dominant issue. It has important consequences on circuit design and performance especially in presence of feedbacks in sequential circuits. Though partially already addressed in literature, these consequences still must be fully understood and solutions thoroughly approached in order to allow this technology any further advancement. This work conducts an exhaustive analysis of the effects and the consequences derived by the presence of loops in QCA circuits. For each problem arisen a solution is presented. The analysis is performed using as test architecture a complex systolic array circuit for biosequences analysis (Smith-Waterman algorithm) which represents one of the most promising application for QCA technology. The circuit is based on NanoMagnetic Logic as QCA implementation, is designed down to the layout level considering technological constraints and experimentally validated structures, counts up to approximately 2.3Ml nanomagnets, is described and simulated with HDL language using as a testbench realistic protein alignment sequences. The results here presented constitute a fundamental advancement in the emerging technologies field, since, 1) they are based on a quantitative approach relying on a realistic and complex circuit involving a large variety of QCA blocks, 2) they strictly are reckoned starting from current technological limits without relying on unrealistic assumptions, 3) they provide general rules to design complex sequential circuits with intrinsically pipelined technologies, like QCA, 4) they prove with a real application benchmark how to maximize the circuits performance.

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“…Then ToPoliNano can perform different analysis on the circuit layout, a logical simulation, a fault analysis and an area and power estimation. more complex and realistic circuits, like microprocessors [14], decoders for telecommunication [15] and a systolic array for biosequences analysis [16]. Due to the complexity of such circuits, finite element micromagnetic simulators cannot be used to verify the circuit functionality.…”

Section: Introductionmentioning

confidence: 99%

Physical design and testing of Nano Magnetic architectures

Turvani

Tohti

Bollo

et al. 2014

2014 9th IEEE International Conference on Design &Amp; Technology of Integrated Systems in Nanoscale Era (DTIS)

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Nano-Magnetic Logic (NML) is a promising candidate to substitute CMOS technology since it is characterized by very low power consumption and it can combine computation and memory in the same device. Several works analyze this technology at device level; nevertheless a higher level analysis is required to fully understand its potentials. It is actually fundamental to analyze how an architecture of realistic complexity can be really implemented taking into account the physical limits due to technology, and which performance it could consequently reach.We present here a physical design and test methodology based on our tool ToPoliNano, which allows analyzing circuits using models specifically targeted for this technology. We developed an automatic engine for placing and routing combinational NML circuits including as constraints realistic rules due to currently available fabrication processes. After the place and route phase, ToPoliNano also allows to perform a circuit logical simulation, detailed at the single nanomagnet level. Furthermore this tool has the ability to analyze and test circuits based on NML, considering the impact that process variations and faults have on the logical behavior of the circuit.

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Biosequences analysis on NanoMagnet Logic

Cited by 15 publications

References 13 publications

Interleaving in Systolic-Arrays: A Throughput Breakthrough

Interleaving in Systolic-Arrays: A Throughput Breakthrough

Feedbacks in QCA: A Quantitative Approach

Physical design and testing of Nano Magnetic architectures

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