다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

International Technology Roadmap for Semiconductors 2003の要求清浄度について － シリコンウエハ表面と雰囲気環境に要求される清浄度, 分析方法の現状について －

Modern computers are based on the von Neumann architecture in which computation and storage are physically separated: data are fetched from the memory unit, shuttled to the processing unit (where computation takes place) and then shuttled back to the memory unit to be stored. The rate at which data can be transferred between the processing unit and the memory unit represents a fundamental limitation of modern computers, known as the memory wall. In-memory computing is an approach that attempts to address this issue by designing systems that compute within the memory, thus eliminating the energy-intensive and time-consuming data movement that plagues current designs. Here we review the development of in-memory computing using resistive switching devices, where the two-terminal structure of the devices, their resistive switching properties, and direct data processing in the memory can enable area- and energy-efficient computation. We examine the different digital, analogue, and stochastic computing schemes that have been proposed, and explore the microscopic physical mechanisms involved. Finally, we discuss the challenges in-memory computing faces, including the required scaling characteristics, in delivering next-generation computing. This Review Article examines the development of in-memory computing using resistive switching devices.

/pdf/in-memory-computing-with-resistive-switching-devices-1mv368csjy.pdf

In-memory computing with resistive switching devices

http://user.it.uu.se/~jarst116/slides/week4.pdf

Graph-Based Algorithms for Boolean Function Manipulation

The development of silicon semiconductor technology has produced breakthroughs in electronics—from the microprocessor in the late 1960s to early 1970s, to automation, computers and smartphones—by downscaling the physical size of devices and wires to the nanometre regime. Now, graphene and related two-dimensional (2D) materials offer prospects of unprecedented advances in device performance at the atomic limit, and a synergistic combination of 2D materials with silicon chips promises a heterogeneous platform to deliver massively enhanced potential based on silicon technology. Integration is achieved via three-dimensional monolithic construction of multifunctional high-rise 2D silicon chips, enabling enhanced performance by exploiting the vertical direction and the functional diversification of the silicon platform for applications in opto-electronics and sensing. Here we review the opportunities, progress and challenges of integrating atomically thin materials with silicon-based nanosystems, and also consider the prospects for computational and non-computational applications. Progress in integrating atomically thin two-dimensional materials with silicon-based technology is reviewed, together with the associated opportunities and challenges, and a roadmap for future applications is presented.

Graphene and two-dimensional materials for silicon technology.

We fabricated and characterized new ambipolar silicon nanowire (SiNW) FET transistors featuring two independent gate-all-around electrodes and vertically stacked SiNW channels. One gate electrode enables dynamic configuration of the device polarity (n or p-type), while the other switches on/off the device. Measurement results on silicon show I on /I off > 106 and S ≈ 64mV/dec (70mV/dec) for p(n)-type operation in the same device. We show that XOR operation is embedded in the device characteristic, and we demonstrate for the first time a fully functional 2-transistor XOR gate.

/pdf/polarity-control-in-double-gate-gate-all-around-vertically-24c6amc24x.pdf

Polarity control in double-gate, gate-all-around vertically stacked silicon nanowire FETs

In this paper, we present the EPFL combinational benchmark suite. We aim at completing existing benchmark suites by focusing only on natively combinational benchmarks. The EPFL combinational benchmark suite consists of 23 combinational circuits designed to challenge modern logic optimization tools. It is further divided into three parts. The first part includes 10 arithmetic benchmarks, e.g., square-root, hypotenuse, divisor, multiplier etc.. The second part consists of 10 random/control benchmarks, e.g., round-robin arbiter, lookahead XY router, alu control unit, memory controller etc.. The third part contains 3 very large circuits, featuring more than ten million gates each. All benchmarks have a moderate number of inputs/outputs ranging from few tens to about one thousand. The EPFL benchmark suite is available to the public and distributed in all Verilog, VHDL, BLIF and AIGER formats. In addition to providing the benchmarks, we keep track of the best optimization results, mapped into LUT-6, for size and depth metrics. Better logic implementations can be submitted online. After combinational equivalence checking tests, the best LUT-6 realizations will be included in the benchmark suite together with the author’s name and affiliation.

The EPFL Combinational Benchmark Suite

In this paper, we propose a paradigm shift in representing and optimizing logic by using only majority (MAJ) and inversion (INV) functions as basic operations. We represent logic functions by majority-inverter graph (MIG): a directed acyclic graph consisting of three-input majority nodes and regular/complemented edges. We optimize MIGs via a new Boolean algebra, based exclusively on majority and inversion operations, that we formally axiomatize in this paper. As a complement to MIG algebraic optimization, we develop powerful Boolean methods exploiting global properties of MIGs, such as bit-error masking. MIG algebraic and Boolean methods together attain very high optimization quality. Considering the set of IWLS’05 benchmarks, our MIG optimizer (MIGhty) enables a 7% depth reduction in LUT-6 circuits mapped by ABC while also reducing size and power activity, with respect to similar and-inverter graph (AIG) optimization. Focusing on arithmetic intensive benchmarks instead, MIGhty enables a 16% depth reduction in LUT-6 circuits mapped by ABC, again with respect to similar AIG optimization. Employed as front-end to a delay-critical 22-nm application-specified integrated circuit flow (logic synthesis + physical design) MIGhty reduces the average delay/area/power by 13%/4%/3%, respectively, over 31 academic and industrial benchmarks. We also demonstrate delay/area/power improvements by 10%/10%/5% for a commercial FPGA flow.

/pdf/majority-inverter-graph-a-new-paradigm-for-logic-8k6eiebvjb.pdf

Majority-Inverter Graph: A New Paradigm for Logic Optimization

In this paper, we present Majority-Inverter Graph (MIG), a novel logic representation structure for efficient optimization of Boolean functions. An MIG is a directed acyclic graph consisting of three-input majority nodes and regular/complemented edges. We show that MIGs include any AND/OR/Inverter Graphs (AOIGs), containing also the well-known AIGs. In order to support the natural manipulation of MIGs, we introduce a new Boolean algebra, based exclusively on majority and inverter operations, with a complete axiomatic system. Theoretical results show that it is possible to explore the entire MIG representation space by using only five primitive transformation rules. Such feature opens up a great opportunity for logic optimization and synthesis. We showcase the MIG potential by proposing a delay-oriented optimization technique. Experimental results over MCNC benchmarks show that MIG optimization reduces the number of logic levels by 18%, on average, with respect to AIG optimization performed by ABC academic tool. Employed in a traditional optimization-mapping circuit synthesis flow, MIG optimization enables an average reduction of {22%, 14%, 11%} in the estimated {delay, area, power} metrics, before physical design, as compared to academic/commercial synthesis flows.

/pdf/majority-inverter-graph-a-novel-data-structure-and-41kjqdwrap.pdf

Majority-Inverter Graph: A Novel Data-Structure and Algorithms for Efficient Logic Optimization

3-D sequential integration stands out from other 3-D schemes as it enables the full use of the third dimension. Indeed, in this approach, 3-D contact density matches with the transistor scale. In this paper, we report on the main advances enabling the demonstration of functional and performant stacked CMOS-FETs; i.e., wafer bonding, low temperature processes (<;650°C) and salicide stabilization achievements. This integration scheme enables fine grain partitioning and thus a gain in performance versus cost ratio linked to separation of heterogeneous technologies on distinct levels. In this work, we will detail examples taking advantage of the unique 3-D contact pitch achieved with sequential 3-D.

Pierre-Emmanuel Gaillardon

Papers

Polarity control in double-gate, gate-all-around vertically stacked silicon nanowire FETs

The EPFL Combinational Benchmark Suite

Majority-Inverter Graph: A New Paradigm for Logic Optimization

Majority-Inverter Graph: A Novel Data-Structure and Algorithms for Efficient Logic Optimization

3-D Sequential Integration: A Key Enabling Technology for Heterogeneous Co-Integration of New Function With CMOS