This paper presents the optimal theoretical specifications of memcapacitors that allow them to surpass the existing state-of-the-art in-memory computing (IMC) prototypes in terms of energy efficiency and weight density. To do so, we build and simulate the SPICE model of an existing memcapacitor device in an IMC macro featuring charge-based computing. We develop the energy efficiency model and weight density model of the memcapacitor-based IMC macro, which are verified against SPICE simulation. Finally, we present the optimal theoretical specifications for memcapacitor devices to obtain a 10x improvement in energy efficiency and/or weight density over the existing IMC prototypes.

With expansion of neural network (NN) applications lowering their hardware implementation cost becomes an urgent task especially in back-end applications where the power-supply is limited. Stochastic computing (SC) is a promising solution to realize low-cost hardware designs. Implementation of matrix multiplication has been a bottleneck in previous stochastic neural networks (SC-NNs). In this paper, we introduce spintronic components into the design of SC-NNs. A novel spin-CMOS matrix multiplier is proposed in which the stochastic multiplications are performed by CMOS AND gates while the sum of products is implemented by spintronic compressor gates. The experimental results indicate that compared to the conventional binary implementations the proposed hybrid spin-CMOS architecture can achieve over 125x, 4.5x and 43x; reduction in terms of power, energy and area consumptions, respectively. Moreover, compared to previous CMOS-based SC-NNs, our design saves the power by 3.1x - 7.3x, reduces energy consumption by 3.1x - 7.3x and decreases area by 1.4x - 7.6x while maintaining similar recognition rates.

Many key technologies of our society, including so-called artificial intelligence (AI) and big data, have been enabled by the invention of transistor and its ever-decreasing size and ever-increasing integration at a large scale. However, conventional technologies are confronted with a clear scaling limit. Many recently proposed advanced transistor concepts are also facing an uphill battle in the lab because of necessary performance tradeoffs and limited scaling potential. We argue for a new pathway that could enable exponential scaling for multiple generations. This pathway involves layering multiple technologies that enable new functions beyond those available from conventional and newly proposed transistors. The key principles for this new pathway have been demonstrated through an interdisciplinary team effort at C-SPIN (a STARnet center), where systems designers, device builders, materials scientists and physicists have all worked under one umbrella to overcome key technology barriers. This paper reviews several successful outcomes from this effort on topics such as the spin memory, logic-in-memory, cognitive computing, stochastic and probabilistic computing and reconfigurable information processing.

As the end draws near for Moore's law, the search for low-power alternatives to complementary metal-oxide-semiconductor (CMOS) technology is intensifying. Among the various post-CMOS candidates, spintronic devices have gained special attention for their potential to overcome the power and performance limitations of CMOS. In particular, all spin logic (ASL) technology, which performs Boolean operations and transfers the output in the spin domain, has been proposed for enabling new capabilities-such as high density, low device count, and nonvolatility-that were previously impossible with CMOS technology. In this paper, first we provide an overview of the history and the current status of the various spintronic devices being pursued by the research community. Then, we describe how spin-based components are integrated into a computing system and the advantages that result. We use a hypothetical spintronic-based Intel Core i7 as a test vehicle to compare the system-level power requirements of ASL- and CMOS-based systems, taking into consideration the unique demands of spin-based interconnects. We conclude with a brief analysis of current limitations and future directions of spintronic research.

The theoretical lower limit of subthreshold swing in mosfets (60 mV/decade) significantly restricts low-voltage operation since it results in a low ON -to- OFF current ratio at low supply voltages. This paper investigates extremely low-power circuits based on new Si/SiGe heterojunction tunneling transistors (HETTs) that have a subthreshold swing of . Device characteristics, as determined through technology computer aided design tools, are used to develop a Verilog-A device model to simulate and evaluate a range of HETT-based circuits. We show that an HETT-based ring oscillator (RO) shows a 9-19 times reduction in dynamic power compared to a CMOS RO. We also explore two key differences between HETTs and traditional mosfets, namely, asymmetric current flow and increased Miller capacitance, analyze their effect on circuit behavior, and propose methods to address them. HETT characteristics have the most dramatic impact on static random access memory (SRAM) operation and we propose a novel seven-transistor HETT-based SRAM cell topology to overcome, and take advantage of, the asymmetric current flow. This new HETT SRAM design achieves 7-37 times reduction in leakage power compared to CMOS.

After decades of continuous scaling, further advancement of silicon microelectronics across the entire spectrum of computing applications is today limited by power dissipation. While the trade-off between power and performance is well-recognized, most recent studies focus on the extreme ends of this balance. By concentrating instead on an intermediate range, an ~ 8× improvement in power efficiency can be attained without system performance loss in parallelizable applications-those in which such efficiency is most critical. It is argued that power-efficient hardware is fundamentally limited by voltage scaling, which can be achieved only by blurring the boundaries between devices, circuits, and systems and cannot be realized by addressing any one area alone. By simultaneously considering all three perspectives, the major issues involved in improving power efficiency in light of performance and area constraints are identified. Solutions for the critical elements of a practical computing system are discussed, including the underlying logic device, associated cache memory, off-chip interconnect, and power delivery system. The IBM Blue Gene system is then presented as a case study to exemplify several proposed directions. Going forward, further power reduction may demand radical changes in device technologies and computer architecture; hence, a few such promising methods are briefly considered.

The theoretical lower limit of subthreshold swing in MOSFETs (60 mV/decade) significantly restricts low voltage operation since it results in a low ON to OFF current ratio at low supply voltages. This paper investigates extremely-low power circuits based on new Si/SiGe HEterojunction Tunneling Transistors (HETTs) that have subthreshold swing < 60 mV/decade. Device characteristics as determined through Technology Computer Aided Design (TCAD) tools are used to develop a Verilog-A device model to simulate and evaluate a range of HETT-based circuits. We show that a HETT-based ring oscillator (RO) shows a 9−19X reduction in dynamic power compared to a CMOS RO. We also explore two key differences between HETTs and traditional MOSFETs, namely asymmetric current flow and increased Miller capacitance, analyzing their effect on circuit behavior and proposing methods to address them. Finally, HETT characteristics have the most dramatic impact on SRAM operation and hence we propose a novel 7-transistor HETT-based SRAM cell topology to overcome, and take advantage of, the asymmetric current flow. This new HETT SRAM design achieves 7−37X reduction in leakage power compared to CMOS.

Despite generation upon generation of scaling, computer chips have until now remained essentially 2-dimensional. Improvements in on-chip wire delay and in the maximum number of I/O per chip have not been able to keep up with transistor performance growth; it has become steadily harder to hide the discrepancy. 3D chip technologies come in a number of flavors, but are expected to enable the extension of CMOS performance. Designing in three dimensions, however, forces the industry to look at formerly-two- dimensional integration issues quite differently, and requires the re-fitting of multiple existing EDA capabilities.