Conventional power system graphic applications use absolute coordinates approach, in which the objects are positioned with respect to a common origin. This can result in problems of re-adjustment and ...re-alignment in the network and substation diagrams when editing or merging the graphics. This paper introduces the notion of layouts and proposes a graphics model to facilitate positioning of graphical elements relative to each other in a hierarchy of layouts, thereby making the network diagrams flexible, sharable and extensible. This proposed graphics model, expressed in unified modeling language (UML), is shown to be compatible with the existing common information model (CIM) graphics model IEC 61970-453. Consequently, the need for extension of CIM graphics model is justified and an extension is proposed. Another key feature of the proposed model is configurability. Since the necessary parameters are explicitly modeled, the user only needs to provide configuration information describing the hierarchical connectivity of the substation or the network. The absolute coordinates can be calculated from the configuration and the power system diagrams can be auto-generated. This paper demonstrates the above benefits highlighting the technologies for implementation. Case study on 400-kV 20-substation diagrams of Maharashtra system in India is presented.
A ferroelectric FET (FeFET), made by integrating a ferroelectric material layer in the gate stack of a MOSFET, is a device that can behave as both a transistor and a non-volatile storage element. ...This unique property of FeFETs enables area efficient and low-power merged logic and memory functionality, desirable for many data analytic and machine learning applications. To best exploit this unique feature of FeFETs, cross-layer design practices spanning from circuits and architectures to algorithms and applications is needed. The paper presents FeFET-based circuits and architectures that offer, either independently or in a configurable fashion, content addressable memory (TCAM) and general-purpose compute-in-memory (GP-CiM) functionalities. These in-memory computing modules bring new opportunities to accelerating data-intensive applications. We discuss the use of these FeFET based in-memory computing fabrics in meta-learning applications, specifically as attentional memory. System-level task mapping and end-to-end evaluation will be discussed.
Although compute-in-memory (CIM) is considered as one of the promising solutions to overcome memory wall problem, the variations in analog voltage computation and analog-to-digital-converter (ADC) ...cost still remain as design challenges. In this paper, we present a 7T SRAM CIM that seamlessly supports multiply-accumulation (MAC) operation between 4-bit inputs and 8-bit weights. In the proposed CIM, highly parallel and robust MAC operations are enabled by exploiting the bit-line charge-sharing scheme to simultaneously process multiple inputs. For the readout of analog MAC values, instead of adopting the conventional ADC structure, the bit-line charge-sharing is efficiently used to reduce the implementation cost of the reference voltage generations. Based on the in-SRAM reference voltage generation and the parallel analog readout in all columns, the proposed CIM efficiently reduces ADC power and area cost. In addition, the variation models from Monte-Carlo simulations are also used during training to reduce the accuracy drop due to process variations. The implementation of 256×64 7T SRAM CIM using 28nm CMOS process shows that it operates in the wide voltage range from 0.6V to 1.2V with energy efficiency of 45.8-TOPS/W at 0.6V.
Compute in memory ( C iM) is a promising solution for solving the bottleneck of frequent data interface between memory and processor in Von-Neumann architecture. In this work, a hybrid current/charge ...domain 7T-SRAM based CiM architecture is proposed to mitigate the PVT-induced RBL variation during computation and thus offer a better linearity without significant impact on the operating frequency and area efficiency. Additionally, a column-referenced 1b to 5b reconfigurable SAR ADC is proposed to support multi-bit output. The proposed design is verified by the Monte-Carlo simulations using 40nm CMOS technology. The 5b mode ADC transferred MAC curve's DNL (LSB) ranges from −0.025 to 0.02 and INL (LSB) ranges from −0.13 to 0.25. The largest RBL variation (\sigma) from MAC value −64 to MAC value +64 is 2.08 mV, resulting in a MNIST classification accuracy of 97.5%, which is only 0.1% degradation and Google Speech Command classification accuracy of 80.5%, which is only 0.5% degradation compared to the software baseline, respectively. The whole architecture offers energy efficiency of 282-to-607 TOPS/W for 1-5b output in the MAC operation, which is competitive when compared to other state-of-art C iM architectures.
This paper presents a low cost PMOS-based 8T (P-8T) SRAM Compute-In-Memory (CIM) architecture that efficiently per-forms the multiply-accumulate (MAC) operations between 4-bit input activations and ...8-bit weights. First, bit-line (BL) charge-sharing technique is employed to design the low-cost and reliable digital-to-analog conversion of 4-bit input activations in the pro-posed SRAM CIM, where the charge domain analog computing provides variation tolerant and linear MAC outputs. The 16 local arrays are also effectively exploited to implement the analog mul-tiplication unit (AMU) that simultaneously produces 16 multipli-cation results between 4-bit input activations and 1-bit weights. For the hardware cost reduction of analog-to-digital converter (ADC) without sacrificing DNN accuracy, hardware aware system simulations are performed to decide the ADC bit-resolutions and the number of activated rows in the proposed CIM macro. In addition, for the ADC operation, the AMU-based reference col-umns are utilized for generating ADC reference voltages, with which low-cost 4-bit coarse-fine flash ADC has been designed. The 256×80 P-8T SRAM CIM macro implementation using 28nm CMOS process shows that the proposed CIM shows the accuracies of 91.46% and 66.67% with CIFAR-10 and CIFAR-100 dataset, respectively, with the energy efficiency of 50.07-TOPS/W.
This letter presents an energy-efficient sparsity-aware reconfigurable-precision compute-in-memory (CIM) 8T-SRAM macro for machine learning (ML) applications. The proposed macro dynamically leverages ...workload sparsity by reconfiguring the output precision in the peripheral circuitry without degrading application accuracy. Specifically, we propose a new energy-efficient reconfigurable-precision SAR ADC design with the ability to form ( n+m)-bit precision using n-bit and m-bit ADCs. Additionally, the transimpedance amplifier (TIA) "required to convert the summed current into voltage before conversion" is reconfigured based on sparsity to improve sense margin at lower output precision. The proposed macro, fabricated in 65-nm technology, provides 35.5-127.2 TOPS/W as the ADC precision varies from 6 to 2 bit, respectively.
Energy efficient, high throughput, noise immune, high density HZO FeFET Computation-in-Memory (CiM) is proposed. Local Multiply & Global Accumulate Array is realized by source-follower read, which ...multiplies neural network inputs and weights (FeFET V TH ), and charge-sharing, which accumulates multiplied values. Proposed CiM is immune to read-disturb. After 10-year data-retention, 3 bit/cell FeFET is feasible. ×64 energy efficient, 66 TOPS/W, reliable multiply-accumulate (MAC) operation is achieved.
Computing-in-memory (CIM) structures are meant to overcome the memory bottleneck and improve energy efficiency for artificial intelligence (AI) edge devices. In this article, we review recent trends ...in the development of CIM macros for the Internet of Things and AI applications. We also look at recent advances in the development of CIMs based on SRAM and nonvolatile memory for AI edge devices as well as the challenges involved in circuit design.
Background
Wheat is the most important crop around the world. Drought stresses affect wheat production and their characterization. Most of the traits that are affected by drought are quantitative ...traits, so detection of the quantitative trait’s loci (QTLs) related to these traits is very important for breeder and wheat producers. In this trend, 285 F2 individuals from crosses between four bread wheat genotypes (
Triticum aestivum
L.), i.e., Sakha93, Sids1, Sakha94, and Gemmiza9, were used for identified QTLs associated with plant height (PH) and leaf wilting (LW). Single marker analysis and composite interval mapping (CIM) were used.
Results
A total of 116 QTLs loci were detected which covered 19 chromosomes out of the 21 chromosomes of wheat. PH and LW had 74 and 42 QTLs loci, respectively. On the other hand, chromosome 7A showed to bear the highest number of QTLs loci (15 loci). While chromosome 1A beard the highest number of QTLs loci related to PH (10 loci), chromosome 2B and 7A beard the highest number of QTLs related LW. We highly recommend our finding to help breeders in wheat breeding programs to improve plant height and leaf wilting.
Conclusion
Our investigation concluded that SSR markers have high efficiency in the identification of QTLs related to abiotic stress; also the CIM method had more advanced priority for QTLs mapping.
A coupled extended finite element method (XFEM) is presented here for modeling propagation of fluid-driven fractures in different regimes including toughness- and viscosity-dominated regimes. The ...extended finite element method allows to model growth, and coalescence of arbitrary discontinuities (fractures) without requiring the mesh to conform to discontinuities nor significant refinement near the fractures. Fluid-driven fractures propagation is a coupled, nonlinear and non-local problem with moving boundary conditions. The proposed method is based on the extended finite element method with modifications to incorporate variable stress singularity at the crack tips for the transition between toughness-dominated and viscosity-dominated regimes. These modifications consist of enriched functions that are initially inspired by the asymptotic analytical solutions. The standard extended finite element approximation is enriched by adding near tip asymptotic solutions just for displacements, however the proposed method introduces a consistent enriched function for fluid pressure calculations close to the fracture tips to catch the singularity. Additionally, a technique is presented to remove singularity issue for required numerical integrations. Green's functions concept is proposed here to expedite calculations. To circumvent violation of partition of unity and parasitic terms in the approximation space induced by the blending elements at the edge of the enriched domain, the ramp function is utilized to improve the convergence rate. Stress intensity factors are calculated using a new contour integral method that can handle cases with different tip singularities. The proposed technique is verified with the cases that have analytical solutions. Some examples are presented to show the advantages of this technique in comparison to the regular XFEM.
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