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At least 919 records · Page 51

Three-dimensional stacked structured ASIC devices and methods of fabrication thereof

A 3D stacked sASIC is provided that includes a plurality of 2D reconfigurable structured structured ASIC (sASIC) levels interconnected through hard-wired arrays of 3D vias. The 2D sASIC levels may contain logic, memory, analog functions, and device input/output pad circuitry. During fabrication, these 2D sASIC levels are stacked on top of each other and fused together with 3D metal vias. Such 3D vias may be fabricated as through-silicon vias (TSVs). They may connect to the back-side of the 2D sASIC level, or they may be connected to top metal pads on the front-side of the 2D sASIC level.

36 MATERIALS SCIENCE↗

Energy-efficient Mott activation neuron for full-hardware implementation of neural networks

To circumvent the von Neumann bottleneck, substantial progress has been made towards in-memory computing with synaptic devices. However, compact nanodevices implementing non-linear activation functions are required for efficient full-hardware implementation of deep neural networks. Here, in this work, we present an energy-efficient and compact Mott activation neuron based on vanadium dioxide and its successful integration with a conductive bridge random access memory (CBRAM) crossbar array in hardware. The Mott activation neuron implements the rectified linear unit function in the analogue domain. The neuron devices consume substantially less energy and occupy two orders of magnitude smaller area than those of analogue complementary metal–oxide semiconductor implementations. The LeNet-5 network with Mott activation neurons achieves 98.38% accuracy on the MNIST dataset, close to the ideal software accuracy. We perform large-scale image edge detection using the Mott activation neurons integrated with a CBRAM crossbar array. Our findings provide a solution towards large-scale, highly parallel and energy-efficient in-memory computing systems for neural networks.

electrical and electronic engineering↗

Two-Way Communication Using RFID Equipment and Techniques

Equipment and techniques used in radio-frequency identification (RFID) would be extended, according to a proposal, to enable short-range, two-way communication between electronic products and host computers. In one example of a typical contemplated application, the purpose of the short-range radio communication would be to transfer image data from a user s digital still or video camera to the user s computer for recording and/or processing. The concept is also applicable to consumer electronic products other than digital cameras (for example, cellular telephones, portable computers, or motion sensors in alarm systems), and to a variety of industrial and scientific sensors and other devices that generate data. Until now, RFID has been used to exchange small amounts of mostly static information for identifying and tracking assets. Information pertaining to an asset (typically, an object in inventory to be tracked) is contained in miniature electronic circuitry in an RFID tag attached to the object. Conventional RFID equipment and techniques enable a host computer to read data from and, in some cases, to write data to, RFID tags, but they do not enable such additional functions as sending commands to, or retrieving possibly large quantities of dynamic data from, RFID-tagged devices. The proposal would enable such additional functions. The figure schematically depicts an implementation of the proposal for a sensory device (e.g., a digital camera) that includes circuitry that converts sensory information to digital data. In addition to the basic sensory device, there would be a controller and a memory that would store the sensor data and/or data from the controller. The device would also be equipped with a conventional RFID chipset and antenna, which would communicate with a host computer via an RFID reader. The controller would function partly as a communication interface, implementing two-way communication protocols at all levels (including RFID if needed) between the sensory device and the memory and between the host computer and the memory. The controller would perform power V

Jedry, Thomas↗

Upsets in Erased Floating Gate Cells With High-Energy Protons

We discuss upsets in erased floating gate cells, due to large threshold voltage shifts, using statistical distributions collected on a large number of memory cells. The spread in the neutral threshold voltage appears to be too low to quantitatively explain the experimental observations in terms of simple charge loss, at least in SLC devices. The possibility that memories exposed to high energy protons and heavy ions exhibit negative charge transfer between programmed and erased cells is investigated, although the analysis does not provide conclusive support to this hypothesis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Ultra-Fast Non-Volatile Resistive Switching Devices with Over 512 Distinct and Stable Levels for Memory and Neuromorphic Computing

Low-current multilevel programmability with inherent non-volatility and high stability of resistance states is required for both multi-bit memory storage and deep learning accelerators but is difficult to achieve. Here, in a resistive switching system, this work realizes >512 (>9 bits) distinct non-volatile conductance levels with stable retention for each state with current levels down to the nanoampere range, highly promising for potential integration with small processing nodes with ultra-low power consumption requirements. This is achieved by demonstrating a new thin film design concept that encompasses three key features: an ultra-thin epitaxial oxygen ionic switching layer that provides a tunable energy barrier at the bottom electrode, an overcoat amorphous layer that acts as an ion migration barrier for stable state retention, and a partial conductive filament as a localized electronic transport channel to the epitaxial switching layer. A large dynamic resistance range of up to seven orders of magnitude is achieved with reset-free transitions among intermediate states, and programmability is demonstrated with ultra-fast (20 ns) pulses. Artificial neural network (ANN) simulations, based on the experimental performance and its non-idealities, demonstrate close-to-ideal inference accuracies for various Modified National Institute of Standards and Technology (MNIST) data sets.

36 MATERIALS SCIENCE↗

Probing Phase Transformations and Microstructural Evolutions at the Small Scales: Synchrotron X-ray Microdiffraction for Advanced Applications in [Phase 3 Memory,] 3D IC (Integrated Circuits) and Solar PV (Photovoltaic) Devices

Synchrotron x-ray microdiffraction (μXRD) allows characterization of a crystalline material in small, localized volumes. Phase composition, crystal orientation and strain can all be probed in few-second time scales. Crystalline changes over a large areas can be also probed in a reasonable amount of time with submicron spatial resolution. However, despite all the listed capabilities, μXRD is mostly used to study pure materials but its application in actual device characterization is rather limited. This article will explore the recent developments of the μXRD technique illustrated with its advanced applications in microelectronic devices and solar photovoltaic systems. Application of μXRD in microelectronics will be illustrated by studying stress and microstructure evolution in Cu TSV (through silicon via) during and after annealing. Here, the approach allowing study of the microstructural evolution in the solder joint of crystalline Si solar cells due to thermal cycling will be also demonstrated.

36 MATERIALS SCIENCE↗

In-memory interconnect protocol configuration registers

Systems, apparatuses, and methods for moving the interconnect protocol configuration registers into the main memory space of a node. The region of memory used for storing the interconnect protocol configuration registers may also be made cacheable to reduce the latency of accesses to the interconnect protocol configuration registers. Interconnect protocol configuration registers which are used during a startup routine may be prefetched into the host's cache to make the startup routine more efficient. The interconnect protocol configuration registers for various interconnect protocols may include one or more of device capability tables, memory-side statistics (e.g., to support two-level memory data mapping decisions), advanced memory and interconnect features such as repair resources and routing tables, prefetching hints, error correcting code (ECC) bits, lists of device capabilities, set and store base address, capability, device ID, status, configuration, capabilities, and other settings.

97 MATHEMATICS AND COMPUTING↗

Reconfigurable Fault Tolerance for FPGAs

The invention allows a field-programmable gate array (FPGA) or similar device to be efficiently reconfigured in whole or in part to provide higher capacity, non-redundant operation. The redundant device consists of functional units such as adders or multipliers, configuration memory for the functional units, a programmable routing method, configuration memory for the routing method, and various other features such as block RAM, I/O (random access memory, input/output) capability, dedicated carry logic, etc. The redundant device has three identical sets of functional units and routing resources and majority voters that correct errors. The configuration memory may or may not be redundant, depending on need. For example, SRAM-based FPGAs will need some type of radiation-tolerant configuration memory, or they will need triple-redundant configuration memory. Flash or anti-fuse devices will generally not need redundant configuration memory. Some means of loading and verifying the configuration memory is also required. These are all components of the pre-existing redundant FPGA. This innovation modifies the voter to accept a MODE input, which specifies whether ordinary voting is to occur, or if redundancy is to be split. Generally, additional routing resources will also be required to pass data between sections of the device created by splitting the redundancy. In redundancy mode, the voters produce an output corresponding to the two inputs that agree, in the usual fashion. In the split mode, the voters select just one input and convey this to the output, ignoring the other inputs. In a dual-redundant system (as opposed to triple-redundant), instead of a voter, there is some means to latch or gate a state update only when both inputs agree. In this case, the invention would require modification of the latch or gate so that it would operate normally in redundant mode, and would separately latch or gate the inputs in non-redundant mode.

Shuler, Robert, Jr.↗

Phase-change heterostructure enables ultralow noise and drift for memory operation

Artificial intelligence and other data-intensive applications have escalated the demand for data storage and processing. New computing devices, such as phase-change random access memory (PCRAM)–based neuro-inspired devices, are promising options for breaking the von Neumann barrier by unifying storage with computing in memory cells. However, current PCRAM devices have considerable noise and drift in electrical resistance that erodes the precision and consistency of these devices. We designed a phase-change heterostructure (PCH) that consists of alternately stacked phase-change and confinement nanolayers to suppress the noise and drift, allowing reliable iterative RESET and cumulative SET operations for high-performance neuro-inspired computing. Our PCH architecture is amenable to industrial production as an intrinsic materials solution, without complex manufacturing procedure or much increased fabrication cost.

Science & Technology - Other Topics↗

Ferromagnetic (Ga,Mn)As nanostructures for spintronic applications

Magneto-resistive, cross-like nanostructures have been designed and fabricated by electron-beam lithography patterning and chemical etching from thin epitaxial layers of the ferromagnetic semiconductor (Ga,Mn)As. The nanostructures, composed of two perpendicular nanostripes crossing in the middle of their length, represent four-terminal devices, in which an electric current can be driven through any of the two nanostripes. In these devices, a novel magneto-resistive memory effect, related to a rearrangement of magnetic domain walls in the central part of the device, has been demonstrated. It consists in that the zero-field resistance of a nanostripe depends on the direction of previously applied magnetic field. The nanostructures can thus work as two-state devices providing basic elements of nonvolatile memory cells.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Data storage technology comparisons

The role of data storage and data storage technology is an integral, though conceptually often underestimated, portion of data processing technology. Data storage is important in the mass storage mode in which generated data is buffered for later use. But data storage technology is also important in the data flow mode when data are manipulated and hence required to flow between databases, datasets and processors. This latter mode is commonly associated with memory hierarchies which support computation. VLSI devices can reasonably be defined as electronic circuit devices such as channel and control electronics as well as highly integrated, solid-state devices that are fabricated using thin film deposition technology. VLSI devices in both capacities play an important role in data storage technology. In addition to random access memories (RAM), read-only memories (ROM), and other silicon-based variations such as PROM's, EPROM's, and EEPROM's, integrated devices find their way into a variety of memory technologies which offer significant performance advantages. These memory technologies include magnetic tape, magnetic disk, magneto-optic disk, and vertical Bloch line memory. In this paper, some comparison between selected technologies will be made to demonstrate why more than one memory technology exists today, based for example on access time and storage density at the active bit and system levels.

Katti, Romney R.↗

CG-Kit: Code Generation Toolkit for performant and maintainable variants of source code applied to Flash-X hydrodynamics simulations

CG-Kit is a new Code Generation tool-Kit that we have developed as a part of the solution for portability and maintainability for multiphysics computing applications. The development of CG-Kit is rooted in the urgent need created by the shifting landscape of high-performance computing platforms and the algorithmic complexities of a particular large-scale multiphysics application: Flash-X. To efficiently use computing resources on a heterogeneous node, an application must have a map of computation to resources and a mechanism to move the data and computation to the resources according to the map. Most existing performance portability solutions are focussed on abstracting the expression of computations so that a unified source code can be specialized to run on different resources. However, such an approach is insufficient for a code like Flash-X, which has a multitude of code components that can be assembled in various permutations and combinations to form different instances of applications. Similar challenges apply to any code that has composability, where a single specified way of apportioning work among devices may not be optimal. Additionally, use cases arise where the optimal control flow of computation may differ for different devices while the underlying numerics remain identical. This combination leads to unique challenges including handling an existing large code base in Fortran and/or C/C++, subdivision of code into a great variety of units supporting a wide range of physics and numerical methods, different parallelization techniques for distributed and shared memory systems and accelerator devices, and heterogeneity of computing platforms requiring coexisting variants of parallel algorithms. All of these challenges demand that scientific software developers apply existing knowledge about domain applications, algorithms, and computing platforms to determine custom abstractions and granularity for code generation. There is a critical lack of tools to tackle those problems. CG-Kit is designed to fill this gap by providing a user with the ability to express their desired control flow and computation-to-resource map in the form a pseudocode-like recipe. It consists of standalone tools that can be combined into highly specific and, we argue, highly effective portability and maintainability toolchains. Here we present the design of our new tools: parametrized source trees, control flow graphs, and recipes. The tools are implemented in Python. They are agnostic to the programming language of the source code targeted for code generation. In conclusion, we demonstrate the capabilities of the toolkit with two examples, first, multithreaded variants of the basic AXPY operation, and second, variants of parallel algorithms within a hydrodynamics solver, called Spark, from Flash-X that operates on block-structured adaptive meshes.

Algorithmic portability↗

Recent Advances in Commercial Memories and Potential Contribution to GN&C Miniaturation

The last few years have seen a surge in technology, device, and architecture introductions in commercial memories such as SDRAM and NAND driven by the explosion of handheld and portable electronics. Some of the resultant devices provide high density in very small and light packages, which may be possible to leverage for the miniaturization of future GN&C systems in addition to providing considerable memory capacity to enable advanced capabilities such as image-based navigation or adaptive/autonomous operations. We will show that these advanced SDRAM and NAND technologies are worth serious consideration for the next generation of GN&C needs by highlighting reliability and radiation effects results from some of these devices.

Yang-Scharlotta, Jean Y.↗

Content-addressable memory based enforcement of configurable policies

A monitoring device for monitoring transactions on a bus includes content-addressable memory ("CAM") and a response policy unit. The CAM includes an input coupled to receive a bus transaction tag based on bus traffic on the bus. The CAM stores data tags associated with rules of a security policy to compare the bus transaction tag to the data tags. The CAM generates an output signal indicating whether one or more matches occurred. The response policy unit is coupled to the CAM to receive the output signal from the CAM and to execute a policy action in response to the output signal.

97 MATHEMATICS AND COMPUTING↗

Field-induced domain wall motion of amorphous [CoSiB/Pt]{sub N} multilayers with perpendicular anisotropy

Amorphous CoSiB/Pt multilayer is a perpendicular magnetic anisotropy material to achieve high squareness, low coercivity, strong anisotropy, and smooth domain wall (DW) motion, because of the smoother interface compared with crystalline multilayers. For [CoSiB(6 Å)/Pt (14 Å)]{sub N} multilayers with N = 3, 6, and 9, we studied the field-induced DW dynamics. The effective anisotropy constant K{sub 1}{sup eff} is 1.5 × 10{sup 6} erg/cm{sup 3} for all the N values, and the linear increment of coercive field H{sub c} with N gives constant exchange coupling J. By analyzing the field dependence of DW images at room temperature, a clear creep motion with the exponent μ = 1/4 could be observed. Even though the pinning field H{sub dep} slightly increases with N, the pinning potential energy U{sub c} is constant (=35 k{sub B}T) for all the N values. These results imply that the amorphous [CoSiB/Pt]{sub N} multilayers are inherently homogeneous compared to crystalline multilayers. For N ≤ 6, the pinning site density ρ{sub pin} is less than 1000/μm{sup 2}, which is about 1 pinning site per the typical device junction size of 30 × 30 nm{sup 2}. Also, the exchange stiffness constant A{sub ex} is obtained to be 0.48 × 10{sup −6} erg/cm, and the domain wall width is expected to be smaller than 5.5 nm. These results may be applicable for spin-transfer-torque magnetic random access memory and DW logic device applications.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures

Efficient parallel implementations of scientific applications on multi-core CPUs with accelerators such as GPUs and Xeon Phis is challenging. This requires - exploiting the data parallel architecture of the accelerator along with the vector pipelines of modern x86 CPU architectures, load balancing, and efficient memory transfer between different devices. It is relatively easy to meet these requirements for highly structured scientific applications. In contrast, a number of scientific and engineering applications are unstructured. Getting performance on accelerators for these applications is extremely challenging because many of these applications employ irregular algorithms which exhibit data-dependent control-ow and irregular memory accesses. Furthermore, these applications are often iterative with dependency between steps, and thus making it hard to parallelize across steps. As a result, parallelism in these applications is often limited to a single step. Numerical simulation of charged particles beam dynamics is one such application where the distribution of work and memory access pattern at each time step is irregular. Applications with these properties tend to present significant branch and memory divergence, load imbalance between different processor cores, and poor compute and memory utilization. Prior research on parallelizing such irregular applications have been focused around optimizing the irregular, data-dependent memory accesses and control-ow during a single step of the application independent of the other steps, with the assumption that these patterns are completely unpredictable. We observed that the structure of computation leading to control-ow divergence and irregular memory accesses in one step is similar to that in the next step. It is possible to predict this structure in the current step by observing the computation structure of previous steps. In this dissertation, we present novel machine learning based optimization techniques to address the parallel implementation challenges of such irregular applications on different HPC architectures. In particular, we use supervised learning to predict the computation structure and use it to address the control-ow and memory access irregularities in the parallel implementation of such applications on GPUs, Xeon Phis, and heterogeneous architectures composed of multi-core CPUs with GPUs or Xeon Phis. We use numerical simulation of charged particles beam dynamics simulation as a motivating example throughout the dissertation to present our new approach, though they should be equally applicable to a wide range of irregular applications. The machine learning approach presented here use predictive analytics and forecasting techniques to adaptively model and track the irregular memory access pattern at each time step of the simulation to anticipate the future memory access pattern. Access pattern forecasts can then be used to formulate optimization decisions during application execution which improves the performance of the application at a future time step based on the observations from earlier time steps. In heterogeneous architectures, forecasts can also be used to improve the memory performance and resource utilization of all the processing units to deliver a good aggregate performance. We used these optimization techniques and anticipation strategy to design a cache-aware, memory efficient parallel algorithm to address the irregularities in the parallel implementation of charged particles beam dynamics simulation on different HPC architectures. Experimental result using a diverse mix of HPC architectures shows that our approach in using anticipation strategy is effective in maximizing data reuse, ensuring workload balance, minimizing branch and memory divergence, and in improving resource utilization.

Arumugam, Kamesh↗