Progress Toward a Magnet-Hall Effect Random Access Memory (MHRAM)
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Features of flash memories: Flash memories are non-volatile; that is they do not require power to retain the information in its memory. They can be erased and written to while the device is still in the circuit.
Computers with virtual memory architecture allow programs to be written as if they were small enough to be contained in memory. Two types of problems are investigated to show that this luxury can lead to quite an inefficient performance if the programmer does not interact strongly with the characteristics of the operating system when developing the program. The two problems considered are the simultaneous solutions of a large linear system of equations by Gaussian elimination and a model three-dimensional finite-difference problem. The Control Data STAR-100 computer runs are made to demonstrate the inefficiencies of programming the problems in the manner one would naturally do if the problems were indeed, small enough to be contained in memory. Program redesigns are presented which achieve large improvements in performance through changes in the computational procedure and the data base arrangement.
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This paper presents the results of measurements performed on two different flash memory types, NOR and NAND technologies.
A linear solver algorithm used by a large-scale unstructured-grid computational fluid dynamics application is examined for a broad range of familiar and emerging architectures. Efficient implementation of a linear solver is challenging on recent CPUs offering vector architectures. Vector loads and stores are essential to effectively utilize available memory bandwidth on CPUs, and maintaining performance across different CPUs can be difficult in the face of varying vector lengths offered by each. A similar challenge occurs on GPU architectures, where it is essential to have coalesced memory accesses to utilize memory bandwidth effectively. In this work, we demonstrate that restructuring a computation, and possibly data layout, with regard to architecture is essential to achieve optimal performance by establishing a performance benchmark for each target architecture in a low level language such as vector intrinsics or CUDA. In doing so, we demonstrate how a linear solver kernel can be mapped to Intel® Xeon™ and Xeon Phi™, Marvell® ThunderX2®, NEC® SX-Aurora™ TSUBASA Vector Engine, and NVIDIA® and AMD® GPUs. We further demonstrate that the required code restructuring can be achieved in higher level programming environments such as OpenACC, OCCA, and Intel® OneAPI™/SYCL, and that each generally results in optimal performance on the target architecture. Relative performance metrics for all implementations are shown, and subjective ratings for ease of implementation and optimization are suggested.
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High-electron-mobility sensor films deposited on superlattice buffer (strain) layers. Improved Hall-effect sensors offer combination of adequate response and high speed needed for use in micromagnet/Hall-effect random-access memories. Hall-effect material chosen for use in sensors is InAs.
The ramp-reversal memory (RRM) effect in metal–insulator transition metal oxides (TMOs), a non-volatile resistance change induced by repeated temperature cycling, has attracted considerable interest in neuromorphic computing and non-volatile memory devices. Our previous defect motion model successfully explained RRM in vanadium dioxide (VO 2 ), capturing observed critical temperature shifts and memory accumulation throughout the sample. However, this approach lacked interactions between metallic and insulating domains. Here, we extend our model by combining a correlated Random Field Ising Model with defect diffusion-segregation, enabling accurate hysteresis modeling while predicting the relationship between RRM and domain interactions. Our simulations demonstrate that the maximum RRM occurs when the turnaround temperature approaches the inflection point. This peak in RRM vs. turnaround temperature is consistent with prior transport measurements, as well as our own optical measurements reported here. Significantly, we find that increasing nearest-neighbor interactions enhances the maximum memory effect, thus providing a clear mechanism for optimizing RRM performance. Since our model employs minimal assumptions, we predict that RRM should be a widespread phenomenon in materials exhibiting patterned phase coexistence of electronic domains. This work not only advances fundamental understanding of memory behavior in TMOs but also establishes a much-needed theoretical framework for optimizing device applications.
The effect of using multiword addressing with laminated ferrite arrays was made. Both a reduction in the number of components, and a reduction in power consumption was obtained for memory capacities between one million bits and one million words. An investigation into the effect of variations in the processing steps resulted in a number of process modifications that improved the quality of the arrays. A feasibility model laminated ferrite memory system was constructed by modifying a commercial plated wire memory system to operate with laminated ferrite arrays. To provide flexibility for the testing of the laminated ferrite memory, an exerciser has been constructed to automatically control the loading and recirculation of arbitrary size checkerboard patterns of one's and zero's and to display the patterns of stored information on a CRT screen.
A new paradigm was developed to examine prospective memory performance in a visual-spatial task that resembles some aspects of the work of air traffic controllers. Two experiments examined the role of workload (number of aeroplanes that participants directed), delay (between receipt of prospective instructions and execution), and phonological rehearsal. High workload increased prospective memory errors but increasing delay from 1-3 or 5 minutes had no effect. Shadowing aurally presented text reduced prospective memory performance, presumably because it prevented verbal rehearsal of the prospective instructions. However, performance on the foreground task of directing aeroplanes to routine destinations was affected only by workload and not by opportunity for rehearsal. Our results suggest that ability to maintain performance on a routine foreground task while performing a secondary task--perhaps analogous to conversation--does not predict ability to retrieve a prospective intention to deviate from the routine.
Facilitating effect of repetition on recall of word from list of unconnected words
The martensitic transformation is a fundamental physical phenomenon at the origin of important industrial applications. However, the underlying microscopic mechanism, which is of critical importance to explain the outstanding mechanical properties of martensitic materials, is still not fully understood. This is because for most martensitic materials the transformation is a fast process that makes in situ studies extremely challenging. Noble solids krypton and xenon undergo a progressive pressure-induced face-centered cubic (fcc) to hexagonal close-packed (hcp) martensitic transition with a very wide coexistence domain. Here, we took advantage of this unique feature to study the detailed transformation progress at the atomic level by employing in situ x-ray diffraction and absorption spectroscopy. We evidenced a four-stage pathway and suggest that the lattice mismatch between the fcc and hcp forms plays a key role in the generation of strain. We also determined precisely the effect of the transformation on the compression behavior of these materials.
A data device includes a memory having a plurality of memory cells configured to store data values in accordance with a predetermined rank modulation scheme that is optional and a memory controller that receives a current error count from an error decoder of the data device for one or more data operations of the flash memory device and selects an operating mode for data scrubbing in accordance with the received error count and a program cycles count.
Memory storage requirements in space systems have steadily increased, much like storage requirements in terrestrial systems. Large arrays of dynamic memories (DRAMs) have been used in solid-state recorders, relying on a combination of shielding and error-detection-and correction (EDAC) to overcome the extreme sensitivity of DRAMs to space radiation. For example, a 2-Gbit memory (with 4-Mb DRAMs) used on the Clementine mission functioned perfectly during its moon mapping mission, in spite of an average of 71 memory bit flips per day from heavy ions. Although EDAC worked well with older types of memory circuits, newer DRAMs use extremely complex internal architectures which has made it increasingly difficult to implement EDAC. Some newer DRAMs have also exhibited catastrophic latchup. Flash memories are an intriguing alternative to DRAMs because of their nonvolatile storage and extremely high storage density, particularly for applications where writing is done relatively infrequently. This paper discusses radiation effects in advanced flash memories, including general observations on scaling and architecture as well as the specific experience obtained at the Jet Propulsion Laboratory in evaluating high-density flash memories for use on the NASA mission to Europa, one of Jupiter's moons. This particular mission must pass through the Jovian radiation belts, which imposes a very demanding radiation requirement.
We report the reversible stress-induced phase transformation in shape memory alloys (SMAs) is a dissipative process during which heat is absorbed or released. The inherent temperature variations inside the material has an elastocaloric effect (eCE) with appealing applications in solid-state cooling technology such as compact and efficient on-board refrigeration system for eletronic devices. In this manuscript, we conduct the first study of eCE of CuAlBe SMAs utilizing phase-field modeling. For an applied stress of 500 MPa, the results for polycrystalline Cu-Al11-2Be (at. %) show a minimum adiabatic unloading temperature change of -10 K over a pseudoelastic window of 40 K. In the absence of plastic deformation, the material demonstrates good reproducibility of the eCE over a few loading–unloading cycles. The presence of plastic deformation is found to cause functional fatigue that deteriorates the cooling capacity; however, the coefficient of performance only decreases from 9.04 to 8.03, which is still a very good value. These results place CuAlBe as a frontrunner SMA for solid-state cooling compared to the expensive NiTi.