Abstract: Prosthetic valves that include support arms extending from support posts thereof, and methods for utilizing such prosthetic valves, are disclosed herein. As one example, a prosthetic valve can include an annular frame movable between a radially compressed state and a radially expanded state, and at least one support arm. The frame can include a plurality of support posts, each extending between a post inflow end and an opposite post outflow end. The support arm can extend from a corresponding support post, and terminate at a free-ended tip which is biased radially away from the corresponding support post.

Abstract: A data storage device has an inference engine that can infer a read threshold based on a non-linear function of inputs that reflect current memory and data conditions. The read threshold can be used in reading a wordline in the memory. Using a machine-learning-based approach to infer a read threshold can provide significant improvement in read threshold accuracy, which can reduce bit error rate and also improve latency, throughput, power consumption, and quality of service.

Abstract: Methods and apparatus for power management in data storage devices are provided wherein conformal prediction is employed to determine correction terms for applying to power-per-processing event (P/PE) values. One such data storage device includes a non-volatile memory (NVM), a set of hardware processing engines, and a power sensor to detect a total power consumption of the set of hardware processing engines. A processor is configured to determine a P/PE value for each of the set of processing engines based on total power consumption measurements using a least squares procedure. A conformalization procedure is applied to sequences of P/PE values to calibrate the P/PE values by determining correction terms for applying to the P/PE values to provide guaranteed power prediction intervals. Delivery of power to the processing engines is then controlled based on the corrected P/PE event values in accordance with a power budget. On-line and off-line examples are provided.

Abstract: Methods and apparatus for energy management in data storage devices are provided. One such data storage device (DSD) includes a non-volatile memory (NVM), a set of hardware processing engines, and a power sensor to detect a total power consumption of the set of hardware processing engines. A processor is configured to determine an energy-per-processing event value for each of the set of processing engines based on total power consumption measurements and processing event duration values, then control energy delivery to the processing engines based on the energy-per-processing event values in accordance with an energy budget. In some examples, the DSD employs a least-squares procedure to estimate power-per-processing event values so the values can be determined without needing to measure individual power consumption of the processing engines. The power-per-processing event values are converted to energy-per-processing event values based on corresponding processing event durations.

Abstract: For bit errors caused by intrinsic cell variations, the bit errors are scattered across a page of memory. However, for bit errors caused by a physical issue in memory, the bit errors cluster together within the same memory area. In an example data storage device, a page of memory is divided into sections, and counters are used to count the number of errors in each section. A physical error location is detected if the number exceeds a parameter, and as compared to the number of errors in the other sections. In another example data storage device having an error correction code (ECC) engine, a histogram and binomial probability are used to detect physical errors. This has the advantage of detecting weak memory blocks that are about to fail, so the blocks can be retired early as a grown bad block.

Abstract: A method for positioning a robotic device connector relative to a body access point in a patient, including: coupling a robotic device to a movable base located at a distal end of an adjustable arm; manipulating the adjustable arm to align a connector of the robotic device with an elongate surgical tool extending from a body access point; linearly moving the movable base coupled to the robotic device towards the body access point to position the connector of the robotic device in proximity to a proximal end of the elongate surgical tool; connecting the proximal end of the elongate surgical tool to the connector of the robotic device

Abstract: A storage device includes a memory die and a controller. The controller identifies a dirty block that was subject to an interrupted I/O operation and performs a coarse inspection of the dirty block. Each iteration of the coarse inspection includes: requesting first bytes of a current page of the dirty block; receiving contents of the first bytes from the at least one memory die; and evaluating a state of the current page based on the contents of the first bytes. The controller also determines an initial last good page based on the coarse inspection and performs a fine inspection of at least one page based on a second number of bytes greater than the first number of bytes. The fine inspection validates the initial last good page and identifies the initial last good page as an actual last good page of the dirty block.

Abstract: The present disclosure generally relates to estimating when data to be written will be read or re-written prior to actually writing the data to the memory device. The estimating can be used to smartly route the data to the appropriate memory location at the writing stage or to evict the data from a hot memory location to a colder memory location. To perform the estimating, typical traces or data may be used as may the metadata of the data. Separating data according to the data “temperature” (i.e. the expected access time and frequency), and usage to optimize the SLC partition usage has meaningful impact on several storage metrics such as performance and endurance.

Abstract: A multi-gear ECC decoder includes a high power decoder and a low power decoder. In order to significantly reduce the decoding time for high-BER codewords using a slow high power decoder, rather than decoding codewords in either slow high power or fast low power, a controller switches between slow high power decoding and fast low power decoding during the decoding process. The controller first will determine, based on a predetermined factor, whether to start decoding in slow high power or fast low power. Once a decoding power is determined, then the decoding will begin. During the decoding process the decoding transitions from a first power lever decoder to a second power level decoder. The decoding will continue in the second decoding power level after the transition, until the decoding is completed or if another switch needs to occur for insufficient decoding.

Abstract: A system and method for calibrating read threshold voltages includes performing a plurality of read operations, determining to perform a read level tracking method, and performing the read level tracking method. The determining may be based on a temperature change or a bit error rate (BER). The read level tracking method includes determining the BER of an indicative word line, determining an adjusted read threshold level based on the BER, and adjusting read threshold levels according to the adjusted read threshold level.

Abstract: A storage device includes a memory die and a controller. The controller identifies a dirty block that was subject to an interrupted I/O operation and performs a coarse inspection of the dirty block. Each iteration of the coarse inspection includes: requesting first bytes of a current page of the dirty block; receiving contents of the first bytes from the at least one memory die; and evaluating a state of the current page based on the contents of the first bytes. The controller also determines an initial last good page based on the coarse inspection and performs a fine inspection of at least one page based on a second number of bytes greater than the first number of bytes. The fine inspection validates the initial last good page and identifies the initial last good page as an actual last good page of the dirty block.

Abstract: The disclosure relates in some aspects to on-chip processing circuitry formed within the die of a non-volatile (NVM) array to perform data searches. In some aspects, the die includes components configured to sense wordlines of stored data in the NVM array by applying voltages on the wordlines serially, and then search for an input data pattern within the serially-sensed wordlines. In some examples, the components of the die include latches and circuits configured to perform bitwise latch logic search operations. In other examples, the search components are configured with under-the-array or next-to-the-array dedicated search circuitry that uses registers and/or random access memory (RAM). Other aspects relate to a separate controller device for controlling the on-chip NVM search operations. For example, the controller may determine whether to search for data using search components of the NVM die or processors of the controller based, e.g., on a degree of fragmentation of data.

Abstract: Methods and apparatus for power management in data storage devices are provided. One such data storage device (DSD) includes a non-volatile memory (NVM), a set of hardware processing engines, and a power sensor to detect a total power consumption of the set of hardware processing engines. A processor is configured to determine a power-per-processing event value for each of the set of processing engines based on total power consumption measurements, then control delivery of power to the processing engines based on the power-per-processing event values in accordance with a power budget. In some examples, the DSD employs a least-squares procedure to estimate the power-per-processing event values so the values can be determined without needing to measure the individual power consumption of the processing engines. Exemplary processing engines include a Read engine, a Write engine, etc. A recursive least-squares update procedure is also described.

Abstract: Methods and apparatus for power management in data storage devices are provided. One such data storage device (DSD) includes a non-volatile memory (NVM), a set of hardware processing engines, and a power sensor to measure a total power consumption of the set of hardware processing engines. A processor is configured to determine a power-per-processing event value for each of the set of processing engines based on total power consumption measurements, then control delivery of power to the processing engines based on the power-per-processing event values in accordance with a power budget. In some examples, the DSD employs a least-squares procedure to estimate the power-per-processing event values so the values can be determined without needing to measure the individual power consumption of the processing engines. Procedures are also provided for assessing the accuracy of the power-per-processing event values and for controlling further operations based on the assessment.

Abstract: An apparatus includes a first encoder circuit configured to compress a block of data using dictionary based compression and a second encoder circuit connected to the first encoder circuit to receive the compressed block of data from the first encoder circuit. The second encoder circuit is configured to further compress the compressed block of data according to a codebook. The codebook is based on a distribution of data of a prior block of data or a distribution of data of a portion of the block of data that is less than the block of data. The operation of the second encoder circuit overlaps with the operation of the first encoder circuit to achieve high throughput and avoid the need for a large block of memory (e.g., SRAM) to occupy the data in flight until the second encoder circuit can start.

Abstract: A data storage device includes a memory device and a controller coupled to the memory device. The controller is configured to determine a read threshold on a wordline, adjust a read threshold voltage level associated with the read threshold, determine an adjusted read threshold at the adjusted read threshold voltage level, where the adjusted read threshold is different from the read threshold, compare the adjusted read threshold to the read threshold, and calibrate the read threshold based on the comparing. The controller is further configured to analyze a bit error rate (BER) difference based on the calibrating and/or a previous read threshold voltage level movement, choose a next target read threshold for next calibration, and read a second page at the next target read threshold.

Abstract: Low-density parity-check (LDPC) coding based on memory cell voltage distribution (CVD) in data storage devices. In one embodiment, a memory controller includes a memory interface configured to interface with a non-volatile memory; and a controller. The controller is configured to receive a plurality of data pages to be stored in the non-volatile memory, and transform the plurality of data pages into a plurality of transformed data pages. The controller is further configured to determine a plurality of parity bits based on the plurality of transformed data pages, and store the plurality of data pages and the plurality of parity bits in the non-volatile memory.

Abstract: Before a read threshold is needed to read a wordline in memory, a data storage device can infer a plurality of read thresholds based on possible conditions of the memory that may exist when the read threshold is eventually needed. When the read threshold is needed, it is selected from the previously-inferred read thresholds based on the current conditions of the memory. This can improve latency and throughput, improve quality of service, reduce power consumption, and reduce errors.

Abstract: A storage system has an inference engine that can infer a read threshold based on a plurality of parameters of the memory. The read threshold can be used in reading a wordline in the memory during a regular read operation or as part of an error handling process. Using this machine-learning-based approach to infer a read threshold can provide significant improvement in read threshold accuracy, which can reduce bit error rate and improve latency, throughput, power consumption, and quality of service. In another embodiment, a storage system is configured to use a binary full-depth symmetrically-sorted tree to infer a read threshold based on a plurality of parameters of the memory.