Abstract:
Method and apparatus for managing data in a memory. In accordance with some embodiments, a non-volatile (NV) buffer is adapted to store input write data having a selected logical address. A write circuit is adapted to transfer a copy of the input write data to an NV main memory while retaining the stored input write data in the NV buffer. A verify circuit is adapted to perform a verify operation at the conclusion of a predetermined elapsed time interval to verify successful transfer of the copy of the input write data to the NV main memory. The input write data are retained in the NV buffer until successful transfer is verified.
Abstract:
Devices and methods are disclosed for trusted listening. In some examples, an apparatus can include an audio receiving device having a microphone configured to capture sound and produce an audio signal, a processing unit configured to add a trusted signature to the audio signal, and an output configured to provide the audio signal. Further, a method of trusted listening can receive a first audio signal representing a real-time sound, generate a trusted signature in an audible format, and produce a second audio signal including the trusted signature.
Abstract:
Devices and methods are disclosed for trusted listening. In some examples, an apparatus can include an audio receiving device having a microphone configured to capture sound and produce an audio signal, a processing unit configured to add a trusted signature to the audio signal, and an output configured to provide the audio signal. Further, a method of trusted listening can receive a first audio signal representing a real-time sound, generate a trusted signature in an audible format, and produce a second audio signal including the trusted signature.
Abstract:
Mapping table entries that map logical block addresses to physical block addresses can be intercepted and compressed to save space. In some cases, the mapping table entries can be compressed into compression units, which can hold multiple mapping table entries. Portions of the mapping table entries can be arranged into groups, and a group can be compressed with a unique compression method. The compression method used to compress a group may be based on data characteristics of the group. When data corresponding to the mapping table entries are read or modified, the compressed data can be decompressed and provided to a requesting controller or processor. When the mapping table entry is modified, the updated mapping entry may be arranged into groups, and the groups can be compressed and stored to the compression units.
Abstract:
A data object is received at a storage compute device in response to a request from a host. A requirement of the data object is determined based on a computation to be performed on the data object. The requirement related to at least speed and capacity of media used to store the data object. A tier is selected from the storage compute device based on speed and capacity characteristics of the selected tier corresponding to the requirement of the data object. The data object is stored in the selected tier.
Abstract:
A system includes a plurality of nonvolatile memory cells and a map that assigns connections between nodes of a neural network to the memory cells. Memory devices containing nonvolatile memory cells and applicable circuitry for reading and writing may operate with the map. Information stored in the memory cells can represent weights of the connections. One or more neural processors can be present and configured to implement the neural network.
Abstract:
Systems and methods are disclosed for trusted imaging. In some examples, a trusted imaging device can emit a patterned light onto a real-world scene while an image sensor (e.g. photo or video) generates data representative of the real-world scene. The data can be processed to attempt to recover a pattern of the patterned light from the data. Whether, or to what extent, the pattern can be recovered can be determinative of a trustworthiness of the data from the image sensor. In further examples, the image data can be encrypted, as well as the imaging device output. In still further examples, a depth map of the image data can also be used to determine the trustworthiness of the image data.
Abstract:
A connection between a user device and a network server is established. Via the connection, a deep learning network is formed for a processing task. A first portion of the deep learning network operates on the user device and a second portion of the deep learning network operates on the network server. Based on cooperation between the user device and the network server, a boundary between the first portion and the second portion of the deep learning network is dynamically modified based on a change in a performance indicator that could affect the processing task.
Abstract:
An apparatus comprises a mass storage unit and a plurality of circuit modules including a machine learning module, a programmable state machine module, and input/output interfaces. Switching circuitry is configured to selectively couple the circuit modules. Configuration circuitry is configured to access configuration data from the mass storage unit and to operate the switching circuitry to connect the circuit modules according to the configuration data.