Micron Technology Incorporated

Samuel E Bradshaw

Justin M Eno

Sean Stephen Eilert

Ameen D Akel

Dmitri A Yudanov

Kenneth Marion Curewitz

Shivasankar Gunasekaran

Shivam Swami

Hongyu Wang

Edward C McGlaughlin

Sai Krishna Mylavarapu

Jeffrey L McVay

Yves Constantin Tchapda

Stephen John Marshall

Niels Reimers

In a mobile device, processes of an application can be monitored and scored for initial data distribution. Specifically, a method can include monitoring processes of an application, and scoring objects or components used by the processes to determine placement of the objects or components in memory during initiation of the application. The method can also include, during initiation of the application, loading, into a first portion of the memory, at least partially, the objects or components scored at a first level. The method can also include, during initiation of the application, loading, into a second portion of the memory, at least partially, the objects or components scored at a second level. The objects or components scored at the second level can be less critical to the application than the objects or components scored at the first level.

Initial data distribution for different application processes

Systems, methods and apparatuses of Artificial Neural Network (ANN) applications implemented via Memory as a Service (MaaS) are described. For example, a computing system can include a computing device and a remote device. The computing device can borrow memory from the remote device over a wired or wireless network. Through the borrowed memory, the computing device and the remote device can collaborate with each other in storing an artificial neural network and in processing based on the artificial neural network. Some layers of the artificial neural network can be stored in the memory loaned by the remote device to the computing device. The remote device can perform the computation of the layers stored in the borrowed memory on behalf of the computing device. When the network connection degrades, the computing device can use an alternative module to function as a substitute of the layers stored in the borrowed memory.

Memory as a service for artificial neural network (ANN) applications

Systems, methods and apparatuses to provide memory as a service are described. For example, a borrower device is configured to: communicate with a lender device; borrow an amount of memory from the lender device; expand memory capacity of the borrower device for applications running on the borrower device, using at least the local memory of the borrower device and the amount of memory borrowed from the lender device; and service accesses by the applications to memory via communication link between the borrower device and the lender device.

Inter operating system memory services over communication network connections

Customized root processes for groups of applications in a computing device. A computing device (e.g., a mobile device) can monitor usage of applications. The device can then store data related to the usage of the applications, and group the applications into groups according to the stored data. The device can customize and execute a root process for a group of applications according to usage common to each application in the group. The device can generate patterns of prior executions shared amongst the applications in the group based on the stored data common to each application in the group, and execute the root process of the group according to the patterns. The device can receive a request to start an application from the group from a user of the device, and start the application upon receiving the request and by using the root process of the group of applications.

Customized root processes for groups of applications

A memory chip having a first set of pins configured to allow the memory chip to be coupled to a first microchip or device via first wiring. The memory chip also having a second set of pins configured to allow the memory chip to be coupled to a second microchip or device via second wiring that is separate from the first wiring. The memory chip also having a data mover configured to facilitate access to the second microchip or device, via the second set of pins, to read data from the second microchip or device and write data to the second microchip or device. Also, a system having the memory chip, the first microchip or device, and the second microchip or device.

Memory chip having an integrated data mover

A computer system includes physical memory devices of different types that store randomly-accessible data in memory of the computer system. In one approach, access to memory in an address space is maintained by an operating system of the computer system. A virtual page is associated with a first memory type. A page table entry is generated to map a virtual address of the virtual page to a physical address in a first memory device of the first memory type. The page table entry is used by a memory management unit to store the virtual page at the physical address.

Page table hooks to memory types

A memory chip having a predefined memory region configured to store program data transmitted from a microchip. The memory chip also having a programmable engine configured to facilitate access to a second memory chip to read data from the second memory chip and write data to the second memory chip according to stored program data in the predefined memory region. The predefined memory region can include a portion configured as a command queue for the programmable engine, and the programmable engine can be configured to facilitate access to the second memory chip according to the command queue.

Programmable engine for data movement

Systems, methods and apparatuses to intelligently migrate content involving borrowed memory are described. For example, after the prediction of a time period during which a network connection between computing devices having borrowed memory degrades, the computing devices can make a migration decision for content of a virtual memory address region, based at least in part on a predicted usage of content, a scheduled operation, a predicted operation, a battery level, etc. The migration decision can be made based on a memory usage history, a battery usage history, a location history, etc. using an artificial neural network; and the content migration can be performed by remapping virtual memory regions in the memory maps of the computing devices.

Intelligent content migration with borrowed memory

Systems, methods and apparatuses of distributed computing based on memory as a service are described. For example, a set of networked computing devices can each be configured to execute an application that accesses memory using a virtual memory address region. Each respective device can map the virtual memory address region to the local memory for a first period of time during which the application is being executed in the respective device, map the virtual memory address region to a local memory of a remote device in the group for a second period of time after starting the application in the respective device and before terminating the application in the respective device, and request the remote device to process data in the virtual memory address region during at least the second period of time.

Distributed computing based on memory as a service

A computer system includes physical memory devices of different types that store randomly-accessible data in a main memory of the computer system. In one approach, an operating system allocates memory from a namespace for use by an application. The namespace is a logical reference to physical memory devices in which physical addresses are defined. The namespace is bound to a memory type. In response to binding the namespace to the memory type, the operating system adjusts a page table to map a logical memory address in the namespace to a memory device of the memory type.

Memory system for binding data to a memory namespace

A computer system includes physical memory devices of different types that store randomly-accessible data in a main memory of the computer system. In one approach, data is stored in memory at one or more logical addresses allocated to an application by an operating system. The data is physically stored in a first memory device of a first memory type (e.g., NVRAM). The operating system determines an access pattern for the stored data. In response to determining the access pattern, the data is moved from the first memory device to a second memory device of a different memory type (e.g., DRAM).

Mapping non-typed memory access to typed memory access

A wear-leveling process for a memory subsystem selects a source chunk to be removed from a usable address space of the memory subsystem to distribute wear across all available chunks in the memory subsystem. The memory subsystem has a plurality of non-volatile memory components. The plurality of non-volatile memory components includes a plurality of chunks including at least one chunk in an unusable address space of the memory subsystem. The wear-leveling process copies valid data of the source chunk to a destination chunk in the unusable address space of the memory subsystem and assigns the destination chunk to a location in the usable address space of the memory subsystem occupied by the source chunk.

Wear-leveling scheme for memory subsystems

A memory sub-system configured to be responsive to a time to live requirement for load commands from a processor. For example, a load command issued by the processor (e.g., SoC) can include, or be associated with, an optional time to live parameter. The parameter requires that the data at the memory address be available within the time specified by the time to live parameter. When the requested data is currently in the lower speed memory (e.g., NAND flash) and not available in the higher speed memory (e.g., DRAM, NVRAM), the memory sub-system can determine that the data cannot be made available with the specified time and optionally skip the operations and return an error response immediately.

Time to live for load commands

Exemplary methods, apparatuses, and systems include determining that data in a group of memory cells of a first memory device is to be moved to a spare group of memory cells. The group of memory cells spans a first dimension and a second dimension that is orthogonal to the first dimension and the spare group of memory cells also spans the first dimension and the second dimension. The data is read from the group of memory cells along the first dimension of the group of memory cells. The data is written to the spare group of memory cells along the second dimension of the spare group of memory cells.

Managing data disturbance in a memory with asymmetric disturbance effects

An example method includes determining a time between writes in place to a particular memory cell, incrementing a disturb count corresponding to a neighboring memory cell by a particular count increment that is based on the time between the writes to the particular memory cell, and determining whether to check a write disturb status of the neighboring memory cell based on the incremented disturb count.

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Sacramento, CA, United States of America

Samuel E Bradshaw