Abstract: 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.

Abstract: A system having multiple devices that can host different versions of an artificial neural network (ANN). In the system, changes to local versions of the ANN can be combined with a master version of the ANN. In the system, a first device can include memory that can store the master version, a second device can include memory that can store a local version of the ANN, and there can be many devices that store local versions of the ANN. The second device (or any other device of the system hosting a local version) can include a processor that can train the local version, and a transceiver that can transmit changes to the local version generated from the training. The first device can include a transceiver that can receive the changes to a local version, and a processing device that can combine the received changes with the master version.

Abstract: Various embodiments enable versioning of data stored on a memory device, where the versioning allows the memory device to maintain different versions of data within a set of physical memory locations (e.g., a row) of the memory device. In particular, some embodiments provide for a memory device or a memory sub-system that uses versioning of stored data to facilitate a rollback operation/behavior, a checkpoint operation/behavior, or both. Additionally, some embodiments provide for a transactional memory device or a transactional memory sub-system that uses versioning of stored data to enable rollback of a memory transaction, commitment of a memory transaction, or handling of a read or write command associated with respect to a memory transaction.

Abstract: Systems, methods and apparatuses to accelerate accessing of borrowed memory over network connection are described. For example, a memory management unit (MMU) of a computing device can be configured to be connected both to the random access memory over a memory bus and to a computer network via a communication device. The computing device can borrow an amount of memory from a remote device over a network connection using the communication device; and applications running in the computing device can use virtual memory addresses mapped to the borrowed memory. When a virtual address mapped to the borrowed memory is used, the MMU translates the virtual address into a physical address and instruct the communication device to access the borrowed memory.

Abstract: A system having multiple devices that can host different versions of an artificial neural network (ANN). In the system, inputs for the ANN can be obfuscated for centralized training of a master version of the ANN at a first computing device. A second computing device in the system includes memory that stores a local version of the ANN and user data for inputting into the local version. The second computing device includes a processor that extracts features from the user data and obfuscates the extracted features to generate obfuscated user data. The second device includes a transceiver that transmits the obfuscated user data. The first computing device includes a memory that stores the master version of the ANN, a transceiver that receives obfuscated user data transmitted from the second computing device, and a processor that trains the master version based on the received obfuscated user data using machine learning.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Systems, methods, and apparatus related to data recovery in memory devices. In one approach, a memory device encodes stored data. The memory device reads a codeword from a storage media and determines that a number errors in the codeword exceeds an error correction capability of the memory device. The errors are due, for example, to one or more stuck bits. In response to this determination, one or more data patterns are written to the storage media at the same address from which the codeword is read. The data patterns are read to identify bit locations of the stuck bits. The identified locations are used to correct bit errors of the read codeword that correspond to the identified locations. The corrected code word is sent to a host device (e.g., which requested data from the memory device using a read command).

Abstract: 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.

Abstract: A system having multiple devices that can host different versions of an artificial neural network (ANN) as well as different versions of a feature dictionary. In the system, encoded inputs for the ANN can be decoded by the feature dictionary, which allows for encoded input to be sent to a master version of the ANN over a network instead of an original version of the input which usually includes more data than the encoded input. Thus, by using the feature dictionary for training of a master ANN there can be reduction of data transmission.

Abstract: 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.

Abstract: Systems, methods and apparatuses to throttle network communications for memory as a service are described. For example, a computing device can borrow an amount of random access memory of the lender device over a communication connection between the lender device and the computing device. The computing device can allocate virtual memory to applications running in the computing device, and configure at least a portion of the virtual memory to be hosted on the amount of memory loaned by the lender device to the computing device. The computing device can throttle data communications used by memory regions in accessing the amount of memory over the communication connection according to the criticality levels of the contents stored in the memory regions.

Abstract: A system having multiple devices that can host different versions of an artificial neural network (ANN) as well as different versions of a feature dictionary. In the system, encoded inputs for the ANN can be decoded by the feature dictionary, which allows for encoded input to be sent to a master version of the ANN over a network instead of an original version of the input which usually includes more data than the encoded input. Thus, by using the feature dictionary for training of a master ANN there can be reduction of data transmission.

Abstract: Systems, methods and apparatuses to throttle network communications for memory as a service are described. For example, a computing device can borrow an amount of random access memory of the lender device over a communication connection between the lender device and the computing device. The computing device can allocate virtual memory to applications running in the computing device, and configure at least a portion of the virtual memory to be hosted on the amount of memory loaned by the lender device to the computing device. The computing device can throttle data communications used by memory regions in accessing the amount of memory over the communication connection according to the criticality levels of the contents stored in the memory regions.

Abstract: 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.

Abstract: Various embodiments enable versioning of data stored on a memory device, where the versioning allows the memory device to maintain different versions of data within a set of physical memory locations (e.g., a row) of the memory device. In particular, some embodiments provide for a memory device or a memory sub-system that uses versioning of stored data to facilitate a rollback operation/behavior, a checkpoint operation/behavior, or both. Additionally, some embodiments provide for a transactional memory device or a transactional memory sub-system that uses versioning of stored data to enable rollback of a memory transaction, commitment of a memory transaction, or handling of a read or write command associated with respect to a memory transaction.

Abstract: 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.

Abstract: Systems, methods and apparatuses of fine grain data migration in using Memory as a Service (MaaS) are described. For example, a memory status map can be used to identify the cache availability of sub-regions (e.g., cache lines) of a borrowed memory region (e.g., a borrowed remote memory page). Before accessing a virtual memory address in a sub-region, the memory status map is checked. If the sub-region has cache availability in the local memory, the memory management unit uses a physical memory address converted from the virtual memory address to make memory access. Otherwise, the sub-region is cached from the borrowed memory region to the local memory, before the physical memory address is used.