Abstract: Associative processing memory (APM) may be used to align reads to a reference sequence. The APM may store shifted permutations and/or other permutations of the reference sequence. A read may be compared to some or all of the permutations of the reference sequence and the APM may provide an output for each comparison. In some examples, the APM may compare the read to many permutations of the reference sequence to the read in parallel. Inferences may be made based on the comparisons between the read and the portions and/or permutations of a reference sequence. Based on the inferences, a candidate alignment location in the reference sequence for a read to be determined.

Abstract: Associative processing memory (APM) may be used to align reads to a reference sequence. The APM may store shifted permutations and/or other permutations of the reference sequence. A read may be compared to some or all of the permutations of the reference sequence and the APM may provide an output for each comparison. In some examples, the APM may compare the read to many permutations of the reference sequence to the read in parallel. Inferences may be made based on the comparisons between the read and the portions and/or permutations of a reference sequence. Based on the inferences, a candidate alignment location in the reference sequence for a read to be determined.

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: An example memory sub-system includes: a plurality of bank groups, wherein each bank group comprises a plurality of memory banks; a plurality of row buffers, wherein two or more row buffers of the plurality of row buffers are associated with each memory bank; a cache comprising a plurality of cache lines; a processing logic communicatively coupled to the plurality of bank groups and the plurality of row buffers, the processing logic to perform operations comprising: receiving an activate command specifying a row of a memory bank of the plurality of memory banks; fetching data from the specified row to a row buffer of the plurality of row buffers; and copying the data to a cache line of the plurality of cache lines.

Abstract: Methods, apparatuses, and systems for in- or near-memory processing are described. Strings of bits (e.g., vectors) may be fetched and processed in logic of a memory device without involving a separate processing unit. Operations (e.g., arithmetic operations) may be performed on numbers stored in a bit-parallel way during a single sequence of clock cycles. Arithmetic may thus be performed in a single pass as numbers are bits of two or more strings of bits are fetched and without intermediate storage of the numbers. Vectors may be fetched (e.g., identified, transmitted, received) from one or more bit lines. Registers of a memory array may be used to write (e.g., store or temporarily store) results or ancillary bits (e.g., carry bits or carry flags) that facilitate arithmetic operations. Circuitry near, adjacent, or under the memory array may employ XOR or AND (or other) logic to fetch, organize, or operate on the data.

Abstract: A memory device may be used to implement a Bloom filter. In some examples, the memory device may include a memory array to perform a multiply-accumulate operation to implement the Bloom filter. The memory device may store multiple portions of a reference genetic sequence in the memory array and compare the portions of the reference genetic sequence to a read sequence in parallel by performing the multiply-accumulate operation. The results of the multiply-accumulate operation between the read sequence and the portions of the reference genetic sequence may be used to determine where the read sequence aligns to the reference sequence.

Abstract: An interface shim layer for a tightly-coupled random access memory device is disclosed. The interface shim layer redirects and coalesces integrated channels and connections between a stacked plurality of memory die and an application specific integrated circuit and directly connects to the memory die and to the application specific integrated circuit. A passive version of the interface shim layer incorporates a plurality of routing layers to facilitate routing of signals to and from the stacked plurality of memory die and the application specific integrated circuit. An active version of the interface shim layer incorporates separate physical interfaces for both the stacked plurality of memory die and the application specific integrated circuit to facilitate routing. The active version of the interface shim layer may further incorporate memory controller functions, built-in self-test circuits, among other capabilities that are migratable into the active interface shim layer.

Abstract: A memory device may be used to implement a Bloom filter. In some examples, the memory device may include a memory array to perform a multiply-accumulate operation to implement the Bloom filter. The memory device may store multiple portions of a reference genetic sequence in the memory array and compare the portions of the reference genetic sequence to a read sequence in parallel by performing the multiply-accumulate operation. The results of the multiply-accumulate operation between the read sequence and the portions of the reference genetic sequence may be used to determine where the read sequence aligns to the reference sequence.

Abstract: Methods, apparatuses, and systems for in- or near-memory processing are described. Spiking events in a spiking neural network may be processed via a memory system. A memory system may store a group of destination neurons, and at each time interval in a series of time intervals of a spiking neural network (SNN), pass through a group of pre-synaptic spike events from respective source neurons, wherein the group of pre-synaptic spike events are subsequently stored in memory.

Abstract: Methods, systems, and devices for redundant computing across planes are described. A device may perform a computational operation on first data that is stored in a first plane that includes content-addressable memory cells. The first data may be representative of a set of contiguous bits of a vector. The device may perform, concurrent with performing the computational operation on the first data, the computational operation on second data that is stored in a second plane. The second data may be representative of the set of contiguous bits of the vector. The device may read from the first plane and write to the second plane, third data representative of a result of the computational operation on the first data.

Abstract: Systems, apparatuses, and methods related to bloom filter implementation into a controller are described. A memory device is coupled to a memory controller. The memory controller is configured to implement a counting bloom filter, increment the counting bloom filter in response to a row activate command of the memory device, determine whether a value of the counting bloom filter exceeds a threshold value, and perform an action in response to the value exceeding the threshold value.

Abstract: An apparatus (e.g., a content addressable memory system) can have a controller; a first content addressable memory coupled to the controller and a second content addressable memory coupled to the controller. The controller can be configured to cause the first content addressable memory to compare input data to first data stored in the first content addressable memory and cause the second content addressable memory to compare the input data to second data stored in the second content addressable memory such the input data is compared to the first and second data concurrently and replace a result of the comparison of the input data to the first data with a result of the comparison of the input data to the second data in response to determining that the first data is invalid and that the second data corresponds to the first data.

Abstract: Row hammer attacks takes advantage of unintended and undesirable side effects of memory devices in which memory cells interact electrically between themselves by leaking their charges and possibly changing the contents of nearby memory rows that were not addressed in an original memory access. Row hammer attacks are mitigated by using a victim cache. Data is written to cache lines of a cache. A least recently used cache line of the cache is written to the victim cache.

Abstract: Systems, methods, and apparatus for memory device security and row hammer mitigation are described. A control mechanism may be implemented in a front-end and/or a back-end of a memory sub-system to refresh rows of the memory. A row activation command having a row address at control circuitry of a memory sub-system and incrementing a first count of a row counter corresponding to the row address stored in a content addressable memory (CAM) of the memory sub-system may be received. Control circuitry may determine whether the first count is greater than a row hammer threshold (RHT) minus a second count of a CAM decrease counter (CDC); the second count may be incremented each time the CAM is full. A refresh command to the row address may be issued when a determination is made that the first count is greater than the RHT minus the second count.

Abstract: Systems, apparatuses, and methods of operating memory systems are described. Processing-in-memory capable memory devices are also described, and methods of performing fused-multiply-add operations within the same. Bit positions of bits stored at one or more portions of one or more memory arrays, may be accessed via data lines by activating the same or different access lines. A sensing circuit operatively coupled to a data line may be temporarily formed and measured to determine a state (e.g., a count of the number of bits that are a logic “1”) of accessed bit positions of a data line, and state information may be used to determine a computational result.

Abstract: Systems and methods for distributing cloud-based language processing services to partially execute in a local device to reduce latency perceived by the user. For example, a local device may receive a request via audio input, that requires a cloud-based service to process the request and generate a response. A partial response may be generated locally and played back while a more complete response is generated remotely.

Abstract: Methods, systems, and devices for error control for content-addressable memory (CAM) are described. A CAM may store bit vectors as a set of subvectors, which each subvector stored in an independent aspect of the CAM, such as in a separate column or array of memory cells within the CAM. The CAM may similarly segment a queried input bit vector and identify, for each resulting input subvector, whether a matching subvector is stored by the CAM. The CAM may identify a match for the input bit vector when the number of matching subvectors satisfies a threshold. The CAM may validate a match based on comparing a stored bit vector corresponding to the identified match to the input bit vector. The stored bit vector may undergo error correction and may be stored in the CAM or another memory array, such as a dynamic random access memory (DRAM) array.

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: Systems and methods for finite time counting period counting of infinite data streams is presented. In particular example systems and methods enable counting row accesses to a memory media device over predetermined time intervals in order to deterministically detect row hammer attacks on the memory media device. Example embodiments use two identical tables that are reset at times offset in relation to each other in a ping-pong manner in order to ensure that there exists no false negative detections. The counting techniques described in this disclosure can be used in various types of row hammer mitigation techniques and can be implemented in content addressable memory or another type of memory. The mitigation may be implemented on a per-bank basis, per-channel basis or per-memory media device basis. The memory media device may be a dynamic random access memory type device.

Abstract: Methods, systems, and devices for in-memory associative processing are described. An apparatus may receive a set of instructions that indicate a first vector and a second vector as operands for a computational operation. The apparatus may select, from a set of vector mapping schemes, a vector mapping scheme for performing the computational operation using associative processing. The apparatus may write the first vector and the second vector to a set of planes each comprising an array of content-addressable memory cells based on the selected vector mapping scheme.