Patent classifications
G06F12/0893
Memory utilized as both system memory and near memory
An embodiment of a memory controller device includes technology to control access to a multi-level memory including at least a first level memory and a second level memory, provide direct access to the first level memory based on a system memory address, cache accesses to the second level memory in a second portion of the first level memory, and address a memory space with a total memory capacity which includes a first capacity of the first portion of the first level memory plus a second capacity of the second level memory. Other embodiments are disclosed and claimed.
Configurable NVM set to tradeoff between performance and user space
An embodiment of an electronic apparatus may include one or more substrates, and logic coupled to the one or more substrates, the logic to determine a set of requirements for a persistent storage media based on input from an agent, dedicate one or more banks of the persistent storage media to the agent based on the set of requirements, and configure at least one of the dedicated one or more banks of the persistent storage media at a program mode width which is narrower than a native maximum program mode width for the persistent storage media. Other embodiments are disclosed and claimed.
Configurable NVM set to tradeoff between performance and user space
An embodiment of an electronic apparatus may include one or more substrates, and logic coupled to the one or more substrates, the logic to determine a set of requirements for a persistent storage media based on input from an agent, dedicate one or more banks of the persistent storage media to the agent based on the set of requirements, and configure at least one of the dedicated one or more banks of the persistent storage media at a program mode width which is narrower than a native maximum program mode width for the persistent storage media. Other embodiments are disclosed and claimed.
MANAGING PERFORMANCE THROTTLING IN A DIGITAL CONTROLLER
Provided is a system and method for storing, via a processor, in a memory of an application specific integrated circuit (ASIC), one or more threshold values responsive to at least one of physical layer and processing layer operating conditions of the ASIC. Also included is monitoring at least one of a physical layer operating condition value and a processing layer performance condition value of the ASIC, the moderating forming a monitored value, comparing the monitored value with the stored threshold values, and throttling processing layer performance of the ASIC when the monitored value exceeds at least one of the stored threshold values.
MANAGING PERFORMANCE THROTTLING IN A DIGITAL CONTROLLER
Provided is a system and method for storing, via a processor, in a memory of an application specific integrated circuit (ASIC), one or more threshold values responsive to at least one of physical layer and processing layer operating conditions of the ASIC. Also included is monitoring at least one of a physical layer operating condition value and a processing layer performance condition value of the ASIC, the moderating forming a monitored value, comparing the monitored value with the stored threshold values, and throttling processing layer performance of the ASIC when the monitored value exceeds at least one of the stored threshold values.
Data-driven online score caching for machine learning
The disclosed embodiments provide a system for processing scoring requests. During operation, the system matches an identifier for an entity in a scoring request to a cache entry in a score cache. Next, the system retrieves, from the cache entry, a previous value of a score generated by a machine learning model from previous values of features for the entity and a first encoded representation of the previous values of a subset of the features with greater than a threshold effect on the score. The system then compares the first encoded representation with a second encoded representation of the most recent values of the subset of the features for the entity. When the comparison indicates that the most recent values match the previous values, the system outputs the previous value of the score for the entity in a response to the scoring request.
Data-driven online score caching for machine learning
The disclosed embodiments provide a system for processing scoring requests. During operation, the system matches an identifier for an entity in a scoring request to a cache entry in a score cache. Next, the system retrieves, from the cache entry, a previous value of a score generated by a machine learning model from previous values of features for the entity and a first encoded representation of the previous values of a subset of the features with greater than a threshold effect on the score. The system then compares the first encoded representation with a second encoded representation of the most recent values of the subset of the features for the entity. When the comparison indicates that the most recent values match the previous values, the system outputs the previous value of the score for the entity in a response to the scoring request.
Memory system
A memory system includes: a first memory module including first volatile memories; a second memory module including second volatile memories, non-volatile memories and a module controller; a memory controller controlling the first and second memory modules through second and third control buses, respectively; and a switch array electrically coupling the second and third control buses, wherein the module controller controls the switch array to electrically couple the second and third control buses in a backup operation for backing up data of the first volatile memories to the non-volatile memories, wherein the first and second memory modules include one or more first memory stacks and one or more second memory stacks, respectively, wherein the first volatile memories are stacked in the first memory stacks, and wherein the second volatile memories, the non-volatile memories and the module controller are stacked in the second memory stacks.
Memory system
A memory system includes: a first memory module including first volatile memories; a second memory module including second volatile memories, non-volatile memories and a module controller; a memory controller controlling the first and second memory modules through second and third control buses, respectively; and a switch array electrically coupling the second and third control buses, wherein the module controller controls the switch array to electrically couple the second and third control buses in a backup operation for backing up data of the first volatile memories to the non-volatile memories, wherein the first and second memory modules include one or more first memory stacks and one or more second memory stacks, respectively, wherein the first volatile memories are stacked in the first memory stacks, and wherein the second volatile memories, the non-volatile memories and the module controller are stacked in the second memory stacks.
Dynamic cache size management of multi-tenant caching systems
Cache memory requirements between normal and peak operation may vary by two orders of magnitude or more. A cache memory management system for multi-tenant computing environments monitors memory requests and uses a pattern matching classifier to generate patterns which are then delivered to a neural network. The neural network is trained to predict near-future cache memory performance based on the current memory access patterns. An optimizer allocates cache memory among the tenants to ensure that each tenant has sufficient memory to meet its required service levels while avoiding the need to provision the computing environment with worst-case scenario levels of cache memory. System resources are preserved while maintaining required performance levels.