Advanced Micro Devices Corporation

Netapp, Inc.

Nathaniel Morris

Sergey Blagodurov

Atul Kumar Sujayendra Sandur

Xiaoyun Zhu

Pradeep Padala

Marko Scrbak

Kishore Punniyamurthy

Brandon K Potter

Kevin Yu-Cheng Cheng

David Lee

Connection modification based on traffic pattern is described. In accordance with the described techniques, a traffic pattern of memory operations across a set of connections between at least one device and at least one memory is monitored. The traffic pattern is then compared to a threshold traffic pattern condition, such as an amount of data traffic in different directions across the connections. A traffic direction of at least one connection of the set of connections is modified based on the traffic pattern corresponding to the threshold traffic pattern condition.

Connection modification based on traffic pattern

Method and apparatus monitor eviction conflicts among cache directory entries in a cache directory and produce cache directory victim entry information for a memory manager. In some examples, the memory manager reduces future cache directory conflicts by changing a page level physical address assignment for a page of memory based on the produced cache directory victim entry information. In some examples, a scalable data fabric includes hardware control logic that performs the monitoring of the eviction conflicts among cache directory entries in the cache directory and produces the cache directory victim entry information.

Method and apparatus for managing a cache directory

The disclosed device includes a memory-semantic fabric comprising memory components accessible by multiple processors and a controller for the memory-semantic fabric. The controller receives, from multiple processes, memory requests for a memory-semantic fabric. The controller also identifies, within the processes, a source process for each of the memory requests and prioritizes forwarding the memory requests to the memory-semantic fabric based on the source processes. Various other methods, systems, and computer-readable media are also disclosed.

Prioritization of memory traffic for multi-process workloads

Identifying a likely cause of a problem in an application can include: injecting a series of a set of predetermined faults into the application; sampling a subset of a set of training features from the application during each predetermined fault injected into the application and labeling each subset with an identifier of the corresponding predetermined fault; and training a classifier to identify the likely cause by associating a set of real-time features sampled from the application that pertain to the problem to one or more of the predetermined faults in response to the training features.

Diagnosing application problems by learning from fault injections

Growing community of inventors

Columbus, OH, United States of America

Nathaniel Morris