Advanced Micro Devices Corporation

Atul Kumar Sujayendra Sandur

Sergey Blagodurov

Nathaniel Morris

Pratik Mishra

Kevin Yu-Cheng Cheng

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

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

A cloud computing system includes cloud orchestrator circuitry and fabric manager circuitry. The cloud orchestrator circuitry receives an input application and determines a task graph, a data graph, and a function popularity heap parameter for the input application. The task graph comprises an indication of function interdependency of functions of the input application, the data graph comprises an indication of data interdependency of the functions, and the function popularity heap parameter corresponds to a re-usability index for the functions. The fabric manager circuitry allocate a first programmable integrated circuit (IC) device to perform a first function of the input application based on the task graph, the data graph, and the function popularity heap parameter.

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Santa Clara, CA, United States of America

Atul Kumar Sujayendra Sandur