Alibaba (china) Co., Ltd.

Yuhao Wang

Hongzhong Zheng

Dimin Niu

Shuangchen Li

Zhe Zhang

Yijin Guan

Shengcheng Wang

This application describes systems and methods for facilitating memory access for graph neural network (GNN) processing. An example method includes fetching, by an access engine circuitry implemented on a circuitry board, a portion of structure data of a graph from a pinned memory in a host memory of a host via a first peripheral component interconnect express (PCIe) connection; performing node sampling using the fetched portion of the structure data of the graph to select one or more sampled nodes; fetching, by the access engine circuitry, a portion of attribute data of the graph from the pinned memory via the first PCIe connection; sending the fetched portion of the attribute data of the graph to one or more processors; and performing, by the one or more processors, GNN processing for the graph using the fetched portion of the attribute data of the graph.

Graph acceleration solution with cloud FPGA

The presented systems enable efficient and effective network communications. The presented systems enable efficient and effective network communications. In one embodiment a memory device includes a memory module, including a plurality of memory chips configured to store information; and an inter-chip network (ICN)/shared smart memory extension (SMX) memory interface controller (ICN/SMX memory interface controller) configured to interface between the memory module and an inter-chip network (ICN), wherein the ICN is configured to communicatively couple the memory device to a parallel processing unit (PPU). In one exemplary implementation, the ICN/SMX memory controller includes a plurality of package buffers, an ICN physical layer interface, a PRC/MAC interface, and a switch. The memory device and be a memory card including memory module (e.g., DDR DIMM, etc.).

Flexible memory extension systems and methods

Growing community of inventors

Sunnyvale, CA, United States of America

Yuhao Wang