公开(公告)号：US20190324857A1

公开(公告)日：2019-10-24

申请号：US15960302

申请日：2018-04-23

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Cong XU ,  Itir AKGUN ,  Paolo FARABOSCHI

IPC: G06F11/14 ,  H04L29/08

Abstract: In some examples, with respect to adaptive multi-level checkpointing, a transfer parameter associated with transfer of checkpoint data from a node-local storage to a parallel file system may be ascertained for the checkpoint data stored in the node-local storage. The transfer parameter may be compared to a specified transfer parameter threshold. A determination may be made, based on the comparison of the transfer parameter to the specified transfer parameter threshold, as to whether to transfer the checkpoint data from the node-local storage to the parallel file system.

公开(公告)号：US20180218257A1

公开(公告)日：2018-08-02

申请号：US15417760

申请日：2017-01-27

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Cong XU ,  Qiong CAI

IPC: G06N3/08 ,  G06F9/48

CPC classification number: G06N3/08 ,  G06F9/4806 ,  G06N3/0454 ,  G06N3/063

Abstract: Examples disclosed herein relate to using a memory side accelerator to calculate updated deep learning parameters. A globally addressable memory includes deep learning parameters. The deep learning parameters are partitioned, where each partition is associated with a memory side accelerator. A memory side accelerator is to receive calculated gradient updates associated with its partition and calculate an update to the deep learning parameters associated with the partition.