From 398c0daf24b662df5edf762cc78b166711eb76ac Mon Sep 17 00:00:00 2001 From: Matt Spencer Date: Fri, 4 Nov 2022 11:31:13 +0000 Subject: [PATCH] Update gitlab references From gitlab.com/Linaro => gitlab.com/soafee --- CONTRIBUTING.md | 2 +- content/_index.md | 2 +- content/blog/2022/all_hands_recording.md | 4 ++-- content/blog/2022/getting_started_cloud_native.md | 2 +- 4 files changed, 5 insertions(+), 5 deletions(-) diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 609497f..1230911 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -32,7 +32,7 @@ repository. ## Development repository -The SOAFEE development repository is hosted at https://gitlab.com/Linaro/ewaol. +The SOAFEE development repository is hosted at https://gitlab.com/soafee/ewaol. ## Communications diff --git a/content/_index.md b/content/_index.md index 5424107..ceba646 100644 --- a/content/_index.md +++ b/content/_index.md @@ -112,7 +112,7 @@ For more information about the SOAFEE project, explore the links below: * [Blog: The software-defined vehicle needs hardware that goes the distance](https://www.arm.com/blogs/blueprint/software-defined-vehicle) * [Blog: The cloud-native approach to the software defined car](https://community.arm.com/2021-ia-reorg-archive/developer/ip-products/system/b/embedded-blog/posts/cloud-native-approach-to-the-software-defined-car?_ga=2.84349662.63983164.1633923986-188627514.1623282169&_gac=1.188151258.1631741153.Cj0KCQjws4aKBhDPARIsAIWH0JWzFX7JhWfY12ecutW_Gaiy3HwXQ1QWT1HbMuvrAnTdtsTSdk57dzAaAq7DEALw_wcB) * [SOAFEE](https://gitlab.com/soafee) -* Reference implementation [EWAOL](https://gitlab.com/Linaro/ewaol) +* Reference implementation [EWAOL](https://gitlab.com/soafee/ewaol) ## Contact diff --git a/content/blog/2022/all_hands_recording.md b/content/blog/2022/all_hands_recording.md index 579d551..500c9e7 100644 --- a/content/blog/2022/all_hands_recording.md +++ b/content/blog/2022/all_hands_recording.md @@ -55,7 +55,7 @@ There are already moves in the industry to standardize on [VirtIO](https://www.o {{< question "Will the SOAFEE effort create a reference architecture? How would that relate to AUTOSAR?" >}} -The reference implementation of the SOAFEE architecture is called EWAOL (Embedded Workload Application Orchestration Layer), and is available from the [meta-ewaol](https://gitlab.com/Linaro/ewaol/meta-ewaol) git repository. This reference implementation is built using [Yocto](https://www.yoctoproject.org/), with additional unofficial layers to support more target devices available from [meta-ewaol-machine](https://gitlab.com/Linaro/ewaol/meta-ewaol-machine), although these are community run with no official backing from the SOAFEE members. +The reference implementation of the SOAFEE architecture is called EWAOL (Embedded Workload Application Orchestration Layer), and is available from the [meta-ewaol](https://gitlab.com/soafee/ewaol/meta-ewaol) git repository. This reference implementation is built using [Yocto](https://www.yoctoproject.org/), with additional unofficial layers to support more target devices available from [meta-ewaol-machine](https://gitlab.com/soafee/ewaol/meta-ewaol-machine), although these are community run with no official backing from the SOAFEE members. The vision for SOAFEE is that it is complementary with upstream rich stacks like [AUTOSAR](https://www.autosar.org/), [AGL](https://www.automotivelinux.org/), [Autoware](https://www.autoware.org/), [Android Automotive](https://source.android.com/devices/automotive/start/what_automotive) and others. SOAFEE is not looking to replace any of these stacks, but make it easier for these complex workloads to be deployed to current and next generation hardware platforms. @@ -69,7 +69,7 @@ The initial scope for SOAFEE is to target rich application processors, but we wo {{< question "Who would fund developing an entire software stack ....??" >}} -There is a reference implementation of the SOAFEE concepts called [meta-ewaol](https://gitlab.com/Linaro/ewaol/meta-ewaol). This project was initially launched by Arm, and they are actively working on a collaboration agreement to enable the SOAFEE ecosystem to contribute to the implementation. But, this reference implementation is designed only to be functional, not necessarily a certified go-to-market solution. For this we will be working with our commercial software partners to create a safety certified and commercially supported equivalent of the EWAOL reference implementation. This is made possible because the base SOAFEE architecture is expressed as a set of upstream open standards that any commercial software entity are free to implement against. +There is a reference implementation of the SOAFEE concepts called [meta-ewaol](https://gitlab.com/soafee/ewaol/meta-ewaol). This project was initially launched by Arm, and they are actively working on a collaboration agreement to enable the SOAFEE ecosystem to contribute to the implementation. But, this reference implementation is designed only to be functional, not necessarily a certified go-to-market solution. For this we will be working with our commercial software partners to create a safety certified and commercially supported equivalent of the EWAOL reference implementation. This is made possible because the base SOAFEE architecture is expressed as a set of upstream open standards that any commercial software entity are free to implement against. {{< /question >}} diff --git a/content/blog/2022/getting_started_cloud_native.md b/content/blog/2022/getting_started_cloud_native.md index 6045363..6683ead 100644 --- a/content/blog/2022/getting_started_cloud_native.md +++ b/content/blog/2022/getting_started_cloud_native.md @@ -22,6 +22,6 @@ This is a major element in achieving the objective of [_automotive_ cloud-native You will learn how to utilize AWS to create a CI/CD pipeline that builds, containerizes, evaluates, and enables deployment - at scale in the cloud and on embedded devices - of a perception network, [YOLO](https://pjreddie.com/darknet/yolo/). This network is used as a stand-in for any automotive application workload to demonstrate the design paradigm. The specific version of YOLO used in this workshop is the [one implemented in the Autoware stack](https://github.com/autowarefoundation/modelzoo/tree/master/perception/camera_obstacle_detection/yolo_v2_tiny/tensorflow_fp32_coco) (YOLOv2-Tiny), running on Ubuntu Linux 20.04. -The full System Under Test (SUT) stack will include the Operating System (a Yocto-Linux distribution) and Arm's [Edge Workload Abstraction and Orchestration Layer (EWAOL)](https://gitlab.com/Linaro/ewaol). +The full System Under Test (SUT) stack will include the Operating System (a Yocto-Linux distribution) and Arm's [Edge Workload Abstraction and Orchestration Layer (EWAOL)](https://gitlab.com/soafee/ewaol). {{< button url="https://catalog.us-east-1.prod.workshops.aws/workshops/12f31c93-5926-4477-996c-d47f4524905d/en-US/" text="Continue to the Workshop">}} -- GitLab