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authorLiam Barry <liam.barry@arm.com>2022-03-03 10:50:40 +0000
committerLiam Barry <liam.barry@arm.com>2022-03-09 14:29:48 +0000
commite7f512592818574d98c4b3ba09b4d3315fe025bd (patch)
tree360ccc81331583c6f7a5c06cb319c02fa6e732e4 /docs/sections/arm_virtual_hardware.md
parente77e001d2e6123e62f8e65c0e45d8d0c2dd7c3f5 (diff)
downloadml-embedded-evaluation-kit-e7f512592818574d98c4b3ba09b4d3315fe025bd.tar.gz
MLECO-3010 Minor clarifications in quick start guide
Tried to clarify location of axf file and need to change directory at a specific step Added note on changing permissions to AVH guide and added link to AVH guide in quickstart.md as well as recommending a VNC viewer if using AVH Change-Id: I653f0ac3ae52a6fc1c44e28024b9513af89c6db6 Signed-off-by: Liam Barry <liam.barry@arm.com>
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@@ -18,12 +18,20 @@ To take advantage of Arm Virtual Hardware, you would need to have an AWS account
2. Go to the AWS Marketplace and search for [Arm Virtual Hardware](https://aws.amazon.com/marketplace/pp/prodview-urbpq7yo5va7g).
3. Subscribe to the Arm Virtual Hardware Amazon Machine Image.
4. Launch the AWS instance.
- 5. If you want to access the Arm Virtual Hardware AWS instance via ssh, at the moment of creating the instance you would need to generate a *.pem* key.
- You could then access the AWS instance over ssh: `$ ssh -i <mykey.pem> ubuntu@<ec2-ip-address>`.
+
+ To access the Arm Virtual Hardware AWS instance via ssh, accept the prompt to generate a *.pem* key while creating the instance or add it later.
+ You can then access the AWS instance over ssh: `$ ssh -i <mykey.pem> ubuntu@<ec2-ip-address>`.
+ It may be necessary to change the permissions for mykey.pem with `$ chmod 400 mykey.pem`.
+
+
+### Useful Links
Note that you can register to receive free AWS credits to use Arm Virtual Hardware from [here](https://www.arm.com/company/contact-us/virtual-hardware).
You can find more information about Arm Virtual Hardware [here](https://arm-software.github.io/VHT/main/overview/html/index.html).
Once you have access to the AWS instance, we recommend starting from the [quick start guide](../quick_start.md#Quick-start-example-ML-application) in order to get familiar
with the ml-embedded-evaluation-kit. Note that on the AWS instance, the FVP is available under `/opt/FVP_Corstone_SSE-300`.
+
+In order to view the FVP window when launching on the AWS instance a VNC is required.
+See relevant section [here](https://aws.amazon.com/premiumsupport/knowledge-center/ec2-linux-2-install-gui/). \ No newline at end of file