embedding forward optimization for MI350

[JaxChen29]

optimization on embedding forward for MI350:

1. apply vec4 on embedding vbe forward kernel instead of vec2
2. As there are 64 threads in rocm, optimize subwarp in embedding forward v2 kernel when embedding dim is from 32 to 64.

[netlify]

✅ Deploy Preview for pytorch-fbgemm-docs ready!

Name	Link
🔨 Latest commit	bce492c
🔍 Latest deploy log	https://app.netlify.com/projects/pytorch-fbgemm-docs/deploys/69008f13b46e4d0008b23f2a
😎 Deploy Preview	https://deploy-preview-5064--pytorch-fbgemm-docs.netlify.app
📱 Preview on mobile	Toggle QR Code... Use your smartphone camera to open QR code link.

---

To edit notification comments on pull requests, go to your Netlify project configuration.

[meta-cla]

Hi @JaxChen29!

Thank you for your pull request.

We require contributors to sign our Contributor License Agreement, and yours needs attention.

You currently have a record in our system, but the CLA is no longer valid, and will need to be resubmitted.

Process

In order for us to review and merge your suggested changes, please sign at https://code.facebook.com/cla. If you are contributing on behalf of someone else (eg your employer), the individual CLA may not be sufficient and your employer may need to sign the corporate CLA.

Once the CLA is signed, our tooling will perform checks and validations. Afterwards, the pull request will be tagged with CLA signed. The tagging process may take up to 1 hour after signing. Please give it that time before contacting us about it.

If you have received this in error or have any questions, please contact us at [email protected]. Thanks!

[meta-cla]

Thank you for signing our Contributor License Agreement. We can now accept your code for this (and any) Meta Open Source project. Thanks!

[meta-codesync]

@echen4096 has imported this pull request. If you are a Meta employee, you can view this in D85701691.