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[cleanup][2/x] split float8 mm by delayed vs dynamic #1461

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@vkuzo vkuzo commented Dec 27, 2024

Summary:

Before this PR, the float8 mm logic was split by axiswise vs tensorwise.
After this PR, the float8 mm logic is split by dynamic vs non-dynamic scaling.

Motivation: there is more and more evidence that dynamic scaling will
be common to the most important lowp recipes. This PR is a step on the way
to making the dynamic scaling logic be simpler and easier to understand
in torchao.float8.

There are a lot of other simplifications to do, but stopping here to
keep the PR small. This is a pure refactor without any logic changes.

Test Plan:

./test/float8/test_everything.sh

// torchtitan LLaMa 3 8B on 8 H100s

// baseline (bf16 + compile)
37.87GiB(39.86%)  tps: 5,787

// before this PR

// dynamic-tensorwise
memory: 37.98GiB(39.98%)  tps: 6,880
// dynamic-tensorwise with float8 all-gather
memory: 37.54GiB(39.51%)  tps: 7,126
// all-axiswise
memory: 57.03GiB(60.03%)  tps: 6,330
// lw_axiswise_with_gw_hp
memory: 57.03GiB(60.03%)  tps: 6,021

// after this PR
// dynamic-tensorwise
memory: 37.98GiB(39.98%)  tps: 6,891
// dynamic-tensorwise with float8 all-gather
memory: 37.54GiB(39.51%)  tps: 7,127
// all-axiswise
memory: 57.03GiB(60.03%)  tps: 6,345
// lw_axiswise_with_gw_hp
memory: 57.03GiB(60.03%)  tps: 6,042

Reviewers:

Subscribers:

Tasks:

Tags:

[ghstack-poisoned]
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pytorch-bot bot commented Dec 27, 2024

🔗 Helpful Links

🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/1461

Note: Links to docs will display an error until the docs builds have been completed.

❌ 1 New Failure

As of commit c9f3a3f with merge base 457c5b1 (image):

NEW FAILURE - The following job has failed:

This comment was automatically generated by Dr. CI and updates every 15 minutes.

@facebook-github-bot facebook-github-bot added the CLA Signed This label is managed by the Facebook bot. Authors need to sign the CLA before a PR can be reviewed. label Dec 27, 2024
vkuzo added a commit that referenced this pull request Dec 27, 2024
Summary:

Before this PR, the float8 mm logic was split by axiswise vs tensorwise.
After this PR, the float8 mm logic is split by dynamic vs non-dynamic scaling.

Motivation: there is more and more evidence that dynamic scaling will
be common to the most important lowp recipes. This PR is a step on the way
to making the dynamic scaling logic be simpler and easier to understand
in `torchao.float8`.

There are a lot of other simplifications to do, but stopping here to
keep the PR small.  This is a pure refactor without any logic changes.

Test Plan:

```
./test/float8/test_everything.sh
```

Reviewers:

Subscribers:

Tasks:

Tags:

ghstack-source-id: 8a9792272e3aeea12d705eb5a466b9830dac6420
ghstack-comment-id: 2564049757
Pull Request resolved: #1461
@vkuzo vkuzo added the topic: not user facing Use this tag if you don't want this PR to show up in release notes label Dec 27, 2024
[ghstack-poisoned]
vkuzo added a commit that referenced this pull request Dec 27, 2024
Summary:

Before this PR, the float8 mm logic was split by axiswise vs tensorwise.
After this PR, the float8 mm logic is split by dynamic vs non-dynamic scaling.

Motivation: there is more and more evidence that dynamic scaling will
be common to the most important lowp recipes. This PR is a step on the way
to making the dynamic scaling logic be simpler and easier to understand
in `torchao.float8`.

There are a lot of other simplifications to do, but stopping here to
keep the PR small.  This is a pure refactor without any logic changes.

Test Plan:

```
./test/float8/test_everything.sh
```

Reviewers:

Subscribers:

Tasks:

Tags:

ghstack-source-id: 90b042fc76549c88a46abf06945ad166ea403e5c
ghstack-comment-id: 2564049757
Pull Request resolved: #1461
[ghstack-poisoned]
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2 participants