pytorch / pytorch/benchmark

TFLOPS calculation for TF32

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Dominant language
Python
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Description

The current TFLOPS is only for FP32. Need to add support for other floating point formats such as TF32 and FP16.

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First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by locating the existing FP32 TFLOPS calculation in the benchmark code and trace how its floating-point format is represented. Determine how TF32 and FP16 should be reported, then verify that the resulting calculations distinguish the supported formats; the issue names no specific files or tests.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
performance
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
38/100

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