[NVIDIA XLA]Replace broadcast of trivial matrix bias by optional custom-call for CUDA >= 12
@reedwm this seems to be of high priority given @wenscarl is reporting the perf hit is ~ 10% of the actual matmul call. Seems like all the unit tests will have to change to accommodate this change. Wenscarl has only implemented a single unit test to show the shape of things to come and is seeking feedback whether the new paradigm works. @philipphack will also give feedback. Version 11 doesn't support non-zero beta. I think that's why we added the version guard [here](https://github.com/tensorflow/tensorflow/blame/0e51c74cd0fa8bef5d9cdbea76f3387a1baae01b/tensorflow/compiler/xla/service/gpu/gemm_rewriter.cc#L728). Changes are made with CUDA_VERSION >= 12000 guards removed. Can you sync with the master branch to get changes from https://github.com/tensorflow/tensorflow/pull/60502? > Can you sync with the master branch to get changes from #60502?

Rebased to current master. As part of the OpenXLA PR rotation:
I'll re-trigger the presubmits as soon as I get permissions. Since the PR author is OOO, I was going to fix some issues when merging. But it's too hard to test on H100s when merging, so instead I'll commit directly to this PR's branch. So let's not merge this PR yet. @philipphack in the FP8 case, when there is no matrix bias, this PR currently sets C to nullptr. But in the FP16 case, when there is no matrix bias, instead C is set to D

I would prefer that the FP16 and FP8 cases be unified. Is there a fundamental reason why it's important for C to be nullptr in the FP8 case but not in the non-FP8 case? If there is no difference in cublas LT between FP8 and FP16 w.r.t. whether C should be nullptr or equal to D, I will set C to D in this PR. (Since @wenscarl is OOO I am addressing my own comments to this PR before merging it)
Replace broadcast of trivial matrix bias by a scalar under CUDA > 12. Nearly all F8 unittests will get impacted but only 1 unittest is included at the moment for the purpose of demonstration. 

Broadcasting trivial matrix bias takes up about 10% time of the actually matmul. 
![image](https://user-images.githubusercontent.com/25590028/234122329-3ae6040e-c940-4131-95ce-0644411a41cd.png)
