Use global user buffer when the bucket size does not fit FixedPoolAllocator

[shengf-nv]

What does this PR do ?

FixedPoolAllocator maintains a double buffer so that one buffer holds the data for the current layer and another buffer is pre-fetching the data for the next layer, it can overlap computing and communication. The size of the double buffer in LLM is usually decided by the size of the transformer layers since their size are all the same. However, the embedding layer and output layer usually have different size. FixedPoolAllocator will fall back to dynamic memory allocation if the size does not fit. The dynamic allocated tensor can not be used as NCCL user buffer. In our SHARP performance test with Llama3 70B model, the large NCCL collectives that do not use user buffer got split into many small collectives before sending down to SHARP. We observed 10x slow performance because of the user buffer issue.

To fix this issue, this PR is to use the buffer in global memory pool with a unique buffer name as the following:

{FixedPoolAllocator name}not_fit_in_fixed_pool{bucket_id}{size}{dtype}_{device}"

This fix will keep unique buffers for the buckets, which do not fit the size of FixedPoolAllocator, in the global memory pool. In LLM, they are the embedding layer and output layer. It will increase the peak memory size. In our Llama3 70B test, it is around 1.5%.

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