FAQ

1. What is UCC?
2. What are important components of UCC reference implementation?
3. How can I contribute?
4. How to compile and run UCC with Open MPI?
5. How to compile and run UCC with PyTorch?
6. What is TL scoring and how to select a certain TL?

env var pattern: UCC_<TL/CL>__SCORE=token1#token2#...#tokenn, '#' separated list of tokens where token=coll_type:msg_range:mem_type:team_size:score:alg - a ':' separated list of qualifiers. Each qualifier is optional. The only requirement is that either "score" or "alg" is provided. Qualifiers:

• coll_type = coll_type_1,coll_type_2,...,coll_type_n - a ',' separated list of coll_types
• msg_range = m_start_1-m_end_1,m_start_2-m_end_2,..,m_start_n-m_end_n - a ',' separated list of msg ranges, where each range is represented by "start" and "end" values separated by "-". Values can be numbers with "Size" characters, e.g. 128, 256b, 4K, 1M. Special value "inf" means MAX msg size.
• mem_type = m1,m2,..,mn - ',' separated list of memory types
• team_size = [t_start_1-t_end_1,t_start_2-t_end_2,...,t_start_n-t_end_n] - a ',' separated list of team size ranges enclosed with [].
• score = , a int value from 0 to "inf"
• alg = @<value|str> - character @ followed by either int number of string representing the collective algorithm. Examples:
• UCC_TL_NCCL_SCORE=0 - disable all the NCCL collectives (score 0 is applied to ALL collectives since qualifier is not specified, similarly to ALL memory types, to default [0-inf] msg range and [0-inf] team size).
• UCC_TL_NCCL_SCORE=allreduce:cuda:inf,alltoall:0 - force NCCL allreduce for "cuda" buffers and disable alltoall
• UCC_TL_UCP_SCORE=bcast:0-4K:cuda:0,bcast:65k-1M:[25-100]:cuda:inf - disable UCP bcast on cuda buffers for msg sizes 0-4K and force UCP bcast on cuda buffers for msg sizes 65K-1M only for teams with 25-100 ranks
• UCC_TL_UCP_SCORE=allreduce:0-4K:@0,allreduce:4K-inf:@sra_knomial - for TL_UCP set allreduce algorithm to 0 for msg range 0-4K and to 1 (sra_knomial) for 4k-inf.

7. What are dependencies for UCC?