refactor: separate device and communication backend layout

[Ziminli]

Summary

Refactor the InfiniCCL internal source layout to separate device/platform code from communication backend code. Device-specific implementations now live under src/devices, MPI backend code lives under src/backends/mpi, and NCCL is moved into the new CCL backend hierarchy under src/backends/ccl.

This change is needed so CCL backends are no longer owned by a single platform directory. The PR introduces a common CCL layer plus an NCCL provider layout for NVIDIA, leaving future platforms/backends to add their own provider aliases or overrides under the backend hierarchy.

Changes

• Source Layout

  • Move platform-specific code from src/{cpu,cuda,nvidia,iluvatar,metax,moore,cambricon} into src/devices/*.
  • Move OpenMPI code from src/ompi into src/backends/mpi/ompi.
  • Update include paths and header guards for the moved device and OpenMPI backend headers.

• CCL Backend Abstraction

  • Add src/backends/ccl/common/ for common CCL APIs and communicator instances.
  • Add reusable CCL operation implementations under src/backends/ccl/common/impl.
  • Move NCCL-specific operation registration into src/backends/ccl/nccl/impl so common CCL code stays backend-agnostic.

• NCCL provider structure

  • Add src/backends/ccl/nccl/api.h as the shared NCCL API wrapper.
  • Add src/backends/ccl/nccl/nvidia/api.h as the NVIDIA specialization that binds BackendType::kNccl to Device::Type::kNvidia.
  • Move NCCL checks and type mapping into src/backends/ccl/nccl.

• Build and generation

  • Update src/CMakeLists.txt source discovery for the new src/devices and src/backends layout.
  • Update scripts/gen_bridge.py so generated manifests include moved device headers, MPI backend headers, NCCL provider headers, NCCL type maps, and NCCL operation registration headers from the new locations.
  • Keep MPICH mapped to the moved OpenMPI implementation path, matching the existing shared MPI implementation model.

Platform and Backend Affected

Platform

• CPU
• NVIDIA GPU
• Iluvatar GPU
• MetaX GPU
• Moore Threads GPU
• Cambricon MLU

Backend

• OpenMPI
• MPICH
• NCCL

Performance Impact

• No performance impact
• Performance improved
• Performance regression possible

N/A. This is a source-layout and backend-abstraction refactor.

Known Issues & Future Work

• Future CCL providers can add provider-specific alias or override headers under src/backends/ccl/<backend>/<provider>/api.h.
• Future MCCL and CNCL backend support can follow the same src/backends/ccl/<backend> structure introduced here.

Test Results

Test Involved Platform

• CPU
• NVIDIA GPU
• Iluvatar GPU
• MetaX GPU
• Moore Threads GPU
• Cambricon MLU

Test Involved Backend

• OpenMPI
• MPICH
• NCCL

NV+MetaX+Iluvatar+Moore with OpenMPI:
mpi_all_gather.log
mpi_all_to_all.log
mpi_all_reduce.log
mpi_broadcast.log
mpi_gather.log
mpi_reduce.log
mpi_reduce_scatter.log
mpi_scatter.log
mpi_send_recv.log

NV with NCCL:
ccl_all_reduce.log

NV with NCCL+OpenMPI:
ccl_mpi_hybrid_all_reduce.log

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Scope and Design

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Python Specific (if Python files changed)

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• Type hints are added / kept consistent with the surrounding code.

Testing

• All applicable example programs have been built and tested successfully on at least one supported heterogeneous cluster setup.

Build, CI, and Tooling

• N/A- New backends or devices have been added to auto-detection in CMakeLists.txt under if(AUTO_DETECT_DEVICES) or to if(AUTO_DETECT_BACKENDS) if applicable.
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Documentation

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