add dsl algorithms support to bench collective

[RJ Souza (Empyreus)]

• add dsl algorithms support to bench collective
• replace multinode pipeline tests with bench_collective tests

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[Copilot]

Pull request overview

Adds multi-node DSL collective autotuning and CI coverage for AllReduce, AllGather, and ReduceScatter.

Changes:

• Compiles and tunes runtime DSL variants with configurable launch geometry.
• Adds ReduceScatter benchmarking and correctness validation.
• Reworks multi-node CI to exercise DSL collectives.

Reviewed changes

Copilot reviewed 7 out of 7 changed files in this pull request and generated 7 comments.

Show a summary per file

File	Description
test/deploy/run_tests.sh	Adds manual multi-node DSL test helpers.
python/mscclpp/default_algos/reducescatter_multi_nodes.py	Adds a plan-generation CLI.
python/mscclpp_benchmark/tuner.py	Supports candidate-specific tuning dimensions.
python/mscclpp_benchmark/correctness.py	Validates ReduceScatter output.
python/mscclpp_benchmark/comm.py	Compiles and executes DSL variants.
python/mscclpp_benchmark/bench_collective.py	Adds DSL candidates and ReduceScatter benchmarking.
.azure-pipelines/multi-nodes-test.yml	Adds three multi-node DSL benchmark jobs.

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[Copilot]

Pull request overview

Copilot reviewed 7 out of 7 changed files in this pull request and generated 3 comments.

Suppressed comments (2)

python/mscclpp_benchmark/comm.py:203

• Every compiled DSL plan is hard-coded as in-place, but --enable-dsl can be combined with --buffer-mode out-of-place, and _dsl_candidate_specs does not filter by algorithm.buffer_mode. For out-of-place AllReduce/AllGather, the tuner therefore executes plans whose buffer layout assumes aliasing, causing incorrect output before falling into its default fallback. Either compile the requested mode where the builder supports it, or reject/filter DSL candidates whose mode does not match the case.

                    collective=collective_op,
                    nranks_per_node=nranks_per_node,
                    world_size=world_size,
                    in_place=True,

python/mscclpp_benchmark/bench_collective.py:405

• The accepted buffer_mode argument is ignored for ReduceScatter: requesting out-of-place still returns an aliased input/output case. This silently benchmarks a different layout than the CLI requested. Since the registered ReduceScatter DSL algorithm is in-place-only, reject this combination explicitly.

    if collective == _REDUCESCATTER:
        # The DSL reducescatter is compiled in-place, so the per-rank output chunk always aliases the
        # matching slice of the full input buffer (mirrors python/test/executor_test.py build_bufs).
        input_buffer = _mscclpp().GpuBuffer(nelems * comm_group.nranks, dtype=dtype_spec.cupy_dtype)