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Adds a single test parameterized over providers. It allocates two symmetric tensors, takes each one's own peer table, and runs one kernel that reads the peer's first tensor through the first table and writes the peer's second tensor through the second. What that reaches which a single-tensor test cannot: each tensor resolves only through its own table. Iris and rocSHMEM both allocate from one symmetric heap, so the peer delta is a constant of the heap and any table happens to translate any pointer. Torch Symmetric Memory is symmetric memory rather than a symmetric heap -- each tensor is its own allocation with its own peer mapping -- so it has one translation per tensor and the deltas differ between allocations. A kernel reusing one table for two tensors works on the heap providers and silently mistranslates on the per-tensor one. Adding a provider is one entry in PROVIDERS; Torch Symmetric Memory joins when its provider lands. Providers are built inside the fixture rather than at module scope so an unavailable one skips its own parameters instead of collecting zero items, which would make pytest exit 5 and fail the distributed run.
mawad-amd
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September 22, 2026 15:56
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The device-side contract is a plain int64 table, so it does not depend on which backend consumes it. Adds a Gluon kernel that does the same manual translation and parameterizes the test over both, so the same two tables are asserted to drive either dialect to the same result. Sizes the BlockedLayout from BLOCK_SIZE rather than hardcoding [1]: the existing Gluon tests use blocks of 32 or fewer, where one element per lane covers the block. At 256 it does not.
The Gluon BlockedLayout has to agree with the block, and the lane count in it is not a constant: 64 on CDNA, 32 on NVIDIA and RDNA. Query it with triton.runtime.driver.active.get_current_target().warp_size and pass it in as a constexpr, rather than hardcoding the CDNA value. Asserts the block divides evenly into warps, so a bad pairing fails with a clear message rather than as a layout compile error.
peer_ptrs[r] is the tensor's address on rank r, so subtracting our own entry from our own pointer is subtracting a number from itself. The byte-cast and add cancelled with it. Carried over from the heap-anchored kernel, where the anchor names the heap rather than the allocation and the offset is real. The kernel no longer needs its own rank, so CUR_RANK goes too.
Every method on it forwarded unchanged. Iris.allocate_symmetric, get_rank, get_num_ranks and barrier already match what the rocSHMEM provider exposes, signatures included, so the context goes into PROVIDERS unwrapped. Needing an adapter would have meant the two interfaces had not actually converged. Also drops a .name attribute nothing read.
mawad-amd
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September 22, 2026 21:45
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Adds a single test parameterized over providers. It allocates two
symmetric tensors, takes each one's own peer table, and runs one kernel
that reads the peer's first tensor through the first table and writes the
peer's second tensor through the second.
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