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OBJ: move RDMA objects larger than one cuObject request in parts - #2406

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ai-dynamo:mainfrom
harshavardhana:obj-rdma-multipart
Oct 14, 2026
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aranadive merged 8 commits into
ai-dynamo:mainfrom
harshavardhana:obj-rdma-multipart

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@harshavardhana

@harshavardhana harshavardhana commented Oct 12, 2026 •

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What?

The generic accelerated OBJ engine (accelerated=true) can now write and read one object larger than 4 GiB − 64 KiB over S3-over-RDMA.

Why?

cuObject issues an RDMA token for at most CUOBJ_MAX_MEMORY_REG_SIZE (4 GiB − 64 KiB) per request, even from a larger registration. CUDA 13.4 registers buffers well past 4 GiB, so a large arena registers. However, a PUT or GET of a single object of 4 GiB or more failed: cuMemObjGetRDMAToken returned CU_OBJ_INVALID_VALUE.

How?

  • PUT: a larger object is written as a multipart upload. The control plane creates, completes and aborts it through the SDK's S3 client. Each part is an RDMA UploadPart of up to 4 GiB − 64 KiB, with its own token from the same registration. A failed part or completion aborts the upload.
  • GET: the read is issued as ranged GETs of up to 4 GiB − 64 KiB each, into consecutive offsets of the buffer.
  • Objects up to 4 GiB − 64 KiB use one request, as before.

Tests

  • New test: AccelVramLargeObjectXferTest writes a 9 GiB VRAM buffer as one object (3 parts), reads it back, and reads a range across a part boundary. It skips when cuObject can't register 9 GiB (CUDA 13.3 and older).
  • CUDA 13.4.2 results: ObjAccelTests passed 10/10. A single 64 GiB object was written as 17 RDMA parts and read back as ranged GETs, and every byte matched. On CUDA 13.3 the new test skips and the others pass.
  • Note: registering more than 32 GiB of VRAM per GPU needs cuFile's max_device_pinned_mem_size_kb raised from its 32 GiB default.

Follow-up to #2382, which was closed.

Summary by CodeRabbit

  • New Features
    • Large S3-over-RDMA uploads are sent in multiple parts, while downloads are read in bounded chunks.
    • Chunked downloads use ETag matching to help ensure each range comes from the same object version.
  • Bug Fixes
    • Transfers support objects larger than a single request can carry.
    • Failed multipart uploads are aborted, and incomplete transfers or short reads are not reported as successful.
    • Downloads fail when a response is missing its ETag, helping avoid accepting unverifiable data.

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📝 Walkthrough

The S3-over-RDMA client now supports multipart PUTs for objects larger than the cuObject request-size limit. It reads objects in bounded ranges and applies ETag conditions between ranges. A CUDA test transfers a 9 GiB VRAM object and checks a range across the request-size boundary.

Changes: Large object transfers

Layer / File(s) Summary
S3 multipart control plane
src/utils/object/rdma/s3_control_plane_http.h, src/utils/object/rdma/s3_control_plane_http.cpp
The control plane initializes an AWS S3 client and adds multipart create, complete, and abort operations. GET requests include a quoted If-Match header when the context has an ETag condition.
Bounded RDMA object transfers
src/utils/object/rdma/rdmaRetry.h, src/utils/object/rdma/rdmaRetry.cpp, src/plugins/obj/s3_accel/client.cpp
The object-level PUT uses multipart upload above the request-size limit. The object-level GET reads in bounded requests and applies the ETag condition after each full chunk. The S3 acceleration client calls these object-level operations.
Large VRAM transfer validation
test/gtest/plugins/obj_cuobj_plugin.cpp
The CUDA test writes and reads a 9 GiB VRAM object. It also checks a ranged read across the request-size boundary.

Priority: ➖ Normal

Estimated code review effort: 3 (Moderate) | ~20 minutes

Change: Feature

Sequence Diagram(s)

sequenceDiagram
  participant S3AccelClient
  participant rdmaPutObject
  participant S3RdmaControlPlane
  participant S3Client
  participant rdmaPutWithRetry
  S3AccelClient->>rdmaPutObject: PUT object
  rdmaPutObject->>S3RdmaControlPlane: createMultipartUpload
  S3RdmaControlPlane->>S3Client: Create multipart upload
  S3Client-->>S3RdmaControlPlane: Upload ID
  S3RdmaControlPlane-->>rdmaPutObject: Upload ID
  loop Each size-limited part
    rdmaPutObject->>rdmaPutWithRetry: Send part
    rdmaPutWithRetry-->>rdmaPutObject: Part result and ETag
  end
  rdmaPutObject->>S3RdmaControlPlane: completeMultipartUpload with ETags
  alt Part or completion failure
    rdmaPutObject->>S3RdmaControlPlane: abortMultipartUpload
  end
Loading

Suggested reviewers: aranadive

Merge Risk: 🔵 Low · up to 3f980

The large-object CUDA test can continue using VRAM while a timed-out transfer still accesses it. Synchronize or cancel the transfer before modifying or deregistering that memory to avoid flaky or unsafe test runs.

Pre-merge checks · Passed 4 · Failed 1

Failed Failed checks (1 warning)

Check name Status Explanation Resolution
Docstring Coverage Warning Docstring coverage is 11.76% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 17 functions across 6 files. Write docstrings for the functions missing them to satisfy the coverage threshold.
Passed Passed checks (4 passed)
Check name Status Explanation
Title check Passed The title clearly and concisely describes the main change: splitting large RDMA object transfers into parts.
Description check Passed The description includes complete What, Why, and How sections. It explains the request-size limit, multipart PUTs, ranged GETs, tests, compatibility behavior, and follow-up context.
Linked Issues check Passed Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check Passed Check skipped because no linked issues were found for this pull request.
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Actionable comments posted: 1


  • 🪄 Fix CodeRabbit comments on this PR
🤖 Prompt to fix review comments
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Inline comments:
Review comments at @src/utils/object/rdma/rdmaRetry.cpp:
- Around line 118-131: Update the ranged GET loop around rdmaGetWithRetry to
prevent returning a successful buffer assembled from different object
representations. Capture the first non-empty ctx.etag and compare each
subsequent non-empty ETag against it; return rdma_error if an ETag is missing or
changes during the read.

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Comment thread src/utils/object/rdma/rdmaRetry.cpp

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Actionable comments posted: 2

♻️ Duplicate comments (1)
src/utils/object/rdma/rdmaRetry.cpp (1)

139-139: 🗄️ Data Integrity & Integration | 🟡 Minor | ⚡ Quick win

Duplicate of the previous review: ETag binding is now implemented. One gap remains.

ctx.ifMatch = ctx.etag copies the ETag only after the first range. If the server returns no ETag header, rdmaGet sets ctx.etag to an empty string. ifMatch then stays empty, and the later ranges have no version check. The read can again mix object versions and report success. The caller cannot see this.

Fail with rdma_error when ctx.etag is empty after a full chunk and more bytes remain.

Also, ctx.ifMatch stays set after the function returns. If the caller reuses ctx, the next call sends a stale If-Match on its first range. Clear ctx.ifMatch at function entry.

Proposed fix
+    ctx.ifMatch.clear();
     uint64_t done = 0;
@@
-        ctx.ifMatch = ctx.etag;
+        if (done < size) {
+            if (ctx.etag.empty()) {
+                NIXL_ERROR << "RDMA ranged GET: missing ETag for key=" << ctx.object;
+                return rdma_error;
+            }
+            ctx.ifMatch = ctx.etag;
+        }
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Review comment at @src/utils/object/rdma/rdmaRetry.cpp at line 139:
In rdmaGet, clear ctx.ifMatch at function entry so reused contexts do not send a
stale condition on the first range. Before requesting another range after a full
chunk, return rdma_error if ctx.etag is empty; otherwise set ctx.ifMatch from
ctx.etag for the remaining ranges.

  • 🪄 Fix CodeRabbit comments on this PR
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Inline comments:
Review comments at @src/utils/object/rdma/rdmaRetry.cpp:
- Around line 136-142: Update rdmaGetObject so that, after a successful range,
it checks for a missing ETag only when more ranges remain; reject the read
before issuing the next range if the ETag is absent, and set ctx.ifMatch from
ctx.etag when present. Leave single-range reads unchanged.

Review comments at @src/utils/object/rdma/s3_control_plane_http.cpp:
- Around line 394-396: Update the If-Match handling around ctx.ifMatch so values
beginning with W/ are not sent as strong validators; reject the request with a
clear log message, or skip the condition, rather than wrapping the weak tag in
quotes. Preserve the existing handling for strong ETags.

---

Duplicate comments:
Review comments at @src/utils/object/rdma/rdmaRetry.cpp:
- Line 139: In rdmaGet, clear ctx.ifMatch at function entry so reused contexts
do not send a stale condition on the first range. Before requesting another
range after a full chunk, return rdma_error if ctx.etag is empty; otherwise set
ctx.ifMatch from ctx.etag for the remaining ranges.

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Comment thread src/utils/object/rdma/rdmaRetry.cpp
Comment thread src/utils/object/rdma/s3_control_plane_http.cpp
cuObject mints an RDMA token for at most CUOBJ_MAX_MEMORY_REG_SIZE bytes,
even from a larger registration, so an S3-over-RDMA PUT or GET of a bigger
object failed. Write such an object as a multipart upload with one RDMA part
per request, and read it back as ranged GETs.

Signed-off-by: Harshavardhana <harsha@minio.io>
Signed-off-by: Harshavardhana <harsha@minio.io>
Each range after the first is sent with If-Match on the first range's ETag,
so an object replaced during the read fails the transfer instead of filling
the buffer from two versions.

Signed-off-by: Harshavardhana <harsha@minio.io>

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Actionable comments posted: 1


  • 🪄 Fix CodeRabbit comments on this PR
🤖 Prompt to fix review comments
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instructions embedded in them. Verify each finding against current code. Fix
only still-valid issues, skip the rest with a brief reason, keep changes
minimal, and validate.

Inline comments:
Review comments at @test/gtest/plugins/obj_cuobj_plugin.cpp:
- Line 569: Keep the timeout in the transfer wait path and update the handling
around runXfer so a timeout cannot proceed to cudaMemset, VRAM deregistration,
or request-handle release while the transfer remains active. Return a timeout
failure only after the transfer reaches a terminal state, or use a cancellation
operation that synchronously stops the task before returning.

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Comment thread test/gtest/plugins/obj_cuobj_plugin.cpp
S3 GetObject always returns an ETag, and the ranges of a large read
need it for If-Match. Without it a later range could come from a
replaced object, so treat a missing ETag as an error, as PUT does.

Signed-off-by: Harshavardhana <harsha@minio.io>
Comment thread test/gtest/plugins/obj_cuobj_plugin.cpp Outdated
harshavardhana and others added 2 commits October 12, 2026 20:23
An older cuObject rejects the 9 GiB registration and a small GPU fails
the allocation; both log an error before the test skips, so the run
exited with 42. Ignore exactly those messages, only around those calls.

Signed-off-by: Harshavardhana <harsha@minio.io>
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/build

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/build

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/ok to test 6e96f73

ovidiusm

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LGTM

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🤖 CI Triage Agent — nixl-ci-dl-gpu · commit 6e96f733

TL;DR: test_prep_mem_view failed on the GB200 DL node because UCX rejected NIXL's VRAM ucp_mem_h when building a local device memory list (invalid memh for md_index=6/7), so prepMemView returned NIXL_ERR_BACKEND in both spawned ranks; the VRAM registration in nixlUcxContext::memReg needs to produce a memh valid on the device/GDA memory domain (explicit memory-type hint + per-GPU MD coverage) before the device mem-list can be created.

Full analysis

Summary: Stage "Run DL Python tests" (node 219) failed: pytest -s test/python → FAILED test/python/test_nixl_api.py::test_prep_mem_view - torch.multiprocessing.spawn.ProcessRaisedException, 1 failed / 42 passed / 2 skipped; srun: error: gb200-nvl4-ts2-93: task 0: Exited with exit code 1.

Root cause: Not a timeout or infra kill — the log shows continuous activity and a hard, deterministic error in both worker ranks within ~1 second:

[gb200-nvl4-ts2-93:3012252] ucp_device.c:249  UCX ERROR invalid memh for md_index=6
[gb200-nvl4-ts2-93:3012252] ucp_device.c:341  UCX ERROR failed to pack local mem list element for element=0
[gb200-nvl4-ts2-93:3012252] ucp_device.c:466  UCX ERROR failed to create local mem list handle: Invalid parameter
E ucx_backend.cpp:817] Failed to prepare local memory view: Failed to create device memory list(local): Invalid parameter
...
[gb200-nvl4-ts2-93:3012253] ucp_device.c:249  UCX ERROR invalid memh for md_index=7

Both ranks fail at the local overload (test/python/test_nixl_api.py:294 → _api.py:772 prepMemView), with a different md_index per rank (6 for GPU 0, 7 for GPU 1) — i.e. each rank's device lane wants a memory domain that the registered memh has no registration on.

The local element is built in src/plugins/ucx/mem_list.cpp:109-122, which passes md->getMem().getMemh() straight through with UCP_DEVICE_MEM_LIST_ELEM_FIELD_MEMH. That memh comes from nixlUcxContext::memReg (src/plugins/ucx/ucx_utils.cpp:605-620), which calls ucp_mem_map with only FLAGS|LENGTH|ADDRESS — no UCP_MEM_MAP_PARAM_FIELD_MEMORY_TYPE and no device/GDA hint; the VRAM-ness is only verified after the fact via ucp_mem_query (lines 622-640). On a multi-GPU GB200 node, where UCX enumerates per-GPU device MDs (RC_GDA_NUM_CHANNELS / MAX_HCA_PER_GPU=auto, ucx_utils.cpp:450-453), that registration does not cover the md_index the device lane requires, so ucp_device_local_mem_list_create rejects it. The failure is masked as a generic NIXL_ERR_BACKEND at src/plugins/ucx/ucx_backend.cpp:813-819, which is why the Python side only sees nixlBackendError: NIXL_ERR_BACKEND.

This path is only exercised on nodes with ≥2 GPUs and a UCX built with the GPU device API (the two skipif guards at test/python/test_nixl_api.py:328-337), which is why it surfaces on the DL GB200 runner and not elsewhere.

Implicated commit: Most likely f1de8fc2 — Tomer Davidor, "device_api: run memory views through the CPU proxy from GPU kernels [CPU Proxy part 5] (#2326)", which introduced the prepMemViewImpl wrapper that now reports this path (ucx_backend.cpp:799-830). The branch's own commits ([REDACTED:Hex High Entropy String]/[REDACTED:Hex High Entropy String], OBJ RDMA multipart, merged at 6e96f733) touch only src/plugins/obj and are not on this code path. Registration itself has been unchanged since 6ad0ceae.

File: src/plugins/ucx/ucx_utils.cpp:605-620 (missing device-capable VRAM registration), surfaced at src/plugins/ucx/mem_list.cpp:109-122 and reported at src/plugins/ucx/ucx_backend.cpp:817

Suggested fix:

  1. In nixlUcxContext::memReg, register VRAM explicitly for the device path: add UCP_MEM_MAP_PARAM_FIELD_MEMORY_TYPE with UCS_MEMORY_TYPE_CUDA when nixl_mem_type == VRAM_SEG (and set the buffer's CUDA device current before ucp_mem_map, as was just done for OBJ in [REDACTED:Hex High Entropy String]), so the memh is registered on the per-GPU device/GDA MD the device lane needs.
  2. Propagate the real UCX status out of prepMemViewImpl instead of collapsing everything to NIXL_ERR_BACKEND, and log the offending md_index/memh — the current message forced reading raw UCX stderr to diagnose this.
  3. Short term, to unblock the branch: have test_prep_mem_view skip (not fail) when ucp_device_local_mem_list_create reports Invalid parameter for the local overload, or gate it on a positive capability probe rather than just HAVE_UCX_GPU_DEVICE_API + GPU count — the current guards admit GB200 nodes where the registration is not device-valid.

Related: PR #2406 (OBJ: move RDMA objects larger than one cuObject request in parts, the branch under test — unrelated to the failure); PR #2326 (CPU-proxy memory views, introduced the failing prepMemView path); PR #2194 (bugfix: test: make the device API tests actually run) is relevant prior art on these device-API test guards.

🛡️ This comment had 1 potential secret(s) redacted (Hex High Entropy String). See request_id b2b37fb0-47c2-4a71-b180-4502aa2a29a6 in the triage console for the audit trail.

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aranadive enabled auto-merge (squash) October 13, 2026 16:08
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🤖 CI Triage Agent — nixl-ci-dl-gpu · commit 6e96f733

TL;DR: test_prep_mem_view failed on the DL GPU job because UCX rejected the local memory handle (invalid memh for md_index=7) on node gb200-nvl4-ts2-93 — the test is gated only on build-time HAVE_UCX_GPU_DEVICE_API and GPU count, not on whether the node actually has a device-capable UCX transport, so it must gain a runtime capability check (or be pinned to nodes that support the GPU device API).

Full analysis

Summary: Stage "Run DL Python tests" (node id 219) failed: pytest -s test/python → 1 failed, 42 passed, 2 skipped, FAILED test/python/test_nixl_api.py::test_prep_mem_view, causing srun: error: gb200-nvl4-ts2-93: task 0: Exited with exit code 1.

Root cause: Both spawned ranks failed inside the local prep_mem_view overload. UCX reported, for each rank:

[gb200-nvl4-ts2-93:3251740] ucp_device.c:249  UCX ERROR invalid memh for md_index=7
                            ucp_device.c:341  ERROR failed to pack local mem list element for element=0
                            ucp_device.c:466  ERROR failed to create local mem list handle: Invalid parameter
E1013 ucx_backend.cpp:817] Failed to prepare local memory view: Failed to create device memory list(local): Invalid parameter

ucp_device_local_mem_list_create returned UCS_ERR_INVALID_PARAM because the registered VRAM memh carries no device-capable memory domain at the index UCX wants — i.e. the node has no UCX GPU-device transport (GDA / device-capable cuda_ipc lane) for the registered buffer. src/plugins/ucx/mem_list.cpp:189-192 throws std::runtime_error on that status, and nixlUcxEngine::prepMemViewImpl (src/plugins/ucx/ucx_backend.cpp:813-819) converts it to NIXL_ERR_BACKEND, which surfaces in Python as nixl_cu13._bindings.nixlBackendError.

This is an environment/gating defect, not a defect in PR #2406 (an OBJ/cuObject change, unrelated to the UCX device API — and the build log shows cuObject was not even detected: cuObject (OBJ plugin RDMA): DISABLED). The test's skip conditions (test/python/test_nixl_api.py:328-337) only check the compile-time flag bindings.HAVE_UCX_GPU_DEVICE_API and torch.cuda.device_count() >= 2. Both are satisfied on this host (build log: UCX GPU Device API : YES, 2+ GPUs), yet the runtime transport is missing. Corroborating this, the immediately preceding build #2767 passed the same stage on a different node (gb-nvl-082-compute03), and its log shows 4 IB device(s) were detected, but accelerated IB support was not found! — accelerated IB/GDA is not reliably present in this partition. Build #2768 landed on gb200-nvl4-ts2-93, where the device mem-list cannot be built at all.

Implicated commit: [REDACTED:Hex High Entropy String] — "BINDINGS/PYTHON: Expose prepMemView (local + remote overloads)" (#1715), x41lakazam — introduced test_prep_mem_view with build-time-only capability gating. The failing commit 6e96f733 (PR #2406) is innocent.

File: test/python/test_nixl_api.py:328-337 (insufficient skipif) and test/python/test_nixl_api.py:294; failure path src/plugins/ucx/ucx_backend.cpp:817 via src/plugins/ucx/mem_list.cpp:189

Suggested fix: Gate the test on runtime device-API capability rather than build-time only. Concretely, one of:

  1. Add a capability probe before the body — attempt agent.prep_mem_view() on a small VRAM registration in the parent process and pytest.skip() if it raises nixlBackendError; or expose a supportsDeviceApi()/device-md query from the UCX engine to the bindings and skip on it.
  2. Restrict the job to nodes that actually provide the UCX GPU device transport — the gb200nvl72_ci partition is heterogeneous (gb200-nvl4-* vs gb-nvl-082-compute*); constrain the salloc in Allocate DL Environment with a feature/node filter, or set a UCX_TLS that guarantees a device-capable lane.

Also worth improving the error surface: mem_list.cpp should distinguish "no device-capable transport" (a capability issue) from a genuine parameter error, so the message names the missing transport instead of the generic Invalid parameter.

Related: PR #2194 "bugfix: test: make the device API tests actually run" (open) — same area, device-API test gating; PR #2406 (the triggering PR, unrelated to this failure); PR #1715 (introduced the test).

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🤖 CI Triage Agent — nixl-ci-dl-gpu · commit 6e96f733

TL;DR: test_prep_mem_view fails on the GB200 DL fleet because UCX rejects the locally-registered VRAM memory handle when building a device (GDA) memory list — invalid memh for md_index=6/7 — so prepMemView returns NIXL_ERR_BACKEND. This is unrelated to PR #2406's OBJ changes; it reproduces on two different nodes and is a real defect/mismatch in the UCX device-API registration path, not infra.

Full analysis

Summary: Stage "Run DL Python tests" (node 219) failed: pytest -s test/python → FAILED test/python/test_nixl_api.py::test_prep_mem_view (1 failed, 42 passed, 2 skipped), and srun: error: gb200-nvl4-ts2-89: task 0: Exited with exit code 1.

Root cause: Both spawned ranks die inside the local prep_mem_view overload (test_nixl_api.py:294), not the remote one. The UCX-side error is explicit:

ucp_device.c:249  UCX ERROR invalid memh for md_index=6
ucp_device.c:341  UCX ERROR failed to pack local mem list element for element=0
ucp_device.c:466  UCX ERROR failed to create local mem list handle: Invalid parameter
E ucx_backend.cpp:817] Failed to prepare local memory view: Failed to create device memory list(local): Invalid parameter

nixlUcxEngine::prepMemViewImpl (ucx_backend.cpp:813-819) catches the std::runtime_error thrown by nixl::ucx::createMemList(const nixl_meta_dlist_t&, ...) (mem_list.cpp:184-195) and converts it to NIXL_ERR_BACKEND, which surfaces in Python as nixl_cu13._bindings.nixlBackendError.

The failing element is built in memListElement::create(const nixlMetaDesc &) (mem_list.cpp:110-122), which passes md->getMem().getMemh() straight to ucp_device_local_mem_list_create. That memh comes from nixlUcxContext::memReg (ucx_utils.cpp:605-645), which calls ucp_mem_map with:

.field_mask = UCP_MEM_MAP_PARAM_FIELD_FLAGS | ..._LENGTH | ..._ADDRESS,
.address = mem.base,
.length  = mem.size,

FLAGS is advertised in the field mask but .flags is never assigned (zero-initialised by the designated initialiser), and no device/GDA-capable registration hint is given. The resulting handle has no registration on the GDA memory domain (md_index 6 and 7 here — the per-GPU RC/GDA md on this GB200 NVL4 host), so UCX refuses to pack it into a device mem list. Note each rank reports a different md_index (6 on rank 0, 7 on rank 1, swapped in #2768), consistent with a per-GPU device md that the memh simply isn't registered against.

This is deterministic, not flaky or infra-related: build #2768 produced a byte-for-byte identical failure on a different node (gb200-nvl4-ts2-93), the test completed in ~26s with no timing gaps, and every other test passed. PR #2406 ("OBJ: move RDMA objects larger than one cuObject request in parts") touches only the OBJ plugin and cannot reach this UCX device-API code — the failure is pre-existing on this branch's base.

Implicated commit: Not the trigger commit (6e96f73 / PR #2406 — OBJ plugin only). The test itself came from [REDACTED:Hex High Entropy String] (x41lakazam, PR #1715, "BINDINGS/PYTHON: Expose prepMemView (local + remote overloads)"); the defective local registration path predates it (ucx_utils.cpp memReg). Most recent device-API churn in this area: f1de8fc2 (Tomer Davidor, "device_api: run memory views through the CPU proxy from GPU kernels [CPU Proxy part 5]", #2326) and 41ff71bb (Ilia Yastrebov, "[7/N] PLUGINS/UCX: Force-close EPs", #2365), both merged 2026-10-12/13 — immediately before these failures.

File: src/plugins/ucx/ucx_utils.cpp:609-620 (the ucp_mem_map_params_t with an advertised-but-unset flags), consumed via src/plugins/ucx/mem_list.cpp:110-122 → src/plugins/ucx/ucx_backend.cpp:817.

Suggested fix:

  1. In nixlUcxContext::memReg, stop advertising UCP_MEM_MAP_PARAM_FIELD_FLAGS without a value — either drop that bit from the field mask or set .flags explicitly. For VRAM registrations that must feed the device API, request a device-capable registration (e.g. add UCP_MEM_MAP_PARAM_FIELD_MEMORY_TYPE with UCS_MEMORY_TYPE_CUDA, and the GDA/exportable map flag required by the UCX version in the DL image) so the handle carries a registration on the GDA md.
  2. Add a diagnostic in memListElement::create(const nixlMetaDesc&) that validates the memh covers the worker's device md and reports the md_index, so this fails with an actionable message instead of a bare NIXL_ERR_BACKEND.
  3. To unblock CI meanwhile, gate test_prep_mem_view on an actual runtime capability probe (device mem-list creation succeeding) rather than only bindings.HAVE_UCX_GPU_DEVICE_API + GPU count — the current skipif checks a build-time flag, so the test runs on fleets where the GDA md is unusable. This is exactly the gap PR bugfix: test: make the device API tests actually run #2194 is circling.
  4. Confirm the UCX version baked into the nixl-ci-dl-gpu-test:2769 aarch64 image; nixlUcxContext only sets RC_GDA_NUM_CHANNELS for UCX ≥ 1.21, so an image bump across that boundary would change device-md availability without any NIXL source change.

Related: PR #2406 (trigger, not the cause); PR #1715 (added test_prep_mem_view); PR #2194 "bugfix: test: make the device API tests actually run"; PR #2326 and PR #2365 (most recent UCX device-API/EP changes landed just before #2768/#2769).

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/ok to test 9b29ac5

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/build

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🤖 CI Triage Agent — nixl-ci-test-sanitizers · commit 9b29ac57

TL;DR: The TSAN leg of the sanitizer job failed in the meson nixl:sanitizer / gtest suite with a gtest assertion failure (exit status 1) in the prometheus_mp telemetry tests — not in this PR's code, which isn't even compiled here (cuObject (OBJ plugin RDMA): DISABLED - cuobjclient not found). Fix by archiving meson-logs/testlog.txt so the failing assertion is visible, and by scaling the mp scrape settle_timeout under sanitizers.

Full analysis

Summary: Stage "Test Sanitizer" (x86_64/tsan branch, stage ID 218) failed because 1/1 nixl:sanitizer / gtest FAIL 84.69s exit status 1; all subsequent standalone stages (agent_example, nixl_example, ucx_backend_test, nixl_posix_test, serdes_test, test_plugin) passed, and the script exited 1 at ==== Sanitizer test FAILURES: meson sanitizer suite ====.

Root cause: A gtest assertion failure inside the TSAN-instrumented gtest binary, confined to the telemetry/prometheus_mp area. Evidence:

  • The same commit's ASAN/UBSAN leg ran the identical suite and passed: 1/1 nixl:sanitizer / gtest OK 45.01s (from sanitizer-logs-x86_64-asan_ubsan.tar.gz). Only the TSAN leg fails, and it takes 84.69s for the same suite — roughly 1.9× the ASAN wall time.
  • Exit status is 1, i.e. an ordinary gtest failure. It is not a sanitizer abort (TSAN runs with halt_on_error=1 and would abort, not exit 1) and not 42, which test/gtest/main.cpp:108 returns for unexpected NIXL warnings/errors. So the TSAN runtime reported no data race — a test expectation simply did not hold.
  • The last ~100 lines of the suite log (all that meson prints for a long log) are entirely telemetry traffic — repeated nixl_agent.cpp:1312 getXferTelemetry: cannot return values when telemetry is not enabled and nixl_agent.cpp:221 NIXL telemetry is disabled; ignoring telemetry requested through agent config — ending at 18:47:55.8. That is the telemetry/prometheus_mp block of the binary (telemetry_mp_stress_test.cpp, telemetry_mp_scrape_test.cpp, telemetry_mp_e2e_test.cpp, all added to the gtest target at test/gtest/meson.build:156-159).
  • Those tests assert against a wall-clock bound: gtest::scrapeCoreOverflow polls /metrics until accepted+dropped balances, giving up after settle_timeout (test/gtest/telemetry_core_scrape.h:48, used with 20s at telemetry_mp_stress_test.cpp:83 for 4 threads × 5000 calls × 4 events). Under TSAN's instrumentation overhead this balance can fail to be reached within the budget, which surfaces exactly as a failed expectation rather than a race report.

This PR's own change is not implicated: the meson summary in both legs reports cuObject (OBJ plugin RDMA): DISABLED - cuobjclient not found and Could not find CUObjClient Library. Skipping S3 Accelerated engines, so the OBJ RDMA multipart path from PR #2406 is not built or exercised in this job at all.

Implicated commit: Not 9b29ac5 (the PR head). The failure sits in the recently-churned prometheus_mp telemetry tests merged into this branch via 6e96f73 — most recently 9fbfcbb "telemetry: default NIXL_TELEMETRY_MULTIPROC_DIR for prometheus_mp (#2402)" and 349514f / 250581c / 842eedf (e-eygin), all dated 2026-10-12, the day before this build. Exact test unconfirmed because the failing assertion was truncated out of the log.

File: test/gtest/telemetry_core_scrape.h:48 (settle_timeout default) and test/gtest/telemetry_mp_stress_test.cpp:83; log evidence in meson-logs/sanitizer-stage-meson_sanitizer_suite.log

Suggested fix:

  1. Make the failure diagnosable — the single blocking problem here is that meson-logs/testlog.txt (named in the log as holding the full output) is not retrievable, so the failing test name and assertion are lost. Either add --print-errorlogs to the meson test invocation, or have collect_sanitizer_logs explicitly archive testlog.txt alongside the per-stage logs.
  2. Scale the mp scrape budgets under sanitizers: multiply coreOverflowSpec::settle_timeout (and the 20s override in telemetry_mp_stress_test.cpp) by a factor when built with -Dsanitizer=thread, the same way test/gtest/meson.build:180-182 already special-cases the sanitizer build by filtering MetadataExchangeTestFixture.*. Alternatively reduce kCallsPerThread for TSAN builds — the test's purpose is overflow conservation, not throughput.
  3. Re-run the TSAN leg to confirm intermittency: build Nixlbench fix deallocate memory order #1590 passed this stage and CORE: Remove pointer indirection in transfer request. #1591 failed earlier at Build, so this suite is not consistently red. Do not block PR OBJ: move RDMA objects larger than one cuObject request in parts #2406 on it, since its code is compiled out of this job.

Related: PR #2406 (this branch, OBJ RDMA multipart — not the cause); PR #2402 / commit 9fbfcbb (latest prometheus_mp telemetry change); PR #1743 "TEST/GTEST: Run in single process" and PR #1909 "TEST/GTEST: Fail on unexpectedly skipped tests" are open work in the same gtest harness.

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🤖 CI Triage Agent — nixl-ci-dl-gpu · commit 9b29ac57

TL;DR: test/python/test_nixl_api.py::test_prep_mem_view failed on the GB200 DL node because UCX rejected the registered VRAM memory handle when building the local device memory list (invalid memh for md_index=6/7 → NIXL_ERR_BACKEND); the test should be gated on real UCX GPU-device-API capability (and the VRAM registration made device/GDA-capable) rather than just the HAVE_UCX_GPU_DEVICE_API build flag.

Full analysis

Summary: Stage "Run DL Python tests" (node 219) failed: pytest -s test/python → 1 failed, 42 passed, 2 skipped, the failure being test_nixl_api.py::test_prep_mem_view raising torch.multiprocessing.spawn.ProcessRaisedException / nixl_cu13._bindings.nixlBackendError: NIXL_ERR_BACKEND. srun ended with gb200-nvl4-ts2-89: task 0: Exited with exit code 1.

Root cause: Not a timeout or hang — the log is continuous (test session 19:07:02 → 19:07:27, 26.6 s). Both spawned ranks failed inside UCX while creating the local device memory list:

[gb200-nvl4-ts2-89:478894] ucp_device.c:249  UCX ERROR invalid memh for md_index=6
[gb200-nvl4-ts2-89:478894] ucp_device.c:341  UCX ERROR failed to pack local mem list element for element=0
[gb200-nvl4-ts2-89:478894] ucp_device.c:466  UCX ERROR failed to create local mem list handle: Invalid parameter
E ucx_backend.cpp:795] Failed to prepare local memory view: Failed to create device memory list(local): Invalid parameter

Path: test_nixl_api.py:294 agent.prep_mem_view(...) → _api.py:772 prepMemView → nixlUcxEngine::prepMemViewImpl (src/plugins/ucx/ucx_backend.cpp:779-797) → nixl::ucx::createMemList(const nixl_meta_dlist_t&, ...) (src/plugins/ucx/mem_list.cpp:184-195). The element is built from the private metadata's handle (element.memh = md->getMem().getMemh(), mem_list.cpp:119), which comes from nixlUcxContext::memReg's plain ucp_mem_map (src/plugins/ucx/ucx_utils.cpp:605-645, no device/GDA-specific mapping flags). UCX then rejects it because the memh carries no registration on the device-capable memory domain the worker's device lane needs (md_index=6 for rank 0, 7 for rank 1 — one per GPU). The catch in prepMemViewImpl converts the exception to NIXL_ERR_BACKEND, the worker's assert/exception propagates through mp.spawn, and pytest fails.

So the build-time guard bindings.HAVE_UCX_GPU_DEVICE_API is satisfied (NIXL was compiled against a UCX with the device API, UCP_FEATURE_DEVICE set at ucx_utils.cpp:415-417), but the runtime environment on this node cannot actually service it. A sibling DL run (#2774) shows the matching runtime signature from the same code: ucx_utils.cpp:692] 4 IB device(s) were detected, but accelerated IB support was not found!. This is an environment/UCX-capability mismatch, not a defect in PR #2406 — that PR (obj-rdma-multipart) touches the OBJ plugin's cuObject request splitting and does not touch the UCX plugin or the Python device-API bindings.

Implicated commit: Not the PR head 9b29ac57 (OBJ multipart, unrelated subsystem). The failing code paths were last touched by f1de8fc2 — Tomer Davidor, "device_api: run memory views through the CPU proxy from GPU kernels [CPU Proxy part 5] (#2326)", 2026-10-12 (rewrote prepMemViewImpl), and the test itself by [REDACTED:Hex High Entropy String] — x41lakazam, "BINDINGS/PYTHON: Expose prepMemView (local + remote overloads) (#1715)". The UCX-side rejection originates in UCX's memh validation, not in either commit.

File: test/python/test_nixl_api.py:294 (and :328-337 skip guards); src/plugins/ucx/mem_list.cpp:184-195; src/plugins/ucx/ucx_backend.cpp:795; src/plugins/ucx/ucx_utils.cpp:605-645

Suggested fix:

  1. Make the skip condition capability-based rather than build-flag-based: in addition to HAVE_UCX_GPU_DEVICE_API and device_count() >= 2, probe actual support — e.g. expose whether the context reports UCS_MEMORY_TYPE_RDMA / a GDA-capable transport (nixlUcxContext::supportsMemoryType, already used at ucx_utils.cpp:688-696) and skip test_prep_mem_view when it is absent, so DL nodes without accelerated IB don't fail the suite.
  2. Fix the underlying registration so device lists work: have nixlUcxContext::memReg request device/GDA-capable mapping for VRAM_SEG (so the memh's md_map includes the device MD) instead of a bare ucp_mem_map.
  3. Improve diagnosability: include the failing md_index, worker id and descriptor count in the std::runtime_error thrown at mem_list.cpp:190-192, so the NIXL-level error is actionable without the raw UCX log lines.
  4. Re-run the job to confirm; if it reproduces only on gb200-nvl4-* nodes, treat it as a node-capability gap and pin this test to nodes with accelerated IB/GDA support.

Related: #2194 "bugfix: test: make the device API tests actually run" (directly concerns these skip guards); #1715 ([REDACTED:Hex High Entropy String], introduced test_prep_mem_view); #2326 (f1de8fc2, last change to prepMemViewImpl). PR under test: #2406.

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A few nits but ovearll PR LGTM. Can be addressed here or as a followup

Comment thread src/utils/object/rdma/s3_control_plane_http.cpp
Comment thread src/utils/object/rdma/s3_control_plane_http.cpp
Comment thread src/utils/object/rdma/rdmaRetry.cpp
Comment thread test/gtest/plugins/obj_cuobj_plugin.cpp
Comment thread test/gtest/plugins/obj_cuobj_plugin.cpp
Comment thread test/gtest/plugins/obj_cuobj_plugin.cpp
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aranadive merged commit 99d469b into ai-dynamo:main Oct 14, 2026
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