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SparkRing 2026.10.2 (pre-release)

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@FujitsuPolycom FujitsuPolycom released this 10 Oct 17:04
· 223 commits to main since this release
2026.10.2
20c9afc

SparkRing 2026.10.2

SparkRing's glm53-flash-tp2 and glm53-flash-tp4 profiles run
GLM-5.3-Flash-NVFP4-MXFP8-CSF-QAD, created by Local Inference Lab, Inc., a
non-profit organization, available at
https://huggingface.co/local-inference-lab/GLM-5.3-Flash-NVFP4-MXFP8-CSF-QAD.
GLM-5.3-Flash-NVFP4-MXFP8-CSF-QAD is licensed under the Local Inference Lab
License, Version 1.0.

Pre-release for testing. Packages built from tag 2026.10.2 install this
release's image by default. main, install.sh from main and the
Install Builder stay on
2026.10.1 until this release merges. The
release record
has the full evidence and gates.

What SIRCL is

SIRCL is SparkRing's own collective-communication layer for DGX Sparks
cabled directly to each other over ConnectX-7, with no switch. It replaces
NCCL for vLLM's tensor-parallel and decode-context-parallel collectives.

  • Each Spark talks RDMA straight to its cabled neighbours. Sparks that aren't
    cabled to each other are reached through the ConnectX-7's hardware relay on
    the Sparks in between, so a ring of four or eight behaves like one fabric.
  • It picks a schedule by message size: one-shot for small messages, two-shot
    for medium, a ring for large. For GLM-5.3 it can also fuse the all-reduce
    with the following RMSNorm.
  • Its settings come from a tuning table measured on real rings. You can
    measure your own with sudo sparkring fabric tune.
  • On eight Sparks, measured through libsircl, a 4 KiB all-reduce takes about
    18 µs, and a 256 MiB all-reduce runs at 24.3 GB/s bus bandwidth, faster
    than NCCL 2.32.3 on the same cables
    (record).

libsircl puts the same protocol behind NCCL's C API (it loads as
libnccl.so.2), so unmodified programs such as nccl-tests and PyTorch can use
it. It's SparkRing's own implementation under Apache-2.0, not NVIDIA NCCL.

What's in it

Installer image dev-20261010-kraken-csf-sircl032-libsircl060cd-plugins-status036
(ghcr.io/fujitsupolycom/sparkring@sha256:4fffc4dc3074d5539f4e9d3a013ff9ef4e0be570a95b74d4646ee341da1f6911): 2026.10.1's image plus SIRCL 0.3.2, libsircl 0.6.0 and the GLM-5.3 plugins.

  • Collectives run on SIRCL with NCCL off on any fabric that sparkring setup
    recorded.
  • Setup handles pairs, lines and rings of up to eight Sparks. It can adopt an
    existing ring (--adopt) or set up a recabled one (--re-form).
  • GLM-5.3 runs on eight Sparks (glm53-nvfp4-tp8), and GLM-5.3-Flash installs
    the CSF checkpoint on this image (--checkpoint nvfp4-spark installs
    NVFP4-Spark).
  • Running vLLM on libsircl (--transport libsircl) is research-only.
  • sparkring check also checks GPU clocks, and --report writes a test
    report to attach to an issue.

Speed

Decode at 32K context, output tok/s:

Model Checkpoint Sparks --profile 1 / 4 / 8 streams Prefill, 32K prompt (tok/s)
GLM-5.3 NVFP4 8 glm53-nvfp4-tp8 47.9 / 99.8 / 143.7 1,343
GLM-5.3-Flash CSF 4 glm53-flash-tp4 64.2 / 126.6 / 218.7 3,127
GLM-5.3-Flash CSF 2 glm53-flash-tp2 39.5 / 87.1 / 123.2 2,138
Qwen3.8-Flash-Next QAD step 5500 4 qwen38-flash-next-qad-tp4 62.1 / 149.4 / 234.0 4,666
Qwen3.8-Flash-Next QAD step 5500 2 qwen38-flash-next-tp2 42.9 / 109.9 / 162.9 3,649
DeepSeek-V4.1-Flash FP8/MXFP4 4 deepseek-v41-flash-tp4 63.8 / 127.5 / 182.8 4,328

On four Sparks, --checkpoint qad-step5500-mxfp8-attention decodes 6–8 % faster than the default checkpoint in the median of two starts on the same ring; it was not compared on two Sparks.

glm53-flash-tp2 and glm53-flash-tp4 are short names of the profile IDs glm53-flash-nvfp4-spark-tp2 and glm53-flash-nvfp4-spark-tp4; both names install the CSF checkpoint on this image.
Each row's record is under performance/records/.

Tested

On eight DGX Sparks, cabled as one ring of eight and then as two rings of
four: every profile above installed with sparkring install and passed
sparkring check and its known-answer requests. So did a model switch and
two pairs on one ring. libsircl passed its collective tests on both layouts.
CPU checks and the release-safety scan pass.

Known issues

  • Installed libsircl deployments report ok: false in sparkring check,
    because the installer doesn't judge libsircl receipts yet.
  • libsircl's broadcast is slow.

Try it

On Node A:

curl -fsSL https://raw.githubusercontent.com/FujitsuPolycom/sparkring/2026.10.2/install.sh | bash -s -- --ref 2026.10.2 --package-only
sudo sparkring setup --plan     # only if `sudo sparkring fabric show` finds no fabric; then sudo sparkring setup
sudo sparkring install --profile PROFILE --image 2026.10.2 --plan
sudo sparkring install --profile PROFILE --image 2026.10.2
sudo sparkring check --report ~/sparkring-report

A Spark that holds the 2026.10.1 image downloads only the 6 layers this image adds, 8.3 MiB.

To tune SIRCL to your cables, run sudo sparkring fabric tune --execute
while no model serves, then install again. It takes up to half an hour per
group shape.

Post the report on the 2026.10.2 pull request or in an issue titled
[test] 2026.10.2 PROFILE.

Go back to 2026.10.1

  • Keep this package and run a profile on 2026.10.1's image and transport:
    sudo sparkring install --profile PROFILE --image 2026.10.1
    (another image).
  • Keep this image without SIRCL: add --transport prepared.
  • Reinstall main's package, whose default image is 2026.10.1's:
    curl -fsSL https://raw.githubusercontent.com/FujitsuPolycom/sparkring/main/install.sh | bash -s -- --package-only.
    This hasn't been tested on a cluster that this package's setup re-formed.
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