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pith:HNQL6W6S

pith:2026:HNQL6W6SSPCRLJA5UXI66BN7QW
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NeuroRing: Scaling Spiking Neural Networks via Multi-FPGA Bidirectional Ring Topologies and Stream-Dataflow Architectures

Artur Podobas, Muhammad Ihsan Al Hafiz

A bidirectional ring topology and stream-dataflow architecture on FPGAs enables scalable faster-than-real-time execution of large spiking neural networks while preserving activity statistics.

arxiv:2604.28059 v2 · 2026-04-30 · cs.AR · cs.DC · cs.NE

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\pithnumber{HNQL6W6SSPCRLJA5UXI66BN7QW}

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3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

NeuroRing preserves the key activity statistics of the NEST reference model, achieves faster-than-real-time execution of the full-scale cortical microcircuit with a real-time factor (RTF) of 0.83, exhibits meaningful strong and weak scaling, and provides competitive energy efficiency on two programmable FPGAs.

C2weakest assumption

That the bidirectional ring topology and stream-dataflow architecture will continue to avoid communication bottlenecks and synchronization overhead when scaled beyond the evaluated two-FPGA configuration or to networks with different spike sparsity patterns.

C3one line summary

NeuroRing delivers a modular multi-FPGA accelerator for spiking neural networks that achieves real-time factor 0.83 on the full cortical microcircuit while preserving NEST activity statistics and showing scaling behavior.

Receipt and verification
First computed 2026-05-27T01:05:55.495584Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

3b60bf5bd293c515a41da5d1ef05bf85a5c08cd4b1b82462d823ac8183badf1d

Aliases

arxiv: 2604.28059 · arxiv_version: 2604.28059v2 · doi: 10.48550/arxiv.2604.28059 · pith_short_12: HNQL6W6SSPCR · pith_short_16: HNQL6W6SSPCRLJA5 · pith_short_8: HNQL6W6S
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/HNQL6W6SSPCRLJA5UXI66BN7QW \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 3b60bf5bd293c515a41da5d1ef05bf85a5c08cd4b1b82462d823ac8183badf1d
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "6b2768f10d21180979f96f5e2194aeb8895a5db4fb95514a104d088c3b643094",
    "cross_cats_sorted": [
      "cs.DC",
      "cs.NE"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.AR",
    "submitted_at": "2026-04-30T16:04:26Z",
    "title_canon_sha256": "847625e38ad65a13137167a7d5e6245df02b0f930655a4e8971809b61a09a6a5"
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  "source": {
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    "kind": "arxiv",
    "version": 2
  }
}