Neuromorphic & spiking networks Federating

SNN Studio

Stochastic-computing and neuromorphic hardware co-design — a Rust SIMD engine, spiking simulation, and SystemVerilog RTL generation, every kernel benchmarked.

Universal Stochastic Computing Framework for Neuromorphic Hardware — Rust SIMD engine, Python simulation, Verilog RTL, HDC/VSA, SCPN integration

Read the documentation → Source on GitHub Run demo PyPI · 3.16.0
At a glance

Live from the source repository

Reflected from the project's public GitHub repository at build time — never hand-copied.

Latest release v3.16.0 4 Jul 2026
Last activity 10 Jul 2026 most recent push
Primary language Python
On PyPI 3.16.0 sc-neurocore
Stars 9
edge-aifpgahyper-dimensional-computingneuromorphicneuromorphic-computingpetri-netspyo3quantumrustsimdsnnspiking-neural-networksstochastic-computingverilog
Capabilities

What this studio federates

The verbs, backends, and evidence types the studio publishes through the Hub's capability manifest — the same sealed contract the client-side verifier reads.

Verbs

encodesimulateanalysebenchmarkvalidatecompilesynthesisedeploy

Acceleration backends

numpyrustmojojuliagonumbacupyjaxtorchmpi4pyfpga-rtl

Evidence types

studio.backend-benchmark.v1studio.bitstream-encoding.v1studio.cosim-parity.v1studio.fpga-deployment.v1studio.rtl-compilation.v1studio.sc-inference.v1studio.spike-analysis.v1
123 catalogued capabilities across the studio

By status

  • 89 library-only
  • 24 wired
  • 7 stub
  • 3 feasibility-only

By tier

  • 107 core
  • 16 research

Largest domains

  • 18 Neuromorphic substrates & physical I/O
  • 16 Interop, serving & deployment
  • 11 Network & dynamics
  • 10 Analysis, explainability & profiling
  • 9 SC substrate & arithmetic
  • 9 Plasticity & continual learning
Evidence

Every claim shown at its true boundary

Federated evidence bundles, rendered at the boundary the studio graded them to — never upgraded.

studio.sc-inference.v1
reference-validated level 3 measured

recompute · bit-exact

studio.fpga-deployment.v1
reference-validated level 3 hardware-validated

recompute · bit-exact

Live evidence bundle

Verified in your browser

This RO-Crate is fetched client-side, unpacked, and checked against the evidence contract — the server cannot silently change the boundary.

studio.unknown.v1reference-validated
level 2measured

Download RO-CrateChecking bundle…
Case studies

How this studio is used

Evidence-backed stories that show the studio in practice, with linked evidence bundles and publications.

Featured

Bit-exact benchmark suite for neuromorphic inference

An 8-capability, 70-cell benchmark databank that compares stochastic-computing and neuromorphic kernels across Rust, Mojo, Julia, Go, and Python — every cell emitted as a studio.sc-inference.v1 evidence bundle with claim boundary and exactness class.

Publications

Related publications

Peer-reviewed and whitepaper outputs that cite this studio's evidence bundles.

SC-NeuroCore: Universal Stochastic Computing Framework for Neuromorphic Hardware

5 Jul 2026

Documentation

Read the full docs

Stochastic computing and neuromorphic hardware co-design toolkit. SC-NeuroCore is a research-to-hardware software stack for designing spiking and stochastic neural systems, validating their numerical behaviour, and moving selected models toward FPGA, ASIC, and embedded neuromorphic deployment.

Open the documentation → README on GitHub

The full documentation is maintained in the project's own repository and rendered on its GitHub Pages — this page links to the canonical source rather than duplicating it.

Reflecting anulum/sc-neurocore @ f7eb4b2 · fetched 10 Jul 2026 · sources: projects.json, github-api, pypi, federation.json