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aHappend/README.md

Hi, I'm Sufeng Guo

Undergraduate at Nanjing University (VLSI Design & System Integration), graduating in 2027.

I work on AI accelerator architecture, hardware-software co-design, and evidence-driven RTL engineering — connecting workload mapping and scheduling with persistent AI engineering systems.

Personal website · Vulcan portfolio · Public RTL Showcase

Education & Experience

  • Nanjing University — VLSI Design & System Integration
  • Campus locations: Nanjing (Year 1); Suzhou (Years 2–4)
  • Expected graduation: 2027
Period Experience
Sep–Dec 2026 Microsoft Research Asia (MSRA) — Research Intern, Systems Research Group, Beijing. Group website ↗
Jan–May 2027 Nanyang Technological University (NTU), Singapore — Government-Sponsored Visiting Undergraduate. Program website ↗

Research & Engineering

Methods: DNN mapping, inter-layer scheduling, NoC and memory-system data movement. I contribute to HyperCut and maintain a Crane reproduction lab.

Argus — team contributions

With Argus AI Team, I contribute to Argus / Microsoft · original project, a persistent multi-agent runtime, its chip-design vertical, interfaces and evidence-driven evaluation.

Vulcan — independent project

Vulcan is an independent AI-native hardware engineering project, not part of Argus AI Team. It connects scoped RTL implementation, verification, independent review and reproducible delivery. Its public portfolio includes ANVIL E/Q, RIVET/BILLET, SABLE and ten component IPs.

AI accelerator families

Family Focus and public evidence
ACE-2 / ACE-3 MP W4A8 persistent RTL dialogue and native AWQ W4A16 research. ACE-2 has accepted two-turn, four-token-per-turn simulation with 24 retained K/V layers and zero mismatches. ACE-3 has verified G128 projection and bounded FP16-boundary blocks; full-regression, full-model and hardware acceptance remain open.
ANVIL — Q (Quantized LLMs) / E (Multimodal Embeddings) Synthesizable 100 MHz+ SystemVerilog accelerators verified on Intel Arria 10 GX PCIe Gen3x8 HIL with dual-track IEEE/ACM reports. Anvil-Q1 (Qwen2.5-0.5B-Instruct-AWQ, 108.48 MHz) & Anvil-Q2 (Qwen2.5-1.5B-Instruct-AWQ, 1/2/4-bank + INT8 KV-Cache, 101.39 MHz); Anvil-E1/E2/E3 (google/embeddinggemma-2 Text, Vision+Text & Audio+Vision+Text Trimodal, 107.31–111.63 MHz).

ACE organization mirrors: ACE-2 · ACE-3.

Reusable RTL families

RIVET & BILLET are presented together, with generations kept inside their repositories:

Family Product lines
RIVET A — AES/GCM, key/context management and DMA · H — SHA/HMAC and saved hashing contexts
BILLET T — FFT/IFFT and spectral analysis · F — programmable FIR/IIR filtering

All 12 generations across RIVET-A (A1..A3), RIVET-H (H1..H3), BILLET-T (T1..T3), and BILLET-F (F1..F3) achieve 100 MHz+ Quartus 17.1 STA timing closure (107.47–210.22 MHz) and physical Intel Arria 10 GX PCIe Gen3x8 HIL verification, accompanied by monolingual dual-track academic and developer PDF reports. SABLE provides 4-stream reliable message transport, and Vulcan Showcase indexes all 17 verified chips and 10 reusable SystemVerilog IP cores.

Hardware foundations

64-Point FFT: folded streaming SDF, Q1.15, XSim/Python co-verification and routed Virtex-7 results. Two-Stage CMOS Op-Amp: TSMC 0.18 μm Miller compensation with Spectre AC/DC/transient verification.

Publications

External Links

Tools

Python C / basic C++ TypeScript SystemVerilog Verilog React Linux

Contact

Popular repositories Loading

  1. ace-2 ace-2 Public

    evidence-first Qwen2.5-0.5B W4A8 accelerator: certified two-token RTL integration, SKY130 100 MHz, and Fresh-L2-accepted V8 host-trust recovery.

    SystemVerilog 1 1

  2. 64-point-fft-hardware 64-point-fft-hardware Public

    Resource-efficient 64-point radix-2 DIT FFT in SystemVerilog: folded streaming SDF RTL, Q1.15 fixed-point arithmetic, Vivado/XSim simulation, Python/NumPy co-verification, and Virtex-7 implementati…

    C

  3. SET-NN-Mapping-Scheduling SET-NN-Mapping-Scheduling Public

    Exploring the impact of neural network task granularity on mapping and scheduling efficiency on multi-core NoC architectures based on the SET framework.

  4. Crane Crane Public

    Independent Python reproduction of Crane (MICRO 2025): real network DAGs, checked ScT/MeT scheduling, native SET core profiles, reproducible experiments and an offline interactive demo.

    Python

  5. two-stage-cmos-op-amp two-stage-cmos-op-amp Public

    Two-stage CMOS operational amplifier designed in TSMC 0.18 um technology, with Spectre AC/DC/transient verification, Miller compensation, and analysis of gain, bandwidth, phase margin, slew rate, o…

    TeX

  6. aHappend aHappend Public

    Sufeng Guo - personal profile