neo4reo

BRISKI

BRISKI ( Barrel RISC-V for Kilo-core Implementations ) is a fast and compact RISC-V barrel processor core that emphasize high throughput and compute density to increase the amount of cores in many-core design without sacrificing performance.

ASIC-Design-Roadmap

The journey of designing an ASIC (application specific integrated circuit) is long and involves a number of major steps – moving from a concept to specification to tape-outs. Although the end product is typically quite small (measured in nanometers), this long journey is interesting and filled with many engineering challenges.

awesome-chatgpt

Curated list of awesome tools, demos, docs for ChatGPT and GPT-3

awesome-list

Cybersecurity oriented awesome list

awesome-neuro-symbolic-ai

A curated list of awesome Neuro-Symbolic AI software frameworks

awesome-tnns

awesome-topological-deep-learning

A curated list of topological deep learning (TDL) resources and links.

Cachet

📛 An open source status page system for everyone.

chipyard

An Agile RISC-V SoC Design Framework with in-order cores, out-of-order cores, accelerators, and more

engineering-blogs-1

A curated list of engineering blogs

f4pga

FOSS Flow For FPGA

FABulous

Fabric generator and CAD tools

finn-examples

Dataflow QNN inference accelerator examples on FPGAs

H.I.V.E

H.I.V.E is an automated OSINT (Open Source Intelligence) multi-tool that enables efficient data gathering from various sources through the utilization of a single, unified platform.

hexapod

HypergraphPartitioning

Hypergraph Partitioning: benchmarks, evaluators, best known solutions and codes

kahypar

KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.

kianRiscV

RISC-V Linux SoC, marchID: 0x2b

mase

Machine-Learning Accelerator System Exploration Tools

mm-cot

Official implementation for "Multimodal Chain-of-Thought Reasoning in Language Models" (stay tuned and more will be updated)

NSIL

Code and technical appendix for the paper "Neuro-Symbolic Learning of Answer Set Programs from Raw Data".

persuasive_jailbreaker

Persuasive Jailbreaker: we can persuade LLMs to jailbreak them!

reading-with-intent

runhouse

Programmable 🐍 remote compute 🔋 and data 📂 across environments 💻 and users 👩‍💻

symbolicai

Compositional Differentiable Programming Library

system-design-101

Explain complex systems using visuals and simple terms. Help you prepare for system design interviews.

techniques

Techniques for deep learning with satellite & aerial imagery

text-generation-webui

A gradio web UI for running Large Language Models like GPT-J 6B, OPT, GALACTICA, LLaMA, and Pygmalion.

tinyengine

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory

TopoModelX

Higher-Order Deep Models For Python