A faster, leaner fork of the superpowers workflow for Claude Code: one approval gate, parallel waves, routed models. 3.9x faster in benchmark at equal quality.
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DeepSeek-V4.1-Flash-1017 EXL3 2.9bpw on 2x NVIDIA DGX Spark (GB10) with TensorFold: 2.1-2.3x the vLLM kit's decode speed.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Making large AI models cheaper, faster and more accessible
:zap: A Fast, Extensible Progress Bar for Python and CLI
A high-performance, zero-overhead, extensible Python compiler with built-in NumPy support
A hyperparameter optimization framework
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
Parallel computing with task scheduling
NumPy aware dynamic Python compiler using LLVM
An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries
AI๊ฐ ์ด ํ๊ธ์ ์ฌ๋ ๊ธ์ฒ๋ผ ์ค๋ฌธํ๋ Claude ์คํฌ โ Korean AI-text humanizer: detects and rewrites translationese, mechanical parallelism, and 71 other AI tells
๐A curated list of Awesome LLM/VLM Inference Papers with Codes: Flash-Attention, Paged-Attention, WINT8/4, Parallelism, etc.๐
Computing with Python functions.
Switch between multiple Claude Code accounts, with automatic rate-limit rotation, usage dashboard, and parallel sessions
A high-performance distributed training framework for Reinforcement Learning
Minimalistic large language model 3D-parallelism training
Long Video Gen / World Model / World Action Model (Embodied) Infrastructure
xDiT: A Scalable Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism
A nano replica of Jev: parallel decisions, dynamic candidates, and an end-to-end training pipeline.
cuTile is a programming model for writing parallel kernels for NVIDIA GPUs
Agent skill for Codex, Claude Code, and OpenClaw that translates entire books (PDF/DOCX/EPUB) into any language using parallel subagents.
GenAI Processors is a lightweight Python library that enables efficient, parallel content processing.
A pipeline parallel training script for diffusion models.
AI-native agent harness for coding workflows by python: multi-model LLM orchestration, stateful sessions, tool governance, traceable delivery, and provider routing for GPT, Claude, DeepSeek, Qwen, Kimi, GLM, and MiniMax.
Extensible, parallel implementations of t-SNE
A Python stream processing engine modeled after Yahoo! Pipes
Flask-based web front-end for monitoring RQ queues
parallel graph management and execution in heterogeneous computing
turns your codebase into an autoresearch loop โ discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.
PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.
LLM-compiled knowledge bases for any AI agent. Parallel multi-agent research, thesis-driven investigation, source ingestion, wiki compilation, querying, and artifact generation.
Curated directory of terminal-native AI coding agents and the harnesses that orchestrate them. Covers open-source tools (Pi, OpenCode, Aider, Goose), platform agents (Claude Code, Codex, Gemini CLI), parallel runners, autonomous loops, and agent infrastructure.
The open-source governance layer for AI agents: write the rules declaratively, Bernstein enforces them and produces the verifiable, replayable record. Free, Apache-2.0. https://bernstein.run
A PyTorch-native inference engine with cache, parallelism, quantization and cpu offload for DiTs.
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
A scalable, agentic-first, and HuggingFace-native RL framework for research (9k lines).
MoonEP: A Perfectly Balanced Expert Parallelism Library via Dynamic Redundant Experts
OpenCL integration for Python, plus shiny features
YaFSDP: Yet another Fully Sharded Data Parallel
Python bindings for MPI
AWS ParallelCluster is an AWS supported Open Source cluster management tool to deploy and manage HPC clusters in the AWS cloud.
Examples for https://github.com/optuna/optuna
[EMNLP 2026] MobileGym: A Verifiable and Highly Parallel Simulation Platform for Mobile GUI Agent Research ยท ๆต่งๅจ้่ฟ่ก็ๅฎๅๆจกๆๅจ ยท Browser-hosted Android Simulator ยท Verifiable Evaluation ยท Scalable Online RL Training
Halo is an open-source framework built by White Circle for training large language and multimodal models
Haven โ MANET IP Mesh Radio toolkit
Benchmark of federated learning. Dedicated to the community. ๐ค
FiPy is a Finite Volume PDE solver written in Python
Parsl - a Python parallel scripting library
Sandboxed code execution for AI agents, locally or on the cloud. Massively parallel, easy to extend. Powering SWE-agent and more.
A Python library for running thousands of MuJoCo simulations in parallel on CPU
DaCe - Data Centric Parallel Programming
Claude Code plugin for Elixir/Phoenix/LiveView โ 26 specialist agents, Iron Laws enforcement, and Tidewave MCP integration. Plan features with parallel research agents, execute with automatic verification, review with 4-agent parallel audits, and capture learnings as reusable knowledge.
Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.
Zero-copy MPI communication of JAX arrays, for turbo-charged HPC applications in Python :zap:
CLI-first orchestration for AI coding agents: run selected agents and models in parallel, compare raw answers, and coordinate review or implementation workflows.
A unified, torch-native training framework for MTP and block-parallel speculative decoding.
Established strong JEV based natural language to SQL performance and well-covered semantic operators for PostgreSQL(PG) with optimized cost and latency. Reusable evidence, with native execution, parallel plans and explainable embeddings in development preview.