Hpc projects on GitHub

High performance computing languages and distributed training.

As of October 17, 2026, the most-starred Hpc projects on GitHub are julia (49.2K stars), ColossalAI (41.4K stars) and llm.c (31.2K stars). GitHub.Locker tracks 9 Hpc repositories with 165.1K stars combined. The fastest-growing on October 16 was llm.c, with +9 stars in a day.

9Projects

165.1KStars in total

+30Stars in a day

Browse in the catalog →github.com/topics/hpc ↗

Hot right now

Most stars gained in a day · Oct 16

llm.c

karpathy/llm.c · ★ 31.2K

llm.c is Karpathy's project for training large language models in raw C and CUDA, with no dependency on 245MB of PyTorch or 107MB of cPython. It currently focuses on pretraining GPT-2 and GPT-3-scale models, with train_gpt2.cu as the main CUDA training path.

julia

JuliaLang/julia · ★ 49.2K

Julia is a high-level, high-performance dynamic programming language built for technical and scientific computing, numerical analysis, and machine learning.

ml-engineering

stas00/ml-engineering · ★ 19.5K

An open book on machine learning engineering: methodologies, tools and step-by-step instructions for training, fine-tuning and running inference on large language models and multi-modal (VLM) models, written by the engineer who led the BLOOM-176B training.

OpenCourant

OpenCourant/OpenCourant · ★ 374

OpenCourant is an open-source build of OpenRadioss, an explicit finite element solver used to simulate highly nonlinear dynamic events like crashes, impacts, and explosions.

The all-time top

9 projects · by stars

#1 · JuliaLang/julia
julia
Julia is a high-level, high-performance dynamic programming language built for technical and scientific computing, numerical analysis, and machine learning.
49.2K
#2 · hpcaitech/ColossalAI
ColossalAI
Colossal-AI is an open-source system for training and running large AI models more cheaply, faster and with less hardware, by providing a toolbox of parallelism and memory-optimization techniques.
41.4K
#3 · karpathy/llm.c
llm.c
llm.c is Karpathy's project for training large language models in raw C and CUDA, with no dependency on 245MB of PyTorch or 107MB of cPython. It currently focuses on pretraining GPT-2 and GPT-3-scale models, with train_gpt2.cu as the main CUDA training path.
31.2K

4
ml-engineering
19.5Kstas00/ml-engineering · Python
An open book on machine learning engineering: methodologies, tools and step-by-step instructions for training, fine-tuning and running inference on large language models and multi-modal (VLM) models, written by the engineer who led the BLOOM-176B training.
5
taskflow
12.2Ktaskflow/taskflow · C++
Taskflow is a C++ library that helps you write high-performance task-parallel programs with high programming productivity, letting you build and run graphs of dependent tasks across CPU threads and GPUs.
6
DeepEP
10.3Kdeepseek-ai/DeepEP · Cuda
DeepEP is a high-performance communication library for MoE (mixture-of-experts) models, providing fast all-to-all GPU kernels for expert-parallel dispatch and combine operations used in ML training and inference.
7
enterprise-system-design
642DrHazemAli/enterprise-system-design
This is a source-grounded engineering course and architectural reference for designing enterprise systems that survive real traffic, partial failure, security review, and changing requirements, covering distributed systems, AI workloads, cybersecurity, reliability, cloud, HPC, and edge infrastructure built on Azure.
8
OpenCourant
374OpenCourant/OpenCourant · Fortran
OpenCourant is an open-source build of OpenRadioss, an explicit finite element solver used to simulate highly nonlinear dynamic events like crashes, impacts, and explosions.
9
DeepEP-Ascend
259deepseek-ai/DeepEP-Ascend · C++
DeepEP-Ascend is a high-performance communication library for machine learning training and inference on Huawei Ascend NPUs, providing expert-parallel all-to-all operations for MoE dispatch and combine.