Software
Collection
Software (GitHub) datasets I've created
•
4 items
•
Updated
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|---|---|---|---|---|---|
https://github.com/pytorch/pytorch
|
pytorch
|
Tensors and Dynamic neural networks in Python with strong GPU acceleration
|
https://pytorch.org
|
machine-learning
|
machine learning framework
|
https://github.com/vllm-project/vllm
|
vllm
|
A high-throughput and memory-efficient inference and serving engine for LLMs
|
https://docs.vllm.ai
|
inference
|
inference engine
|
https://github.com/ollama/ollama
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ollama
|
Get up and running with OpenAI gpt-oss, DeepSeek-R1, Gemma 3 and other models.
|
https://ollama.com
|
llms
|
inference engine
|
https://github.com/sgl-project/sglang
|
sglang
|
SGLang is a fast serving framework for large language models and vision language models.
|
https://docs.sglang.ai/
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inference
|
inference engine
|
https://github.com/ggml-org/llama.cpp
|
llama.cpp
|
LLM inference in C/C++
| null |
ggml
|
inference engine
|
https://github.com/triton-lang/triton
|
triton
|
Development repository for the Triton language and compiler
|
https://triton-lang.org/
| null |
dsl
|
https://github.com/pytorch/helion
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helion
|
A Python-embedded DSL that makes it easy to write fast, scalable ML kernels with minimal boilerplate.
| null | null |
dsl
|
https://github.com/microsoft/TileIR
|
TileIR
| null | null | null |
dsl
|
https://github.com/tile-ai/tilelang
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tilelang
|
Domain-specific language designed to streamline the development of high-performance GPU/CPU/Accelerators kernels
|
https://tilelang.com/
| null |
dsl
|
https://github.com/NVIDIA/cutlass
|
cutlass
|
CUDA Templates and Python DSLs for High-Performance Linear Algebra
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https://docs.nvidia.com/cutlass/index.html
|
cuda
| null |
https://github.com/tensorflow/tensorflow
|
tensorflow
|
An Open Source Machine Learning Framework for Everyone
|
https://tensorflow.org
|
deep-learning
|
machine learning framework
|
https://github.com/HazyResearch/ThunderKittens
|
ThunderKittens
|
Tile primitives for speedy kernels
| null | null | null |
https://github.com/pytorch/executorch
|
executorch
|
On-device AI across mobile, embedded and edge for PyTorch
|
https://executorch.ai
|
mobile
|
model compiler
|
https://github.com/onnx/onnx
|
onnx
|
Open standard for machine learning interoperability
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https://onnx.ai/
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deep-learning
| null |
https://github.com/ray-project/ray
|
ray
|
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
|
https://ray.io
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deep-learning
| null |
https://github.com/jax-ml/jax
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jax
|
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
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https://docs.jax.dev
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jax
| null |
https://github.com/llvm/llvm-project
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llvm-project
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The LLVM Project is a collection of modular and reusable compiler and toolchain technologies.
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http://llvm.org
| null |
compiler
|
https://github.com/NVIDIA/TensorRT
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TensorRT
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NVIDIA® TensorRT™ is an SDK for high-performance deep learning inference on NVIDIA GPUs. This repository contains the open source components of TensorRT.
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https://developer.nvidia.com/tensorrt
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inference
| null |
https://github.com/pytorch/ao
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ao
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PyTorch native quantization and sparsity for training and inference
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https://pytorch.org/ao/stable/index.html
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quantization
| null |
https://github.com/AMD-AGI/GEAK-agent
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GEAK-agent
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It is an LLM-based AI agent, which can write correct and efficient gpu kernels automatically.
| null | null | null |
https://github.com/block/goose
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goose
|
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
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https://block.github.io/goose/
|
mcp
|
agent
|
https://github.com/codelion/openevolve
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openevolve
|
Open-source implementation of AlphaEvolve
| null |
genetic-algorithm
| null |
https://github.com/volcengine/verl
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verl
|
verl: Volcano Engine Reinforcement Learning for LLMs
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https://verl.readthedocs.io/en/latest/index.html
| null | null |
https://github.com/huggingface/peft
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peft
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🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
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https://huggingface.co/docs/peft
|
lora
| null |
https://github.com/Dao-AILab/quack
|
quack
|
A Quirky Assortment of CuTe Kernels
| null | null |
kernels
|
https://github.com/AMDResearch/intelliperf
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intelliperf
|
Automated bottleneck detection and solution orchestration
| null |
performance
| null |
https://github.com/letta-ai/letta
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letta
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Letta is the platform for building stateful agents: open AI with advanced memory that can learn and self-improve over time.
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https://docs.letta.com/
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ai-agents
| null |
https://github.com/lastmile-ai/mcp-agent
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mcp-agent
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Build effective agents using Model Context Protocol and simple workflow patterns
| null |
ai-agents
| null |
https://github.com/modular/modular
|
modular
|
The Modular Platform (includes MAX & Mojo)
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https://docs.modular.com/
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mojo
| null |
https://github.com/ScalingIntelligence/KernelBench
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KernelBench
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KernelBench: Can LLMs Write GPU Kernels? - Benchmark with Torch -> CUDA problems
|
https://scalingintelligence.stanford.edu/blogs/kernelbench/
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benchmark
|
benchmark
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https://github.com/thunlp/TritonBench
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TritonBench
|
TritonBench: Benchmarking Large Language Model Capabilities for Generating Triton Operators
| null | null |
benchmark
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https://github.com/flashinfer-ai/flashinfer-bench
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flashinfer-bench
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Building the Virtuous Cycle for AI-driven LLM Systems
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https://bench.flashinfer.ai
| null |
benchmark
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https://github.com/laude-institute/terminal-bench
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terminal-bench
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A benchmark for LLMs on complicated tasks in the terminal
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https://www.tbench.ai
| null |
benchmark
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https://github.com/SWE-bench/SWE-bench
|
SWE-bench
|
SWE-bench: Can Language Models Resolve Real-world Github Issues?
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https://www.swebench.com
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benchmark
|
benchmark
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https://github.com/gpu-mode/reference-kernels
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reference-kernels
|
Official Problem Sets / Reference Kernels for the GPU MODE Leaderboard!
|
https://gpumode.com
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gpu
|
kernels
|
https://github.com/linkedin/Liger-Kernel
|
Liger-Kernel
|
Efficient Triton Kernels for LLM Training
|
https://openreview.net/pdf?id=36SjAIT42G
|
triton
|
kernels
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https://github.com/huggingface/kernels
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kernels
|
Load compute kernels from the Hub
| null | null |
kernels
|
https://github.com/huggingface/kernels-community
|
kernels-community
|
Kernel sources for https://huggingface.co/kernels-community
| null | null |
kernels
|
https://github.com/unslothai/unsloth
|
unsloth
|
Fine-tuning & Reinforcement Learning for LLMs. 🦥 Train OpenAI gpt-oss, DeepSeek-R1, Qwen3, Gemma 3, TTS 2x faster with 70% less VRAM.
|
https://docs.unsloth.ai/
|
unsloth
| null |
https://github.com/jupyterlab/jupyterlab
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jupyterlab
|
JupyterLab computational environment.
|
https://jupyterlab.readthedocs.io/
|
jupyter
|
ui
|
https://github.com/ROCm/rocm-systems
|
rocm-systems
|
super repo for rocm systems projects
| null | null | null |
https://github.com/ROCm/hip
|
hip
|
HIP: C++ Heterogeneous-Compute Interface for Portability
|
https://rocmdocs.amd.com/projects/HIP/
|
hip
| null |
https://github.com/ROCm/ROCm
|
ROCm
|
AMD ROCm™ Software - GitHub Home
|
https://rocm.docs.amd.com
|
documentation
| null |
https://github.com/ROCm/omnitrace
|
omnitrace
|
Omnitrace: Application Profiling, Tracing, and Analysis
|
https://rocm.docs.amd.com/projects/omnitrace/en/docs-6.2.4/
|
performance-analysis
| null |
https://github.com/vosen/ZLUDA
|
ZLUDA
|
CUDA on non-NVIDIA GPUs
|
https://vosen.github.io/ZLUDA/
|
cuda
| null |
https://github.com/vtsynergy/CU2CL
|
CU2CL
|
A prototype CUDA-to-OpenCL source-to-source translator, built on the Clang compiler framework
|
http://chrec.cs.vt.edu/cu2cl
| null | null |
https://github.com/pocl/pocl
|
pocl
|
pocl - Portable Computing Language
|
https://portablecl.org
|
opencl
| null |
https://github.com/cwpearson/cupti
|
cupti
|
Profile how CUDA applications create and modify data in memory.
| null | null |
profiler
|
https://github.com/LLNL/hatchet
|
hatchet
|
Graph-indexed Pandas DataFrames for analyzing hierarchical performance data
|
https://llnl-hatchet.readthedocs.io
|
performance
|
profiler
|
https://github.com/toyaix/triton-runner
|
triton-runner
|
Multi-Level Triton Runner supporting Python, IR, PTX, and cubin.
|
https://triton-runner.org
|
triton
| null |
https://github.com/ByteDance-Seed/Triton-distributed
|
Triton-distributed
|
Distributed Compiler based on Triton for Parallel Systems
|
https://triton-distributed.readthedocs.io/en/latest/
| null |
model compiler
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https://github.com/meta-pytorch/tritonparse
|
tritonparse
|
TritonParse: A Compiler Tracer, Visualizer, and Reproducer for Triton Kernels
|
https://meta-pytorch.org/tritonparse/
|
triton
| null |
https://github.com/numpy/numpy
|
numpy
|
The fundamental package for scientific computing with Python.
|
https://numpy.org
|
python
|
python library
|
https://github.com/scipy/scipy
|
scipy
|
SciPy library main repository
|
https://scipy.org
|
python
|
python library
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https://github.com/numba/numba
|
numba
|
NumPy aware dynamic Python compiler using LLVM
|
https://numba.pydata.org/
|
compiler
| null |
https://github.com/Lightning-AI/lightning-thunder
|
lightning-thunder
|
PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.
| null | null | null |
https://github.com/pytorch/torchdynamo
|
torchdynamo
|
A Python-level JIT compiler designed to make unmodified PyTorch programs faster.
| null | null | null |
https://github.com/NVIDIA/nccl
|
nccl
|
Optimized primitives for collective multi-GPU communication
|
https://docs.nvidia.com/deeplearning/nccl/user-guide/docs/index.html
|
cuda
| null |
https://github.com/ai-dynamo/nixl
|
nixl
|
NVIDIA Inference Xfer Library (NIXL)
| null | null | null |
https://github.com/guandeh17/Self-Forcing
|
Self-Forcing
|
Official codebase for "Self Forcing: Bridging Training and Inference in Autoregressive Video Diffusion" (NeurIPS 2025 Spotlight)
| null | null | null |
https://github.com/cumulo-autumn/StreamDiffusion
|
StreamDiffusion
|
StreamDiffusion: A Pipeline-Level Solution for Real-Time Interactive Generation
| null | null | null |
https://github.com/comfyanonymous/ComfyUI
|
ComfyUI
|
The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface.
|
https://www.comfy.org/
|
stable-diffusion
| null |
https://github.com/Jeff-LiangF/streamv2v
|
streamv2v
|
Official Pytorch implementation of StreamV2V.
|
https://jeff-liangf.github.io/projects/streamv2v/
| null | null |
https://github.com/deepspeedai/DeepSpeed
|
DeepSpeed
|
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
|
https://www.deepspeed.ai/
|
gpu
| null |
https://github.com/triton-inference-server/server
|
server
|
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
|
https://docs.nvidia.com/deeplearning/triton-inference-server/user-guide/docs/index.html
|
inference
| null |
https://github.com/elastic/elasticsearch
|
elasticsearch
|
Free and Open Source, Distributed, RESTful Search Engine
|
https://www.elastic.co/products/elasticsearch
|
search-engine
|
search engine
|
https://github.com/kubernetes/kubernetes
|
kubernetes
|
Production-Grade Container Scheduling and Management
|
https://kubernetes.io
|
containers
| null |
https://github.com/modelcontextprotocol/modelcontextprotocol
|
modelcontextprotocol
|
Specification and documentation for the Model Context Protocol
|
https://modelcontextprotocol.io
| null | null |
https://github.com/milvus-io/milvus
|
milvus
|
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
|
https://milvus.io
|
vector-search
|
vector databse
|
https://github.com/gaoj0017/RaBitQ
|
RaBitQ
|
[SIGMOD 2024] RaBitQ: Quantizing High-Dimensional Vectors with a Theoretical Error Bound for Approximate Nearest Neighbor Search
|
https://github.com/VectorDB-NTU/RaBitQ-Library
|
nearest-neighbor-search
| null |
https://github.com/Airtable/airtable.js
|
airtable.js
|
Airtable javascript client
| null | null | null |
https://github.com/mistralai/mistral-inference
|
mistral-inference
|
Official inference library for Mistral models
|
https://mistral.ai/
|
llm-inference
|
inference engine
|
https://github.com/dstackai/dstack
|
dstack
|
dstack is an open-source control plane for running development, training, and inference jobs on GPUs—across hyperscalers, neoclouds, or on-prem.
|
https://dstack.ai
|
orchestration
| null |
https://github.com/sandialabs/torchdendrite
|
torchdendrite
|
Dendrites for PyTorch and SNNTorch neural networks
| null |
scr-3078
|
machine learning framework
|
https://github.com/pytorch/torchtitan
|
torchtitan
|
A PyTorch native platform for training generative AI models
| null | null | null |
https://github.com/NVIDIA/cudnn-frontend
|
cudnn-frontend
|
cudnn_frontend provides a c++ wrapper for the cudnn backend API and samples on how to use it
| null | null | null |
https://github.com/pytorch/ort
|
ort
|
Accelerate PyTorch models with ONNX Runtime
| null | null | null |
https://github.com/sgl-project/ome
|
ome
|
OME is a Kubernetes operator for enterprise-grade management and serving of Large Language Models (LLMs)
|
http://docs.sglang.ai/ome/
|
k8s
| null |
https://github.com/aws-neuron/neuronx-distributed-inference
|
neuronx-distributed-inference
| null | null | null |
inference engine
|
https://github.com/meta-pytorch/monarch
|
monarch
|
PyTorch Single Controller
|
https://meta-pytorch.org/monarch
| null | null |
https://github.com/LMCache/LMCache
|
LMCache
|
Supercharge Your LLM with the Fastest KV Cache Layer
|
https://lmcache.ai/
|
inference
| null |
https://github.com/linux-rdma/rdma-core
|
rdma-core
|
RDMA core userspace libraries and daemons
| null |
linux-kernel
| null |
https://github.com/Cambridge-ICCS/FTorch
|
FTorch
|
A library for directly calling PyTorch ML models from Fortran.
|
https://cambridge-iccs.github.io/FTorch/
|
deep-learning
| null |
https://github.com/facebook/hhvm
|
hhvm
|
A virtual machine for executing programs written in Hack.
|
https://hhvm.com
|
hack
| null |
https://github.com/apache/spark
|
spark
|
Apache Spark - A unified analytics engine for large-scale data processing
|
https://spark.apache.org/
|
big-data
| null |
https://github.com/ROCm/composable_kernel
|
composable_kernel
|
Composable Kernel: Performance Portable Programming Model for Machine Learning Tensor Operators
|
https://rocm.docs.amd.com/projects/composable_kernel/en/latest/
| null | null |
https://github.com/ROCm/aiter
|
aiter
|
AI Tensor Engine for ROCm
| null | null | null |
https://github.com/AMD-AGI/torchtitan
|
torchtitan
|
A PyTorch native platform for training generative AI models
| null | null | null |
https://github.com/AMD-AGI/hipBLASLt
|
hipBLASLt
|
hipBLASLt is a library that provides general matrix-matrix operations with a flexible API and extends functionalities beyond a traditional BLAS library
|
https://rocm.docs.amd.com/projects/hipBLASLt/en/latest/index.html
| null | null |
https://github.com/AMD-AGI/rocm-torchtitan
|
rocm-torchtitan
| null | null | null | null |
https://github.com/HazyResearch/Megakernels
|
Megakernels
|
kernels, of the mega variety
| null | null | null |
https://github.com/opencv/opencv
|
opencv
|
Open Source Computer Vision Library
|
https://opencv.org
|
image-processing
| null |
https://github.com/Lightning-AI/lightning-thunder
|
lightning-thunder
|
PyTorch compiler that accelerates training and inference. Get built-in optimizations for performance, memory, parallelism, and easily write your own.
| null | null | null |
https://github.com/tracel-ai/burn
|
burn
|
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
|
https://burn.dev
|
machine-learning
| null |
https://github.com/OSC/ondemand
|
ondemand
|
Supercomputing. Seamlessly. Open, Interactive HPC Via the Web
|
https://openondemand.org/
|
hpc
| null |
https://github.com/flashinfer-ai/flashinfer
|
flashinfer
|
FlashInfer: Kernel Library for LLM Serving
|
https://flashinfer.ai
|
attention
| null |
https://github.com/AutomataLab/cuJSON
|
cuJSON
|
cuJSON: A Highly Parallel JSON Parser for GPUs
| null | null | null |
https://github.com/Netflix/metaflow
|
metaflow
|
Build, Manage and Deploy AI/ML Systems
|
https://metaflow.org
|
machine-learning
| null |
https://github.com/harmonic-ai/IMO2025
|
IMO2025
| null | null | null | null |
https://github.com/leanprover/lean4
|
lean4
|
Lean 4 programming language and theorem prover
|
https://lean-lang.org
|
lean
| null |
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