jingairpi

jingairpi's Stars

• KellerJordan/modded-nanogpt

  NanoGPT (124M) quality in 2.67B tokens

  Language:Python71540

• AI-Hypercomputer/gpu-recipes

  Recipes for reproducing training and serving benchmarks for large machine learning models using GPUs on Google Cloud.

  Language:Python9

• nicolaka/netshoot

  a Docker + Kubernetes network trouble-shooting swiss-army container

  Language:Shell8.6k965

• jax-ml/jax

  Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

  Language:Python30.3k2.8k

• SzymonOzog/GPU_Programming

  Language:Python171

• apache/yunikorn-core

  Apache YuniKorn Core

  Language:Go839231

• openucx/ucx

  Unified Communication X (mailing list - https://elist.ornl.gov/mailman/listinfo/ucx-group)

  Language:C1.1k424

• magicproduct/hash-hop

  Long context evaluation for large language models

  Language:Python18315

• OpenAutoCoder/Agentless

  Agentless🐱: an agentless approach to automatically solve software development problems

  Language:Python69183

• vllm-project/vllm

  A high-throughput and memory-efficient inference and serving engine for LLMs

  Language:Python28.8k4.3k

• halanelson/Essential-Math-For-AI

  This repository contains the supplementary material associated with my book: Essential Math for AI published by O'Reilly Media

  Language:Jupyter Notebook30170

• gpu-mode/lectures

  Material for gpu-mode lectures

  Language:Jupyter Notebook2.8k272

• imbue-ai/cluster-health

  Language:Python26135

• amjadmajid/BabyTorch

  BabyTorch is a minimalist deep-learning framework with a similar API to PyTorch. This minimalist design encourages learners explore and understand the underlying algorithms and mechanics of deep learning processes. It is design such that when learners are ready to switch to PyTorch they only need to remove the word `baby`.

  Language:Python27

• codecrafters-io/build-your-own-x

  Master programming by recreating your favorite technologies from scratch.

  Language:Markdown305k28.6k

• google/neper

  neper is a Linux networking performance tool.

  Language:C29272

• bbycroft/llm-viz

  3D Visualization of an GPT-style LLM

  Language:TypeScript3.9k428

• microsoft/AI-For-Beginners

  12 Weeks, 24 Lessons, AI for All!

  Language:Jupyter Notebook34.5k5.8k

• naklecha/llama3-from-scratch

  llama3 implementation one matrix multiplication at a time

  Language:Jupyter Notebook13.6k1.1k

• adam-maj/deep-learning

  A deep-dive on the entire history of deep-learning

  Language:Jupyter Notebook1k81

• adam-maj/tiny-gpu

  A minimal GPU design in Verilog to learn how GPUs work from the ground up

  Language:SystemVerilog7k526

• ray-project/kuberay

  A toolkit to run Ray applications on Kubernetes

  Language:Go1.2k391

• minio/minio

  MinIO is a high-performance, S3 compatible object store, open sourced under GNU AGPLv3 license.

  Language:Go47.5k5.5k

• 3b1b/videos

  Code for the manim-generated scenes used in 3blue1brown videos

  Language:Python6.9k1.7k

• ibm-granite/granite-code-models

  Granite Code Models: A Family of Open Foundation Models for Code Intelligence

  1.1k74

• Mozilla-Ocho/llamafile

  Distribute and run LLMs with a single file.

  Language:C++19.9k999

• mit-han-lab/qserve

  QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving

  Language:Python41920

• rauhul/ece408

  Applied Parallel Programming UIUC FA 2017

  Language:C2917

• facebookincubator/dynolog

  Dynolog is a telemetry daemon for performance monitoring and tracing. It exports metrics from different components in the system like the linux kernel, CPU, disks, Intel PT, GPUs etc. Dynolog also integrates with pytorch and can trigger traces for distributed training applications.

  Language:C++26239

• meta-llama/llama3

  The official Meta Llama 3 GitHub site

  Language:Python26.7k3k