mananshah99

mananshah99's Stars

• golang/go

  The Go programming language

  Language:Go125k3.4k64.9k17.8k

• kubernetes/kubernetes

  Production-Grade Container Scheduling and Management

  Language:Go112k3.2k46.4k40k

• mingrammer/diagrams

  :art: Diagram as Code for prototyping cloud system architectures

  Language:Python40k4065132.6k

• kilimchoi/engineering-blogs

  A curated list of engineering blogs

  Language:Ruby32k1k951.7k

• karpathy/llm.c

  LLM training in simple, raw C/CUDA

  Language:Cuda24.9k2521412.8k

• simdjson/simdjson

  Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks

  Language:C++19.5k2428491k

• ahmetb/kubectx

  Faster way to switch between clusters and namespaces in kubectl

  Language:Go18k1342331.3k

• benfred/py-spy

  Sampling profiler for Python programs

  Language:Rust13.1k110375439

• adam-maj/tiny-gpu

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

  Language:SystemVerilog7.3k6924553

• google/gemma.cpp

  lightweight, standalone C++ inference engine for Google's Gemma models.

  Language:C++6.1k4188520

• ReagentX/imessage-exporter

  Export iMessage data + run iMessage Diagnostics

  Language:Rust3.3k27160141

• axboe/liburing

  Library providing helpers for the Linux kernel io_uring support

  Language:C2.9k107799411

• unitycatalog/unitycatalog

  Open, Multi-modal Catalog for Data & AI

  Language:Java2.6k52280416

• unum-cloud/ucall

  Web Serving and Remote Procedure Calls at 50x lower latency and 70x higher bandwidth than FastAPI, implementing JSON-RPC & REST over io_uring ☎️

  Language:C1.2k193044

• ianlancetaylor/libbacktrace

  A C library that may be linked into a C/C++ program to produce symbolic backtraces

  Language:C1k3697234

• Liu-xiandong/How_to_optimize_in_GPU

  This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several basic kernel optimizations, including: elementwise, reduce, sgemv, sgemm, etc. The performance of these kernels is basically at or near the theoretical limit.

  Language:Cuda8761315138

• roma-glushko/awesome-distributed-system-projects

  🚀 List of distributed system projects for inspiration and learning to build distributed services from real world examples

  7688272

• PABannier/bark.cpp

  Suno AI's Bark model in C/C++ for fast text-to-speech generation

  Language:C++756399162

• baidu-research/baidu-allreduce

  Language:Cuda572697114

• BobMcDear/attorch

  A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.

  Language:Python50211726

• mattgodbolt/pt-three-ways

  Path tracing, done three ways

  Language:C++19317320

• siboehm/ShallowSpeed

  Small scale distributed training of sequential deep learning models, built on Numpy and MPI.

  Language:Python111304

• eschluntz/PytorchBridge

  Designing bridge trusses with Pytorch autograd

  Language:Jupyter Notebook61314

• jkomoros/card-web

  The web app behind thecompendium.cards

  Language:TypeScript5666448

• AIWintermuteAI/whispercpp

  Pybind11 bindings for Whisper.cpp

  Language:C++48439

• okuvshynov/llama_duo

  asynchronous/distributed speculative evaluation for llama3

  Language:C++37210

• srush/anynp

  Proof-of-concept of global switching between numpy/jax/pytorch in a library.

  Language:Python1820

• evelynmitchell/shouldersOfGiants.rs

  I have no idea what I'm doing , but llm.c in rust

  Language:Python12200

• jpetazzo/color

  Language:Go11302

• Tigerrr07/How_to_optimize_in_GPU

  This is a series of GPU optimization topics. Here we will introduce how to optimize the CUDA kernel in detail. I will introduce several basic kernel optimizations, including: elementwise, reduce, sgemv, sgemm, etc. The performance of these kernels is basically at or near the theoretical limit.

  Language:Cuda1000