anneouyang

ChatGPT

Reverse engineered ChatGPT API

taichi

Productive, portable, and performant GPU programming in Python.

wenyan

文言文編程語言 A programming language for the ancient Chinese.

PyMySQL

MySQL client library for Python

flexboxfroggy

A game for learning CSS flexbox 🐸

composer

Supercharge Your Model Training

goleak

Goroutine leak detector

openmlsys-zh

《Machine Learning Systems: Design and Implementation》- Chinese Version

alpa

Training and serving large-scale neural networks with auto parallelization.

SciMLBook

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

koila

Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.

opencbdc-tx

A transaction processor for a hypothetical, general-purpose, central bank digital currency

tinyengine

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory

Dagger.jl

A framework for out-of-core and parallel execution

mlc-zh

torchprofile

A general and accurate MACs / FLOPs profiler for PyTorch models

mlc-en

timeloop

Timeloop performs modeling, mapping and code-generation for tensor algebra workloads on various accelerator architectures.

torch-quiver

PyTorch Library for Low-Latency, High-Throughput Graph Learning on GPUs.

linear-regression-demo

private quantized linear regression on Ethereum

18337

18.337 - Parallel Computing and Scientific Machine Learning

6s965-fall2022

DaggerFlux.jl

Distributed computation of differentiation pipelines to use multiple workers, devices, GPU, etc. since Julia wasn't fast enough already

pyproximal

PyProximal – Proximal Operators and Algorithms in Python

tinygrad

You like pytorch? You like micrograd? You love tinygrad! ❤️

AES.jl

AES implementation in Julia. Supports 128/192/256-bit keys and several cipher modes of operation.

AES.jl

Advanced Encryption Standard On-the-Fly mode in Julia

AES-variants

Performance-engineered and parallelized implementations of AES in Julia

6_867_fa21_notes

notes for machine learning 6.867 @ mit fall 2021

tiny_nas