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adventofcode2016

My java solutions of the programming puzzles.

algorhythmhashcode

Repo to practice Google's HashCode problems

dali

A GPU-accelerated library containing highly optimized building blocks and an execution engine for data processing to accelerate deep learning training and inference applications.

deepspeed

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

faster-pytorch-blog

Outlining techniques for improving the training performance of your PyTorch model without compromising its accuracy

ffcv

FFCV: Fast Forward Computer Vision (and other ML workloads!)

fp8-benchmark

fuser

A Fusion Code Generator for NVIDIA GPUs (commonly known as "nvFuser")

lightning

Build and train PyTorch models and connect them to the ML lifecycle using Lightning App templates, without handling DIY infrastructure, cost management, scaling, and other headaches.

lightning-quick-start

lightning-thunder

Source to source compiler for PyTorch. It makes PyTorch programs faster on single accelerators and distributed.

litdata

Blazingly fast, distributed streaming of training data from any cloud storage for training AI models

lm-evaluation-harness

A framework for few-shot evaluation of autoregressive language models.

megatron-lm

Ongoing research training transformer models at scale

neurips_llm_efficiency_challenge

NeurIPS Large Language Model Efficiency Challenge: 1 LLM + 1GPU + 1Day

nnutils

CPU & CUDA implementation of several neural network utils

probot

pylaia

A deep learning toolkit for handwritten document analysis

pylaia-examples

A set of experiments using PyLaia on different datasets

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

stable-diffusion

A latent text-to-image diffusion model

taming-transformers

Taming Transformers for High-Resolution Image Synthesis

toolbox

Essential guides and programming tools in my toolbox (with focus on ML Training)

transformerengine

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper GPUs, to provide better performance with lower memory utilization in both training and inference.

uva

UVA programming challenges

windifier

Wind [instrument] Classifier. Using CNNs.

xla

Enabling PyTorch on Google TPU