qingleicao Goto Github PK

ai-science-training-series

ai-training-series

AI Training Series Material

auto-gpt

An experimental open-source attempt to make GPT-4 fully autonomous.

booklet_wamta_2025

casting_on_device

climaatmos.jl

ClimaAtmos.jl is a library for building atmospheric circulation models that is designed from the outset to leverage data assimilation and machine learning tools. We welcome contributions!

cudalibrarysamples

CUDA Library Samples

dplasma

DPLASMA is the fastest implementation of a dense linear algebra package for distributed heterogeneous systems. It is designed to deliver sustained performance for distributed systems where each node featuring multiple sockets of multicore processors, and if available, accelerators, using the PaRSEC runtime as a backend.

flexflow

FlexFlow Serve: Low-Latency, High-Performance LLM Serving

free-programming-books

:books: Freely available programming books

gptune

h5bench

A benchmark suite for measuring HDF5 performance.

hip-training-series

Repository with examples and exercises for OLCF and AMD's HIP training series

latent-diffusion

High-Resolution Image Synthesis with Latent Diffusion Models

learning_note_qinglei

llm_tutorial

llm_tutorials

llmspracticalguide

A curated list of practical guide resources of LLMs (LLMs Tree, Examples, Papers)

malt

MALT is a MALloc Tracker to find where and how your made your memory allocations in C/C++/Fortran applications.

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

mpi4py

Python bindings for MPI

nsf-proposal-latex-samples

LaTeX samples for NSF Research.gov Proposal Submission. For more information about Research.gov Proposal Submission visit https://www.research.gov/research-web/content/aboutpsm Feedback [email protected]

parsec

PaRSEC is a generic framework for architecture aware scheduling and management of micro-tasks on distributed, GPU accelerated, many-core heterogeneous architectures. PaRSEC assigns computation threads to the cores, GPU accelerators, overlaps communications and computations and uses a dynamic, fully-distributed scheduler based on architectural features such as NUMA nodes and algorithmic features such as data reuse.

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

pytorch-deep-learning

Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.

qingleicao.github.io

roop_face

one-click deepfake (face swap)

sort-google-scholar

Sorting Google Scholar search results based on the number of citations

stable-diffusion

A latent text-to-image diffusion model

task-bench

A task benchmark

ttg

TTG: Template Task Graph C++ API