jack-pan-ai

jack-pan-ai's Stars

• langchain-ai/langchain

  🦜🔗 Build context-aware reasoning applications

  Language:Jupyter Notebook97.1k6978k15.8k

• facebookresearch/faiss

  A library for efficient similarity search and clustering of dense vectors.

  Language:C++32.1k4792.5k3.7k

• Dao-AILab/flash-attention

  Fast and memory-efficient exact attention

  Language:Python14.8k1241.2k1.4k

• NVIDIA/DeepLearningExamples

  State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

  Language:Jupyter Notebook13.7k2968493.3k

• NVIDIA/Megatron-LM

  Ongoing research training transformer models at scale

  Language:Python10.9k1668112.4k

• NVIDIA/TensorRT-LLM

  TensorRT-LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and build TensorRT engines that contain state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT-LLM also contains components to create Python and C++ runtimes that execute those TensorRT engines.

  Language:C++9k972.1k1k

• EleutherAI/gpt-neox

  An implementation of model parallel autoregressive transformers on GPUs, based on the Megatron and DeepSpeed libraries

  Language:Python7k1274511k

• Stability-AI/StableCascade

  Official Code for Stable Cascade

  Language:Jupyter Notebook6.6k60124533

• NeoVertex1/SuperPrompt

  SuperPrompt is an attempt to engineer prompts that might help us understand AI agents.

  5.7k7621528

• kokkos/kokkos

  Kokkos C++ Performance Portability Programming Ecosystem: The Programming Model - Parallel Execution and Memory Abstraction

  Language:C++2.1k903k440

• microsoft/Megatron-DeepSpeed

  Ongoing research training transformer language models at scale, including: BERT & GPT-2

  Language:Python1.9k25183344

• BBuf/how-to-optim-algorithm-in-cuda

  how to optimize some algorithm in cuda.

  Language:Cuda1.8k2610147

• openai/blocksparse

  Efficient GPU kernels for block-sparse matrix multiplication and convolution

  Language:Cuda1k19548202

• 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:Cuda8701315137

• src-d/kmcuda

  Large scale K-means and K-nn implementation on NVIDIA GPU / CUDA

  Language:Jupyter Notebook81228103146

• guoshnBJTU/ASTGCN-2019-pytorch

  Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting, AAAI 2019, pytorch version

  Language:Python61560156

• kakao/n2

  TOROS N2 - lightweight approximate Nearest Neighbor library which runs fast even with large datasets

  Language:Jupyter Notebook568393669

• js05212/BayesianDeepLearning-Survey

  Bayesian Deep Learning: A Survey

  50629062

• NVIDIA/modulus-makani

  Massively parallel training of machine-learning based weather and climate models

  Language:Python24013433

• ecrc/kblas-gpu

  Subset of BLAS routines optimized for NVIDIA GPUs

  Language:Cuda657910

• suco-gt/HPC-Internships

  Supercomputing @ GT has compiled a list of organizations that offer internships and experiences in HPC and applications of HPC.

  54303

• tulerfeng/Awesome-Embodied-Multimodal-LLMs

  Latest Advances on Embodied Multimodal LLMs (or Vison-Language-Action Models).

  50203

• davidruegamer/FDA_tutorial

  Language:R21402

• TheCoreTeam/core_scheduler

  CoreScheduler: A High-Performance Scheduler for Large Model Training

  Language:C++21296

• zuochunwei/hpc

  21301

• ecrc/ExaGeoStatCPP

  Language:C++5200

• DragosTana/kmeans

  KMeans algorithmn parallelized with OpenMP

  Language:C++3100

• hpc-io/aiio

  Language:Jupyter Notebook3405

• paper-code1/BV-Gaussian

  Language:C++1000

• suco-gt/HPC-Student-Resources

  Student resources and opportunities in HPC!

  10