nus-hpc-ai-lab Goto Github PK

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colossalai

Colossal-AI: A Unified Deep Learning System for Large-Scale Parallel Training

ctrl

Pytorch implementation of "Two Trades is not Baffled: Condensing Graph via Crafting Rational Gradient Matching"

datm

ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching

dynamic-tuning

The official implementation of "2024Arxiv Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation"

energonai

Large-scale model inference.

fastfold

Optimizing Protein Structure Prediction Model Training and Inference on GPU Clusters

geom

Pytorch implementation of ICML-2024 "Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching"

helen

The official implementation of "Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization"

infobatch

Lossless Training Speed Up by Unbiased Dynamic Data Pruning

infogrowth

Efficient and Online Dataset Growth Algorithm (with cleanness and diversity awareness) to deal with growing web data

lars-imagenet-pytorch

Accuracy 77%. Large batch deep learning optimizer LARS for ImageNet with PyTorch and ResNet, using Horovod for distribution. Optional accumulated gradient and NVIDIA DALI dataloader.

neural-network-parameter-diffusion

We introduce a novel approach for parameter generation, named neural network parameter diffusion (p-diff), which employs a standard latent diffusion model to synthesize a new set of parameters

oh-my-server

opendit

OpenDiT: An Easy, Fast and Memory-Efficient System for DiT Training and Inference

palm-colossalai

Scalable PaLM implementation of PyTorch

pytorch-lamb

PyTorch implementation of LAMB for ImageNet/ResNet-50 training

skycomputing

Sky Computing, a new way for federated learning

tensornvme

A Python library transfers PyTorch tensors between CPU and NVMe