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18-447

big

cmu-18-447

cmulabs

Lab assignments in CMU 18-447 Computer Architecture course

colossal-test

colossalai

Making big AI models cheaper, easier, and scalable

cubework-hzy1

cupq

a CUDA implementation of a priority queue

cusync

diffusers

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch

flash-attention

Fast and memory-efficient exact attention

flash-attention-minimal

Flash Attention in ~100 lines of CUDA (forward pass only)

for_pre_commit

fsdp

gpt2-1

lsolver

:1234: lsolver is developed to optimize the performance of the sparse matrix triangular solve.

mips-processor

5 Stage MIPS Processor

mips-sim

mips-simulator

o-vit-ddp

o-vit-fsdp

resnet-ddp

s-blas

This package includes the implementation for four sparse linear algebra kernels: Sparse-Matrix-Vector-Multiplication (SpMV), Sparse-Triangular-Solve (SpTRSV), Sparse-Matrix-Transposition (SpTrans) and Sparse-Matrix-Matrix-Multiplication (SpMM) for Single-node Multi-GPU (scale-up) platforms such as NVIDIA DGX-1 and DGX-2.

sparse

Optimized sparse triangular solve.

test_action

test_action_new

test_github_action

test_huoshan

vit

vit-colossal