thu-ml / SageAttention
Quantized Attention that achieves speedups of 2.1-3.1x and 2.7-5.1x compared to FlashAttention2 and xformers, respectively, without lossing end-to-end metrics across various models.
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Quantized Attention that achieves speedups of 2.1-3.1x and 2.7-5.1x compared to FlashAttention2 and xformers, respectively, without lossing end-to-end metrics across various models.
FlashInfer: Kernel Library for LLM Serving
RAFT contains fundamental widely-used algorithms and primitives for machine learning and information retrieval. The algorithms are CUDA-accelerated and form building blocks for more easily writing high performance applications.
NCCL Tests
CUDA Kernel Benchmarking Library
cuGraph - RAPIDS Graph Analytics Library
Instant neural graphics primitives: lightning fast NeRF and more
cuVS - a library for vector search and clustering on the GPU
CUDA Library Samples
Causal depthwise conv1d in CUDA, with a PyTorch interface
LLM training in simple, raw C/CUDA
Tile primitives for speedy kernels