xdit-project / DiTCacheAnalysisLinks
An auxiliary project analysis of the characteristics of KV in DiT Attention.
☆31Updated 6 months ago
Alternatives and similar repositories for DiTCacheAnalysis
Users that are interested in DiTCacheAnalysis are comparing it to the libraries listed below
Sorting:
- Quantized Attention on GPU☆44Updated 7 months ago
- A parallelism VAE avoids OOM for high resolution image generation☆64Updated 5 months ago
- A Suite for Parallel Inference of Diffusion Transformers (DiTs) on multi-GPU Clusters☆47Updated 11 months ago
- FastCache: Fast Caching for Diffusion Transformer Through Learnable Linear Approximation [Efficient ML Model]☆24Updated 3 weeks ago
- 🎬 3.7× faster video generation E2E 🖼️ 1.6× faster image generation E2E ⚡ ColumnSparseAttn 9.3× vs FlashAttn‑3 💨 ColumnSparseGEMM 2.5× …☆74Updated last week
- Code for Draft Attention☆72Updated last month
- Patch convolution to avoid large GPU memory usage of Conv2D☆88Updated 5 months ago
- 🤗CacheDiT: A Training-free and Easy-to-use Cache Acceleration Toolbox for Diffusion Transformers🔥☆61Updated this week
- [ECCV24] MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization☆42Updated 6 months ago
- Accelerate LLM preference tuning via prefix sharing with a single line of code☆41Updated last month
- [CVPR 2025] Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers☆51Updated 9 months ago
- ☆167Updated 5 months ago
- XAttention: Block Sparse Attention with Antidiagonal Scoring☆166Updated this week
- (WIP) Parallel inference for black-forest-labs' FLUX model.☆19Updated 7 months ago
- ☆49Updated last month
- [ICLR'25] ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation☆102Updated 3 months ago
- DeeperGEMM: crazy optimized version☆69Updated last month
- ☆60Updated 2 months ago
- [NeurIPS 2024] Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching☆105Updated 11 months ago
- Decoding Attention is specially optimized for MHA, MQA, GQA and MLA using CUDA core for the decoding stage of LLM inference.☆38Updated 2 weeks ago
- SpInfer: Leveraging Low-Level Sparsity for Efficient Large Language Model Inference on GPUs☆48Updated 3 months ago
- A WebUI for Side-by-Side Comparison of Media (Images/Videos) Across Multiple Folders☆24Updated 4 months ago
- ☆82Updated last month
- ☆75Updated 5 months ago
- 16-fold memory access reduction with nearly no loss☆99Updated 3 months ago
- Triton implement of bi-directional (non-causal) linear attention☆50Updated 4 months ago
- Debug print operator for cudagraph debugging☆10Updated 10 months ago
- Odysseus: Playground of LLM Sequence Parallelism☆70Updated last year
- FORA introduces simple yet effective caching mechanism in Diffusion Transformer Architecture for faster inference sampling.☆46Updated 11 months ago
- Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"☆36Updated 3 weeks ago