NVIDIA / Star-Attention
Efficient LLM Inference over Long Sequences
☆372Updated this week
Alternatives and similar repositories for Star-Attention:
Users that are interested in Star-Attention are comparing it to the libraries listed below
- [ICLR 2025] DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads☆456Updated 2 months ago
- LLM KV cache compression made easy☆471Updated this week
- [MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Se…☆656Updated 2 months ago
- [NeurIPS 2024] KVQuant: Towards 10 Million Context Length LLM Inference with KV Cache Quantization☆346Updated 8 months ago
- A throughput-oriented high-performance serving framework for LLMs☆804Updated this week
- 🚀 Efficiently (pre)training foundation models with native PyTorch features, including FSDP for training and SDPA implementation of Flash…☆244Updated this week
- Code for "LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding", ACL 2024☆291Updated this week
- Perplexity GPU Kernels☆272Updated this week
- Ring attention implementation with flash attention☆757Updated 3 weeks ago
- [ICLR'25] Fast Inference of MoE Models with CPU-GPU Orchestration☆209Updated 5 months ago
- Applied AI experiments and examples for PyTorch☆262Updated last week
- 🐳 Efficient Triton implementations for "Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention"☆647Updated last month
- [NeurIPS'24 Spotlight, ICLR'25] To speed up Long-context LLMs' inference, approximate and dynamic sparse calculate the attention, which r…☆997Updated last week
- Dynamic Memory Management for Serving LLMs without PagedAttention☆360Updated 2 weeks ago
- USP: Unified (a.k.a. Hybrid, 2D) Sequence Parallel Attention for Long Context Transformers Model Training and Inference☆488Updated 2 weeks ago
- VPTQ, A Flexible and Extreme low-bit quantization algorithm☆632Updated last week
- Advanced Quantization Algorithm for LLMs/VLMs.☆449Updated this week
- [MLSys'24] Atom: Low-bit Quantization for Efficient and Accurate LLM Serving☆307Updated 10 months ago
- A curated collection of resources, tutorials, and best practices for learning and mastering NVIDIA CUTLASS☆169Updated last month
- Fast low-bit matmul kernels in Triton☆295Updated this week
- A subset of PyTorch's neural network modules, written in Python using OpenAI's Triton.☆536Updated last week
- Memory layers use a trainable key-value lookup mechanism to add extra parameters to a model without increasing FLOPs. Conceptually, spars…☆322Updated 4 months ago
- [ICML 2024] Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference☆274Updated 5 months ago
- A family of compressed models obtained via pruning and knowledge distillation☆335Updated 5 months ago
- A low-latency & high-throughput serving engine for LLMs☆351Updated 2 weeks ago
- PyTorch per step fault tolerance (actively under development)☆291Updated this week
- ☆434Updated last week
- ☆186Updated 7 months ago
- A high-throughput and memory-efficient inference and serving engine for LLMs☆262Updated 6 months ago
- Towards Economical Inference: Enabling DeepSeek's Multi-Head Latent Attention in Any Transformer-based LLMs☆163Updated this week