zhengzangw / Sequence-SchedulingLinks
PyTorch implementation of paper "Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline".
☆94Updated 2 years ago
Alternatives and similar repositories for Sequence-Scheduling
Users that are interested in Sequence-Scheduling are comparing it to the libraries listed below
Sorting:
- ☆88Updated 3 years ago
- [NeurIPS 2024] Efficient LLM Scheduling by Learning to Rank☆65Updated last year
- [OSDI'24] Serving LLM-based Applications Efficiently with Semantic Variable☆199Updated last year
- SpotServe: Serving Generative Large Language Models on Preemptible Instances☆132Updated last year
- ☆124Updated last year
- ☆58Updated last year
- ☆61Updated last year
- 16-fold memory access reduction with nearly no loss☆108Updated 8 months ago
- A resilient distributed training framework☆96Updated last year
- ☆83Updated last year
- [ICML 2024] Serving LLMs on heterogeneous decentralized clusters.☆31Updated last year
- Code associated with the paper **Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative Decoding**☆210Updated 9 months ago
- [ICML 2024] Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference☆353Updated 4 months ago
- ☆290Updated 4 months ago
- ☆79Updated last month
- GEAR: An Efficient KV Cache Compression Recipefor Near-Lossless Generative Inference of LLM☆170Updated last year
- ☆347Updated last year
- ☆152Updated 4 months ago
- ☆82Updated 7 months ago
- [NeurIPS'23] H2O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.☆488Updated last year
- Stateful LLM Serving☆89Updated 8 months ago
- [NeurIPS 2024] The official implementation of "Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exitin…☆63Updated last year
- Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity☆224Updated 2 years ago
- ☆141Updated last year
- Official repository for DistFlashAttn: Distributed Memory-efficient Attention for Long-context LLMs Training☆218Updated last year
- PyTorch library for cost-effective, fast and easy serving of MoE models.☆262Updated last month
- [ICLR 2025] TidalDecode: A Fast and Accurate LLM Decoding with Position Persistent Sparse Attention☆49Updated 3 months ago
- [ICLR 2025] PEARL: Parallel Speculative Decoding with Adaptive Draft Length☆131Updated last month
- ☆101Updated last year
- Spec-Bench: A Comprehensive Benchmark and Unified Evaluation Platform for Speculative Decoding (ACL 2024 Findings)☆338Updated 7 months ago