alibaba / ServeGenLinks
A framework for generating realistic LLM serving workloads
☆65Updated this week
Alternatives and similar repositories for ServeGen
Users that are interested in ServeGen are comparing it to the libraries listed below
Sorting:
- Stateful LLM Serving☆85Updated 6 months ago
- SpotServe: Serving Generative Large Language Models on Preemptible Instances☆129Updated last year
- A ChatGPT(GPT-3.5) & GPT-4 Workload Trace to Optimize LLM Serving Systems☆205Updated 2 months ago
- ☆72Updated last year
- A resilient distributed training framework☆95Updated last year
- [NeurIPS 2024] Efficient LLM Scheduling by Learning to Rank☆59Updated 10 months ago
- ☆77Updated 3 years ago
- ☆123Updated 10 months ago
- [ICML 2024] Serving LLMs on heterogeneous decentralized clusters.☆30Updated last year
- [OSDI'24] Serving LLM-based Applications Efficiently with Semantic Variable☆184Updated last year
- Dynamic resources changes for multi-dimensional parallelism training☆28Updated last month
- AlpaServe: Statistical Multiplexing with Model Parallelism for Deep Learning Serving (OSDI 23)☆87Updated 2 years ago
- kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference.☆94Updated this week
- An interference-aware scheduler for fine-grained GPU sharing☆147Updated 8 months ago
- Open-source implementation for "Helix: Serving Large Language Models over Heterogeneous GPUs and Network via Max-Flow"☆67Updated 10 months ago
- ☆138Updated 2 months ago
- NEO is a LLM inference engine built to save the GPU memory crisis by CPU offloading☆62Updated 3 months ago
- Efficient Interactive LLM Serving with Proxy Model-based Sequence Length Prediction | A tiny BERT model can tell you the verbosity of an …☆42Updated last year
- ☆51Updated 3 months ago
- Artifact of OSDI '24 paper, ”Llumnix: Dynamic Scheduling for Large Language Model Serving“☆62Updated last year
- High performance Transformer implementation in C++.☆134Updated 8 months ago
- This repository is established to store personal notes and annotated papers during daily research.☆152Updated last month
- nnScaler: Compiling DNN models for Parallel Training☆118Updated last week
- ☆55Updated 2 weeks ago
- PyTorch library for cost-effective, fast and easy serving of MoE models.☆241Updated 2 months ago
- PyTorch implementation of paper "Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline".☆90Updated 2 years ago
- ☆42Updated 5 months ago
- Compiler for Dynamic Neural Networks☆46Updated last year
- LLM serving cluster simulator☆114Updated last year
- paper and its code for AI System☆330Updated last month