ml-energy / leaderboardLinks
How much energy do GenAI models consume?
☆47Updated 4 months ago
Alternatives and similar repositories for leaderboard
Users that are interested in leaderboard are comparing it to the libraries listed below
Sorting:
- Measure and optimize the energy consumption of your AI applications!☆291Updated last month
- A resilient distributed training framework☆95Updated last year
- PyTorch implementation of paper "Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline".☆90Updated 2 years ago
- LLM Serving Performance Evaluation Harness☆79Updated 6 months ago
- ☆25Updated 2 years ago
- SpotServe: Serving Generative Large Language Models on Preemptible Instances☆129Updated last year
- ☆71Updated last year
- ☆47Updated last year
- [ICLR2025] Breaking Throughput-Latency Trade-off for Long Sequences with Speculative Decoding☆126Updated 9 months ago
- [ICLR 2025] TidalDecode: A Fast and Accurate LLM Decoding with Position Persistent Sparse Attention☆47Updated last month
- NAACL '24 (Best Demo Paper RunnerUp) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference☆68Updated 9 months ago
- A minimal implementation of vllm.☆54Updated last year
- Code for MLSys 2024 Paper "SiDA-MoE: Sparsity-Inspired Data-Aware Serving for Efficient and Scalable Large Mixture-of-Experts Models"☆21Updated last year
- Dynamic resources changes for multi-dimensional parallelism training☆25Updated 3 weeks ago
- ☆86Updated 3 years ago
- Surrogate-based Hyperparameter Tuning System☆27Updated 2 years ago
- (NeurIPS 2022) Automatically finding good model-parallel strategies, especially for complex models and clusters.☆40Updated 2 years ago
- Modular and structured prompt caching for low-latency LLM inference☆100Updated 10 months ago
- EE-LLM is a framework for large-scale training and inference of early-exit (EE) large language models (LLMs).☆67Updated last year
- ☆94Updated 3 years ago
- [OSDI'24] Serving LLM-based Applications Efficiently with Semantic Variable☆181Updated 11 months ago
- GEAR: An Efficient KV Cache Compression Recipefor Near-Lossless Generative Inference of LLM☆168Updated last year
- Efficient Compute-Communication Overlap for Distributed LLM Inference☆43Updated last week
- Stateful LLM Serving☆84Updated 6 months ago
- A framework for generating realistic LLM serving workloads☆58Updated 3 months ago
- [NeurIPS 2024] Efficient LLM Scheduling by Learning to Rank☆59Updated 10 months ago
- End-to-end carbon footprint mod- eling tool☆47Updated 3 months ago
- PyTorch library for cost-effective, fast and easy serving of MoE models.☆236Updated 2 months ago
- ACT An Architectural Carbon Modeling Tool for Designing Sustainable Computer Systems☆42Updated last month
- ☆42Updated 4 months ago