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Found 5 papers, 3 papers with code
Optimizing RLHF Training for Large Language Models with Stage Fusion
Due to the intrinsic nature of RLHF training, i. e., the data skewness in the generation stage and the pipeline bubbles in the training stage, existing RLHF systems suffer from low GPU utilization.
Mirage: A Multi-Level Superoptimizer for Tensor Programs
We introduce Mirage, the first multi-level superoptimizer for tensor programs.
LoongServe: Efficiently Serving Long-Context Large Language Models with Elastic Sequence Parallelism
The context window of large language models (LLMs) is rapidly increasing, leading to a huge variance in resource usage between different requests as well as between different phases of the same request.
Fast Distributed Inference Serving for Large Language Models
Large language models (LLMs) power a new generation of interactive AI applications exemplified by ChatGPT.
Learning Accurate Performance Predictors for Ultrafast Automated Model Compression
On the contrary, we obtain the optimal efficient networks by directly optimizing the compression policy with an accurate performance predictor, where the ultrafast automated model compression for various computational cost constraint is achieved without complex compression policy search and evaluation.
