101 citations · 102 across the 6 of their papers we have counts for
6 papers
Search Your Block Floating Point Scales!
Tanmaey Gupta, Hayden Prairie, Xiaoxia Wu +10
Quantization has emerged as a standard technique for accelerating inference for generative models by enabling faster low-precision computations and reduced memory transfers. Recent…
OSWorld-Human: Benchmarking the Efficiency of Computer-Use Agents
Reyna Abhyankar, Qi Qi, Yiying Zhang
Generative AI is being leveraged to solve a variety of computer-use tasks involving desktop applications. State-of-the-art systems have focused solely on improving accuracy on lead…
Cognify: Supercharging Gen-AI Workflows With Hierarchical Autotuning
Zijian He, Reyna Abhyankar, Vikranth Srivatsa +1
Today's gen-AI workflows that involve multiple ML model calls, tool/API calls, data retrieval, or generic code execution are often tuned manually in an ad-hoc way that is both time…
Preble: Efficient Distributed Prompt Scheduling for LLM Serving
Vikranth Srivatsa, Zijian He, Reyna Abhyankar +2
Prompts to large language models (LLMs) have evolved beyond simple user questions. For LLMs to solve complex problems, today's practices are to include domain-specific instructions…
InferCept: Efficient Intercept Support for Augmented Large Language Model Inference
Reyna Abhyankar, Zijian He, Vikranth Srivatsa +2
Large language models are increasingly integrated with external environments, tools, and agents like ChatGPT plugins to extend their capability beyond language-centric tasks. Howev…
SpecInfer: Accelerating Generative Large Language Model Serving with Tree-based Speculative Inference and Verification
Xupeng Miao, Gabriele Oliaro, Zhihao Zhang +12
This paper introduces SpecInfer, a system that accelerates generative large language model (LLM) serving with tree-based speculative inference and verification. The key idea behind…