Ashok Chandrasekar
Ashok Chandrasekar is a Staff Software Engineer at Google working on AI Inference performance evaluation and optimization for Google Kubernetes Engine. He is a project lead and maintainer of Inference Perf and co-lead of SIG Benchmarking in the llm-d project. He holds a Master's degree from Carnegie Mellon University. Previously, he was a Staff Engineer at VMware. His research interests lie in Distributed Systems with his current focus being Systems for AI/ML applications.
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Inference Perf: A Benchmarking Tool for GenAI Inference
Sachin Varghese
Jason Kramberger
Brendan Slabe
Chen Wang
Yuan Tang
Journal of Open Source Software (2026)
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Inference Perf is a generative AI (GenAI) inference performance benchmarking tool aimed at benchmarking and analyzing the performance of inference deployments. It is designed to be model-server agnostic, allowing for apples-to-apples comparisons across different model servers and serving stacks. As part of the inference benchmarking and metrics standardization effort in the Kubernetes wg-serving, it seeks to standardize tooling and metrics for measuring inference performance across the Kubernetes and model server communities.
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