Hi Pablo and Beam Dev Team, I am extremely sorry; I forgot to include an appropriate subject line in my previous message. Please accept my apologies.
My name is Sai Shashank Mudliar, and I am a full-time Computer Engineering student at Purdue University. I am writing to express my interest in the GSoC 2025 project "A learning path to using accelerators with Beam." I believe I bring a strong fit for this project because I have direct production experience with the exact stack involved. I served as a Staff Machine Learning Engineer at CVS Health, where I: • Deployed multiple ML models for inference on Google Cloud Dataflow at scale, several of which are running in production today. • Authored an internal ML Inference Cookbook used across CVS Health's ML teams for deploying models on Dataflow with accelerators. • Led a Proof-of-Concept integrating NVIDIA Triton Inference Server with Beam by building a custom ModelHandler—a framework not natively supported at the time. • Built GPU-accelerated Dataflow pipelines with custom Docker containers, Flex Templates, and T4/A100 GPU workers. I have also identified and am actively working on a concrete contribution: the existing TensorRTEngineHandlerNumPy in tensorrt_inference.py uses deprecated TensorRT 8.x/9.x APIs (num_bindings, get_binding_name, execute_async_v2, trt.volume) that are incompatible with TensorRT 10.x. I plan to submit a PR fixing this before the GSoC period begins: https://github.com/apache/beam/pull/36309/ <https://www.google.com/search?q=https://github.com/apache/beam/pull/36309/> Proposal Overview My proposal covers the five deliverables outlined in the project idea—a CPU baseline script, GPU-accelerated inference, TPU inference with LLMs, a parallel multi-model training pipeline, and a blog post—plus continuous testing infrastructure. Each deliverable is provided as both a standalone Python script and a Jupyter notebook, addressing the gap that all 44 existing beam-ml examples are notebooks only. I have attached my full proposal for your review. I would welcome any feedback on the proposal or guidance on how to best align with the project's priorities. I am also happy to hop on a call at your convenience. Thank you for your time and for mentoring this project. Best regards, Sai Shashank Mudliar Purdue University, Computer Engineering
GSoC_Proposal_HW_Accelerators_Learning_Path.docx
Description: MS-Word 2007 document
