Running ML Inference Services in Shared Hosting Environments
Offered By: MLOps World: Machine Learning in Production via YouTube
Course Description
Overview
Explore the challenges and solutions of running machine learning inference services in shared hosting environments like ECS and Kubernetes in this 26-minute conference talk from MLOps World. Learn how Nextdoor's ML team identified and resolved issues affecting latency and throughput, resulting in significant performance improvements. Discover key insights on request queue management and OpenMP parameter tuning to optimize ML inference services. Gain valuable knowledge from machine learning engineer Danny Luo's experience in implementing ML solutions in complex enterprise environments, and understand how to achieve substantial latency reductions, throughput increases, and improved resource utilization while maintaining performance in shared hosting setups.
Syllabus
Running ML Inference Services in Shared Hosting Environments
Taught by
MLOps World: Machine Learning in Production
Related Courses
High Performance ComputingGeorgia Institute of Technology via Udacity Введение в параллельное программирование с использованием OpenMP и MPI
Tomsk State University via Coursera Introduction to parallel Programming in Open MP
Indian Institute of Technology Delhi via Swayam High Performance Computing for Scientists and Engineers
Indian Institute of Technology, Kharagpur via Swayam Introduction to Parallel Programming in OpenMP
Indian Institute of Technology Delhi via Swayam