tungngreen/PipelineScheduler
PipelineScheduler optimizes workload distribution between servers and edge devices, setting optimal batch sizes to maximize throughput and minimize latency amid content dynamics and network instability. It also addresses resource contention with spatiotemporal inference scheduling to reduce co-location interference.
This system helps operations engineers and IT managers automatically manage and optimize video analytics pipelines running across servers and edge devices like cameras. It takes live video streams and inference models as input, and outputs optimized processing decisions that maximize video analysis speed and minimize delays, even when network conditions or video content changes. It's designed for those responsible for deploying and maintaining high-performance, real-time video analytics infrastructure.
Use this if you need to run complex video analytics workflows across distributed hardware, ensuring maximum speed and minimal delay while automatically adapting to real-time changes in network conditions and video content.
Not ideal if your video analytics are run on a single, isolated device without distributed processing or dynamic environmental challenges.
Stars
10
Forks
2
Language
C++
License
MIT
Category
Last pushed
Mar 18, 2026
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/mlops/tungngreen/PipelineScheduler"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
mlflow/mlflow
The open source AI engineering platform. MLflow enables teams of all sizes to debug, evaluate,...
kitops-ml/kitops
An open source DevOps tool from the CNCF for packaging and versioning AI/ML models, datasets,...
aws-samples/mlops-e2e
MLOps End-to-End Example using Amazon SageMaker Pipeline, AWS CodePipeline and AWS CDK
tensorchord/envd
🏕️ Reproducible development environment for humans and agents
techiescamp/mlops-for-devops
MLOps for DevOps Engineers - A hands-on, project-based guide to Machine Learning Operations