awesome-ai-systems
github.com/jason-cs18/awesome-ai-systems ↗Resources for recent AI systems (deployment concerns, cost and accessibility). -- closed
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Deployment ConcernsCostAccessibilityBooks for Deep Learning (a popular learning approaches in machine learning)CourseConferenceTools
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Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me popular approaches (todo, summary) resources from awesome-ai-systems"
Installation instructions →What's inside
Deployment Concerns
- A Systematic Methodology for Analysis of Deep Learning Hardware and Software Platforms. In MLSys'20.Popular approaches (todo, summary)
- Attention-based Learning for Missing Data Imputation in HoloClean. In MLSys'20.Popular approaches (todo, summary)
- Cryptography for Safe Machine Learning. In MLSys'20.Popular approaches (todo, summary)
- Federated Optimization in Heterogeneous Networks. In MLSys'20.Popular approaches (todo, summary)
- FLEET: Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. In MLSys'20.Popular approaches (todo, summary)
- MLPerf Training Benchmark. In MLSys'20.Popular approaches (todo, summary)
Accessibility
- A System for Massively Parallel Hyperparameter Tuning. In MLSys'20.Popular approaches (todo, summary)
- BPPSA: Scaling Back-propagation by Parallel Scan Algorithm. In MLSys'20.Popular approaches (todo, summary)
- MNN: A Universal and Efficient Inference Engine. In MLSys'20.Popular approaches (todo, summary)
- PLink: Discovering and Exploiting Locality for Accelerated Distributed Training on the public Cloud. In MLSys'20.Popular approaches (todo, summary)
Cost
- Blink: Fast and Generic Collectives for Distributed ML. In MLSys'20.Popular approaches (todo, summary)
- Breaking the Memory Wall with Optimal Tensor Rematerialization. In MLSys'20.Popular approaches (todo, summary)
- Distributed Hierarchical GPU Parameter Server for Massive Scale Deep Learning Ads Systems. In MLSys'20.Popular approaches (todo, summary)
- Fine-Grained GPU Sharing Primitives for Deep Learning Applications. In MLSys'20.Popular approaches (todo, summary)
- Improving Resource Efficiency of Deep Activity Recognition via Redundancy Reduction. In HotMobile'20.Popular approaches (todo, summary)
- Improving the Accuracy, Scalability, and Performance of Graph Neural Networks with Roc. In MLSys'20.Popular approaches (todo, summary)
Books for Deep Learning (a popular learning approaches in machine learning)
Conference
Showing a sample of 44 resources. View the full list on GitHub →