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Schedule Overview |
Schedule Overview |
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- This schedule might change slightly during the quarter. The dates of the exam, however, will not change.
- Slides will be uploaded to the course home page, typically before each lecture. The lectures themselves might deviate significantly from the textbooks. Thus, it is necessary to attend a lecture live or view its video asynchronously to keep up with course content.
- The industry guest lectures are not included in the syllabus for the exams. But they will be the focus of the extra credit activities.
- Some topics may take a few weeks to cover.
| Week | Topic | References |
|---|---|---|
| 1-2 | Basics: Computer Organization, Operating systems, Storage | |
| 3 | Basics of Cloud Computing | |
| 4 | Cloud Storage | |
| 5 | Parallel and Scalable Data Processing: Parallelism Basics | |
| 6 | Big Data: Data encoding, query languages, etc. | |
| 7 | Big Data: MapReduce, Spark, batch and streaming processing | |
| 7-8 | Guest Talk: TBD | |
| 8 | MLSYS: machine learning, Autodiff, Dataflow graphs, GPUs, ML frameworks | |
| 8 | Guest Talk: TBD | |
| 9 | MLSYS: ML compilation, graph optimizaiton, ML parallelisms | |
| 9 | Guest Talk: TBD | |
| 10 | MLSYS: ML parallelisms, LLMs, scaling law, training, serving | |
| 10 | Final exam reviews | |
| 11 | Final exam on March 22, 8 - 11am. |