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CMU 15-721: Advanced Database Systems →0/22
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S2024 #00 - Course Overview & Logistics (CMU Advanced Database Systems)

33:17
2

S2024 #01 - Modern OLAP Database Systems (CMU Advanced Database Systems)

1:09:05
3

S2024 #02 - Data Formats & Encoding Part 1 (CMU Advanced Database Systems)

1:23:08
4

S2024 #03 - Data Formats & Encoding Part 2 (CMU Advanced Database Systems)

1:21:48
5

S2024 #04 - Query Execution & Processing Part 1 (CMU Advanced Database Systems)

1:23:43
6

S2024 #05 - Query Execution & Processing Part 2 (CMU Advanced Database Systems)

1:24:55
7

S2024 #06 - Vectorized Query Execution Using SIMD (CMU Advanced Database Systems)

1:18:40
8

Lecture 7: JIT Query Compilation & Code Generation (15-721)

1:21:57
9

Lecture 8: Query Scheduling & Coordination (15-721)

1:24:32
10

Lecture 9: Parallel Hash Join Algorithms (15-721)

1:25:37
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Lecture 10: Multi-Way Join Algorithms / Worst-Case Optimal Joins (15-721)

1:09:43
12

Lecture 11: User-Defined Function Optimizations (15-721)

1:20:25
13

Lecture 12: Database Networking Protocols (15-721)

1:22:56
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Lecture 13: Query Optimizer Implementation 1 (15-721)

1:23:31
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Lecture 14: Query Optimizer Implementation 2 (15-721)

1:20:31
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Lecture 15: Query Optimizer Implementation 3 (15-721)

43:13
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Lecture 17: Google BigQuery / Dremel (15-721)

1:08:59
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Lecture 18: Databricks Photon / Spark SQL (15-721)

1:07:30
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Lecture 19: Snowflake Data Warehouse Internals (15-721)

1:20:55
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Lecture 20: DuckDB Embedded Database System (15-721)

1:02:13
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Lecture 21: Yellowbrick Data Warehouse System (15-721)

1:21:10
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Lecture 22: Amazon Redshift Data Warehouse System (15-721)

1:04:03

S2024 #06 - Vectorized Query Execution Using SIMD (CMU Advanced Database Systems)

Andy PavloCarnegie Mellon University

Associate Professor of Databaseology

1:18:40·2024·graduate level

This lecture from CMU's Advanced Database Systems course details the principles and implementation of vectorized query execution, leveraging Single Instruction, Multiple Data (SIMD) CPU instructions to accelerate database operations. It covers the architectural considerations and performance implications of vectorization.

Systems & CSDatabase SystemsComputer ArchitectureQuery OptimizationSIMD Instructions

Andy Pavlo (https://www.cs.cmu.edu/~pavlo/)

Slides: https://15721.courses.cs.cmu.edu/spring2024/slides/06-vectorization.pdf

Notes: https://15721.courses.cs.cmu.edu/spring2024/notes/06-vectorization.pdf

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S2024 #05 - Query Execution & Processing Part 2 (CMU Advanced Database Systems)

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Lecture 7: JIT Query Compilation & Code Generation (15-721)

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