doppioDB 2.0: Hardware Techniques for Improved Integration of Machine Learning into Databases
Summary: Hardware-accelerated ML integration in a DBMS. Demonstrates two complementary approaches in doppioDB 2.0: coordinate-descent training of generalized linear models on compressed/encrypted column-stores, and bitwise weaving index enabled SGD on low-precision data, exposed via SQL. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Authors
- 1. Kaan Kara
- 2. Zeke Wang
- 3. Ce Zhang
- 4. Gustavo Alonso
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 8,432 | Tackling Hardware/Software co-design from a database perspective | 2020 | CIDR | 4.5081086e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 10 of 10 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 832 | Learning Linear Regression Models over Factorized Joins | 2016 | SIGMOD | 0.00016089705 |
| 1,172 | Learning Generalized Linear Models Over Normalized Data | 2015 | SIGMOD | 0.00013504249 |
| 1,267 | BitWeaving: Fast Scans for Main Memory Data Processing | 2013 | SIGMOD | 0.00012917585 |
| 4,040 | In-RDBMS Hardware Acceleration of Advanced Analytics | 2018 | VLDB | 6.5052227e-05 |
| 5,124 | Accelerating Generalized Linear Models with MLWeaving: A One-Size-Fits-All System for Any-Precision Learning | 2019 | VLDB | 5.6747536e-05 |
| 5,179 | FPGA-based Data Partitioning | 2017 | SIGMOD | 5.6384436e-05 |
| 6,400 | ColumnML: Column-Store Machine Learning with On-The-Fly Data Transformation | 2019 | VLDB | 5.0739311e-05 |
| 7,419 | MLBench: Benchmarking Machine Learning Services Against Human Experts | 2018 | VLDB | 4.7302312e-05 |
| 8,201 | Accelerating Pattern Matching Queries in Hybrid CPU-FPGA Architectures | 2017 | SIGMOD | 4.5555217e-05 |
| 8,417 | doppioDB: A Hardware Accelerated Database | 2017 | SIGMOD | 4.5120193e-05 |
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