diff --git a/Schedule.md b/Schedule.md
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@@ -14,7 +14,7 @@ Note that all of the readings are accessible from the original repositories I ha
| 7 | 2/22 | No class -- Reading week| | |
| 8 | 2/29 | No class -- I have a conflict| | |
| 9 | 3/7 | Memory disaggregation | Joseph Boulis
Brian Song | * Y. Zhang et al., [Towards Cost-Effective and Elastic Cloud Database Deployment via Memory Disaggregation](https://doi.org/10.14778/3467861.3467877){:target="_blank"}, _Proc. VLDB Endowment_, 14(10): 1900 - 1912, 2021.
* Wei Cao et al., [PolarDB Serverless: A Cloud Native Database for Disaggregated Data Centers](https://doi.org/10.1145/3448016.3457560){:target="_blank"}, In _Proc. ACM SIGMOD Int. Conf. Management of Data_, pages 2477–2489, 2021. | [Joseph Slides](https://www.dropbox.com/scl/fi/zjihngj2ymabqzn84t7dv/7-boulis-slides1-Joseph-Boulis.pdf?rlkey=tiwema9cayo6whl81ionrpjtc&dl=0){:target="_blank"}
[Brian Slides](https://www.dropbox.com/scl/fi/1i6j3q7fvyf51cvg61wmx/9-Song-slides2-Brian-Song.pdf?rlkey=dd0og633wl37ha3jmha285bu4&dl=0){:target="_blank"} |
-| 10 | 3/12 | Hardware accelerators | Tilmann Rabl, Hasso Plattner Institute
Xiangyao Yu, Uni. Wisconsin-Madison | * C. Lutz et al., [Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects](https://doi.org/10.1145/3318464.3389705){:target="_blank"}, In _Proc. ACM SIGMOD Int. Conf. Management of Data_, pages 1633–1649, 2020. (This is the paper to review.)
* T. Maltenberger et al, [Evaluating Multi-GPU Sorting with Modern Interconnects](https://dl.acm.org/doi/10.1145/3514221.3517842){:target="_blank"}, In _Proc. ACM SIGMOD International Conference on Management of Data_, , pages 1795–1809, 2022.
* B. Yogatama et al, [Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS](https://www.vldb.org/pvldb/vol15/p2491-yogatama.pdf){:target="_blank"}, Proc. VLDB Endowment_, 15(11): 2491-2503, 2022. (This is the paper to review.)
A. Shanbhag et al, [A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics](https://dl.acm.org/doi/abs/10.1145/3318464.3380595){:target="_blank"}, In _Proc. ACM SIGMOD Int. Conf. Management of Data_, pages 1617–1632, 2020.
A. Shanbhag et al, [Tile-based Lightweight Integer Compression in GPU](https://dl.acm.org/doi/10.1145/3514221.3526132){:target="_blank"}, In _Proc. ACM SIGMOD Int. Conf. Management of Data_, pages 1390–1403, 2022. | Tilmann Slides
Xiangyao Slides |
+| 10 | 3/12 | Hardware accelerators | Tilmann Rabl, Hasso Plattner Institute
Xiangyao Yu, Uni. Wisconsin-Madison | * C. Lutz et al., [Pump Up the Volume: Processing Large Data on GPUs with Fast Interconnects](https://doi.org/10.1145/3318464.3389705){:target="_blank"}, In _Proc. ACM SIGMOD Int. Conf. Management of Data_, pages 1633–1649, 2020. (This is the paper to review.)
* T. Maltenberger et al, [Evaluating Multi-GPU Sorting with Modern Interconnects](https://dl.acm.org/doi/10.1145/3514221.3517842){:target="_blank"}, In _Proc. ACM SIGMOD International Conference on Management of Data_, , pages 1795–1809, 2022.
* B. Yogatama et al, [Orchestrating Data Placement and Query Execution in Heterogeneous CPU-GPU DBMS](https://www.vldb.org/pvldb/vol15/p2491-yogatama.pdf){:target="_blank"}, Proc. VLDB Endowment_, 15(11): 2491-2503, 2022. (This is the paper to review.)
A. Shanbhag et al, [A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics](https://dl.acm.org/doi/abs/10.1145/3318464.3380595){:target="_blank"}, In _Proc. ACM SIGMOD Int. Conf. Management of Data_, pages 1617–1632, 2020.
A. Shanbhag et al, [Tile-based Lightweight Integer Compression in GPU](https://dl.acm.org/doi/10.1145/3514221.3526132){:target="_blank"}, In _Proc. ACM SIGMOD Int. Conf. Management of Data_, pages 1390–1403, 2022. | [Tilmann Slides](https://uwaterloo.ca/data-systems-group/sites/ca.data-systems-group/files/uploads/files/gpuaccelerateddataprocessingtilmannrabl_0.pdf){:target="_blank"}
Xiangyao Slides |
| 11 | 3/21 | Hardware accelerators | Gustavo Alonso, ETH Zürich
Wolfgang Lehner & Alexander Krause, TU Dresden | * D. Korilija et al, [Farview: Disaggregated Memory with Operator Off-loading for Database Engines](https://www.cidrdb.org/cidr2022/papers/p11-korolija.pdf){:target="_blank"}, In _Proc. 12th Conf. on Innovative Data Syst. Research_, 2022. (This is the paper to review)
* Woods et al, [Ibex - An Intelligent Storage Engine with Support for Advanced SQL Off-loading](https://www.vldb.org/pvldb/vol7/p963-woods.pdf){:target="_blank"}, _Proc. VLDB Endow_, 7(11): 963-974, 2014.
* J. Pietrzyk et al., [Program your (custom) SIMD instruction set on FPGA in C++](https://www.dropbox.com/scl/fi/z9j10uarublz9i50vgsq2/p53-pietrzyk.pdf?rlkey=jeuwk2d8z1mne0d0ki0kwuqhl&dl=0), In _Proc. 12th Conf. on Innovative Data Syst. Research_, 2024. | Gustavo Slides
Wolfgang/Alexander Slides |
| 12 | 3/28 | Memory disaggregation | Sairaj Voruganti
Philip Bernstein, Microsoft Research | * Q. Zhang et al., [Understanding the Effect of Data Center Resource Disaggregation on Production DBMSs](https://doi.org/10.14778/3397230.3397249){:target="_blank"}, _Proc. VLDB Endowment_, 13(9): 1568-1581, 2020.
* Q. Zhang et al., [Redy: Remote Dynamic Memory Cache](https://doi.org/10.14778/3503585.3503587){:target="_blank"}, _Proc. VLDB Endowment_, 15(4): 766 - 779, 2022. (This is the paper to review)
* Q. Zhang et al., [CompuCache: Remote Computable Caching using Spot VMs](https://www.cidrdb.org/cidr2022/papers/p31-zhang.pdf){:target="_blank"}, In _Proc. Conference on Innovative Data Systems Research_, 2022 | Sairaj Slides
Phil Slides |
13 | 4/4 | Project presentations | Arman Davoodi & Emanuel Haque
Amin Setayesh & Sairaj Voruganti
Lasantha Fernando
Joseph Boulis, Brian Song & Guanqi Huang| Triangle Listing for graphs stored on disaggregated memory
Disaggregating Graph-based Vector Indexes
Data Stream Processing on FaaS with Memory Disaggregation
Elastic Memory Disaggregated System Architecture for Dynamic Workloads | Slides
Slides
Slides
Slides |
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