1. Introduction

This website hosts my notes for papers that I've read. ‌

Disclaimer: These notes shared here are by no means professional nor accurate. I'm simply sharing my thoughts at the exact time when I read this paper with my limited background.

2. Related Course Notes

1. CS 245 Principles of Data-Intensive Systems @ Stanford
2. CSE 599W Systems for ML @ UW
3. Distributed ML by Tie-Yan Liu (in Chinese)

3. Databases

1. Staring into the Abyss: An Evaluation of Concurrency Control with One Thousand Cores
2. Calvin: Fast Distributed Transactions for Partitioned Database Systems
3. A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics
4. Q100: The Architecture and Design of a Database Processing Unit
5. Managing Non-Volatile Memory in Database Systems
6. Write-Behind Logging
7. Joins in a Heterogeneous Memory Hierarchy: Exploiting High-Bandwidth Memory
8. Query Processing on Smart SSDs: Opportunities and Challenges
9. Database Processing-in-Memory: An Experimental Study
10. The End of Slow Networks: It's Time for a Redesign
11. Rethinking Database High Availability with RDMA Networks
12. Offloading Distributed Applications onto SmartNICs using iPipe
13. Distributed Join Algorithms on Thousands of Cores
14. Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational
15. Choosing A Cloud DBMS: Architectures and Tradeoffs
16. The Snowflake Elastic Data Warehouse
17. Starling: A Scalable Query Engine on Cloud Function Services
18. HyPer: A Hybrid OLTP&OLAP Main Memory Database System Based on Virtual Memory
19. Gorilla: A Fast, Scalable, In-Memory Time Series Database
20. Adaptive Concurrency Control: Despite the Looking Glass, One Concurrency Control Does Not Fit All
21. Toward Coordination-Free and Reconfigurable Mixed Concurrency Control

To Read List

4. Distributed Systems

To Read List

5. ML & Big Data Systems

To Read List

1. Themis: Fair and Efficient GPU Cluster Scheduling - NSDI 2020
2. Blink: Fast and Generic Collectives for Distributed ML - MLSys 2020
3. Accelerating Deep Learning Inference via Freezing - HotCloud 2019
4. Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads - USENIX ATC 2019

6. Theory

To Read List

1.