Introduction

Introduction

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

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.

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)

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

Distributed Systems

To Read List

  1. ​

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

Theory

To Read List

  1. ​