2024

Below is a list of papers and books I’ve read in 2024.

Books

• * The Meditations of Marcus Aurelius
• A Sorceress Comes to Call by T. Kingfisher
• Project Hail Mary by Andy Weir
• King, Warrior, Magician, Lover by Robert Moore by Douglas Gillette
• * Walden by Henry David Thoreau
• * Endurance by Alfred Lansing
• * Ikigai: The Japanese Secret to a Long and Happy Life by Héctor García, Francesc Miralles
• Clearer, Closer, Better: How Successful People See the World by Emily Balcetis
• Tress of the Emerald Sea: A Cosmere Novel by Brandon Sanderson
• * Relentless: From Good to Great to Unstoppable by Tim Grover, Shari Wenk
• The Three-Body Problem Series by Cixin Liu
  • The Three-Body Problem
  • The Dark Forest
  • Death’s End
• The Mountain Is You: Transforming Self-Sabotage Into Self-Mastery
• Bushido, The Soul Of Japan by Inazo Nitobe
• * A Psalm for the Wild-Built: A Monk and Robot Book (Monk & Robot, 1) by Becky Chambers
• * A Prayer for the Crown-Shy: A Monk and Robot Book (Monk & Robot, 2) by Becky Chambers

Blogs

• Rebuilding Netflix Video Processing Pipeline with Microservices
• Slack’s Migration to a Cellular Architecture
• Skeleton Key Gen AI Jailbreak
• Resource Management in Aurora Serverless
• Continuous reinvention: A brief history of block storage at AWS
• Life Lessons from the First Half-Century of My Career by David Patterson

Papers

DBMS

• What Goes Around Comes Around… And Around… by Michael Stonebraker and Andrew Pavlo
• Resource Management in Aurora Serverless

Job/Cluster Scheduling

• Apollo: Scalable and Coordinated Scheduling for Cloud-Scale Computing by Boutin, Microsoft Research et al
• Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center by Hindman, et al
• Hawk: Hybrid Datacenter Scheduling by Delgado, et al
• Apache Hadoop YARN: Yet Another Resource Negotiator by Vavilapallih, et al
• Tarcil: reconciling scheduling speed and quality in large shared clusters by Delimitrou, et al
• Large-scale cluster management at Google with Borg by Verma, et al
• Container Loading in AWS Lambda by Marc Brooker
• Quincy: Fair Scheduling for Distributed Computing Clusters by Isgard, et al
• Mercury: Hybrid Centralized and Distributed Scheduling in Large Shared Clusters by Karanasos, et al
• Sparrow: distributed, low latency scheduling by Ousterhout et al

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