Random Notes
  • Introduction
  • Reading list
  • Theory
    • Index
      • Impossibility of Distributed Consensus with One Faulty Process
      • Time, Clocks, and the Ordering of Events in a Distributed System
      • Using Reasoning About Knowledge to analyze Distributed Systems
      • CAP Twelve Years Later: How the “Rules” Have Changed
      • A Note on Distributed Computing
  • Operating System
    • Index
  • Storage
    • Index
      • Tachyon: Reliable, Memory Speed Storage for Cluster Computing Frameworks
      • Exploiting Commutativity For Practical Fast Replication
      • Don’t Settle for Eventual: Scalable Causal Consistency for Wide-Area Storage with COPS
      • Building Consistent Transactions with Inconsistent Replication
      • Managing Update Conflicts in Bayou, a Weakly Connected Replicated Storage System
      • Spanner: Google's Globally-Distributed Database
      • Bigtable: A Distributed Storage System for Structured Data
      • The Google File System
      • Dynamo: Amazon’s Highly Available Key-value Store
      • Chord: A Scalable Peer-to-peer Lookup Service for Internet Applications
      • Replicated Data Consistency Explained Through Baseball
      • Session Guarantees for Weakly Consistent Replicated Data
      • Flat Datacenter Storage
      • Small Cache, Big Effect: Provable Load Balancing forRandomly Partitioned Cluster Services
      • DistCache: provable load balancing for large-scale storage systems with distributed caching
      • Short Summaries
  • Coordination
    • Index
      • Logical Physical Clocks and Consistent Snapshots in Globally Distributed Databases
      • Paxos made simple
      • ZooKeeper: Wait-free coordination for Internet-scale systems
      • Just Say NO to Paxos Overhead: Replacing Consensus with Network Ordering
      • Keeping CALM: When Distributed Consistency is Easy
      • In Search of an Understandable Consensus Algorithm
      • A comprehensive study of Convergent and Commutative Replicated Data Types
  • Fault Tolerance
    • Index
      • The Mystery Machine: End-to-end Performance Analysis of Large-scale Internet Services
      • Gray Failure: The Achilles’ Heel of Cloud-Scale Systems
      • Capturing and Enhancing In Situ System Observability for Failure Detection
      • Check before You Change: Preventing Correlated Failures in Service Updates
      • Efficient Scalable Thread-Safety-Violation Detection
      • REPT: Reverse Debugging of Failures in Deployed Software
      • Redundancy Does Not Imply Fault Tolerance
      • Fixed It For You:Protocol Repair Using Lineage Graphs
      • The Good, the Bad, and the Differences: Better Network Diagnostics with Differential Provenance
      • Lineage-driven Fault Injection
      • Short Summaries
  • Cloud Computing
    • Index
      • Improving MapReduce Performance in Heterogeneous Environments
      • CLARINET: WAN-Aware Optimization for Analytics Queries
      • MapReduce: Simplified Data Processing on Large Clusters
      • Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks
      • Resource Management
      • Apache Hadoop YARN: Yet Another Resource Negotiator
      • Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center
      • Dominant Resource Fairness: Fair Allocation of Multiple Resource Types
      • Large-scale cluster management at Google with Borg
      • MapReduce Online
      • Delay Scheduling: A Simple Technique for Achieving Locality and Fairness in Cluster Scheduling
      • Reining in the Outliers in Map-Reduce Clusters using Mantri
      • Effective Straggler Mitigation: Attack of the Clones
      • Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing
      • Discretized Streams: Fault-Tolerant Streaming Computation at Scale
      • Sparrow: Distributed, Low Latency Scheduling
      • Making Sense of Performance in Data Analytics Framework
      • Monotasks: Architecting for Performance Clarity in Data Analytics Frameworks
      • Drizzle: Fast and Adaptable Stream Processing at Scale
      • Naiad: A Timely Dataflow System
      • The Dataflow Model:A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale
      • Interruptible Tasks:Treating Memory Pressure AsInterrupts for Highly Scalable Data-Parallel Program
      • PACMan: Coordinated Memory Caching for Parallel Jobs
      • Multi-Resource Packing for Cluster Schedulers
      • Other interesting papers
  • Systems for ML
    • Index
      • A Berkeley View of Systems Challenges for AI
      • Tiresias: A GPU Cluster Managerfor Distributed Deep Learning
      • Gandiva: Introspective Cluster Scheduling for Deep Learning
      • Workshop papers
      • Hidden Technical Debt in Machine Learning Systems
      • Inference Systems
      • Parameter Servers and AllReduce
      • Federated Learning at Scale - Part I
      • Federated Learning at Scale - Part II
      • Learning From Non-IID data
      • Ray: A Distributed Framework for Emerging AI Applications
      • PipeDream: Generalized Pipeline Parallelism for DNN Training
      • DeepXplore: Automated Whitebox Testingof Deep Learning Systems
      • Distributed Machine Learning Misc.
  • ML for Systems
    • Index
      • Short Summaries
  • Machine Learning
    • Index
      • Deep Learning with Differential Privacy
      • Accelerating Deep Learning via Importance Sampling
      • A Few Useful Things to Know About Machine Learning
  • Video Analytics
    • Index
      • Scaling Video Analytics on Constrained Edge Nodes
      • Focus: Querying Large Video Datasets with Low Latency and Low Cost
      • NoScope: Optimizing Neural Network Queriesover Video at Scale
      • Live Video Analytics at Scale with Approximation and Delay-Tolerance
      • Chameleon: Scalable Adaptation of Video Analytics
      • End-to-end Learning of Action Detection from Frame Glimpses in Videos
      • Short Summaries
  • Networking
    • Index
      • Salsify: Low-Latency Network Video through Tighter Integration between a Video Codec and a Transport
      • Learning in situ: a randomized experiment in video streaming
      • Short Summaries
  • Serverless
    • Index
      • Serverless Computing: One Step Forward, Two Steps Back
      • Encoding, Fast and Slow: Low-Latency Video Processing Using Thousands of Tiny Threads
      • SAND: Towards High-Performance Serverless Computing
      • Pocket: Elastic Ephemeral Storage for Serverless Analytics
      • Fault-tolerant and Transactional Stateful Serverless Workflows
  • Resource Disaggregation
    • Index
  • Edge Computing
    • Index
  • Security/Privacy
    • Index
      • Differential Privacy
      • Honeycrisp: Large-Scale Differentially Private Aggregation Without a Trusted Core
      • Short Summaries
  • Misc.
    • Index
      • Rate Limiting
      • Load Balancing
      • Consistency Models in Distributed System
      • Managing Complexity
      • System Design
      • Deep Dive into the Spark Scheduler
      • The Actor Model
      • Python Global Interpreter Lock
      • About Research and PhD
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  • Big Data Systems
  • Resource Management
  • Scheduling
  • Storage
  • Fault Tolerance
  • Misc.

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  1. Cloud Computing

Index

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Last updated 4 years ago

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Big Data Systems

  • - Dean et al., OSDI '04 []

  • - Isard et al., EuroSys '07 []

  • - Condie et al., NSDI '10 []

  • (Spark) - Zaharia et al., NSDI '12 []

  • - Murray et al., SOSP '13 []

  • - Zaharia et al., SOSP '13 []

  • - Akidau et al., VLDB '15 []

  • - Hindman et al., NSDI '11 []

  • - Ghodsi et al., NSDI '11[Summary]

  • - Ananthanarayanan et al., NSDI '12 []

  • - Vavilapallih et al., SoCC '13 []

  • - Ousterhout et al., SOSP '15 []

  • - Verma et al., EuroSys '15 []

  • - Rasley et al., EuroSys '16 []

  • -Jyothi et al., OSDI '16

  • - Burns et al., ACM Queue '16

  • - Hongzi et al., SIGCOMM '19

Scheduling

Storage

Fault Tolerance

Misc.

- Zaharia et al., EuroSys '10 []

- Ousterhout et al., SOSP '13 []

- Grandl et al., SIGCOMM '14 []

- Viswanathan et al., OSDI '16 []

- Ousterhout et al., SOSP '17 []

- Venkataraman et al., SOSP '17 []

- Nightingale et al., OSDI '12 []

- Li et al., SoCC '14 []

- Rashmi et al., OSDI '16

- Zaharia et al., OSDI '08 []

- Ananthanarayanan et al., OSDI '10 []

- Ananthanarayanan et al., NSDI '13 []

- Fang et al., SOSP '15 []

- Wang et al., SOSP '19 []

- Goiri et al., ASPLOS '15

- Nguyen et al., OSDI '16

MapReduce: Simplified Data Processing on Large Clusters
Summary
Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks
Summary
MapReduce Online
Summary
Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing
Summary
Naiad: A Timely Dataflow System
Summary
Discretized Streams: Fault-Tolerant Streaming Computation at Scale
Summary
The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale
Summary
Resource Management
Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center
Summary
Dominant Resource Fairness
PACMan: Coordinated Memory Caching for Parallel Jobs
Summary
Apache Hadoop YARN: Yet Another Resource Negotiator
Summary
Making Sense of Performance in Data Analytics Framework
Summary
Large-scale cluster management at Google with Borg
Summary
Efficient Queue Management for Cluster Scheduling
Summary
Morpheus: Towards Automated SLOs for Enterprise Clusters
Borg, Omega, and Kubernetes
Learning Scheduling Algorithms for Data Processing Clusters
Delay Scheduling: A Simple Technique for Achieving Locality and Fairness in Cluster Scheduling
Summary
Sparrow: Distributed, Low Latency Scheduling
Summary
Multi-Resource Packing for Cluster Schedulers
Summary
CLARINET: WAN-Aware Optimization for Analytics Queries
Summary
Monotasks: Architecting for Performance Clarity in Data Analytics Frameworks
Summary
Drizzle: Fast and Adaptable Stream Processing at Scale
Summary
Flat Datacenter Storage
Summary
Tachyon: Reliable, Memory Speed Storage for Cluster Computing Frameworks
Summary
EC-Cache: Load-balanced, Low-latency Cluster Caching with Online Erasure Coding
Improving MapReduce Performance in Heterogeneous Environments
Summary
Reining in the Outliers in Map-Reduce Clusters using Mantri
Summary
Effective Straggler Mitigation: Attack of the Clones
Summary
Interruptible Tasks: Treating Memory Pressure AsInterrupts for Highly Scalable Data-Parallel Program
Summary
Lineage Stash: Fault Tolerance Off the Critical Path
Summary
ApproxHadoop: Bringing Approximations to MapReduce Frameworks
Yak: A High-Performance Big-Data-Friendly Garbage Collector