AMPLab Publications

• pHost: Distributed Near-Optimal Datacenter Transport Over Commodity Network Fabric
• Universal Packet Scheduling
• Making Sense of Performance in Data Analytics Frameworks
• Tachyon: Reliable, Memory Speed Storage for Cluster Computing Frameworks
• Discretized Streams: Fault-Tolerant Streaming Computation at Scale
• Tachyon: Memory Throughput I/O for Cluster Computing Frameworks
• The Case for Tiny Tasks in Compute Clusters
• Choosy: Proportional Sharing for Datacenter Jobs with Constraints
• Fast and Interactive Analytics over Hadoop Data with Spark
• Shark: SQL and Rich Analytics at Scale
• Discretized Streams: An Efficient and Fault-Tolerant Model for Stream Processing on Large Clusters
• Faster and More Accurate Sequence Alignment with SNAP
• PACMan: Coordinated Memory Caching for Parallel Jobs
• Shark: Fast Data Analysis Using Coarse-grained Distributed Memory (Best Demo Award)
• Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing (Best Paper Award)
• The Datacenter Needs an Operating System
• Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center
• Dominant Resource Fairness: Fair Allocation of Multiple Resources Types
• Spark: Cluster Computing with Working Sets
• Disk-Locality in Datacenter Computing Considered Irrelevant