Sriram Rao

TL;DR: This work presents Tetris, a cluster scheduler that packs, i.e., matches multi-resource task requirements with resource availabilities of machines so as to increase cluster efficiency (makespan).

TL;DR: Morpheus is a new system that codifies implicit user expectations as explicit Service Level Objectives (SLOs) inferred from historical data, enforces SLOs using novel scheduling techniques that isolate jobs from sharing-induced performance variability, and mitigates inherent performance variance by means of dynamic reprovisioning of jobs.

TL;DR: Corral is a scheduling framework that uses characteristics of future workloads to determine an offline schedule which jointly places data and compute to achieve better data locality, and isolates jobs both spatially (by scheduling them in different parts of the cluster) and temporally, improving their performance.

TL;DR: A newcluster scheduler aimed at jobs that have a complex dependency structure and heterogeneous resource demands, which can compute a DAG schedule, offline, by first scheduling such troublesome tasks and then scheduling the remaining tasks without violating dependencies.

TL;DR: The Quantcast File System is an efficient alternative to the Hadoop Distributed File System that offers several efficiency improvements relative to HDFS: 50% disk space savings through erasure coding instead of replication, a resulting doubling of write throughput, a faster name node, support for faster sorting and logging through a concurrent append feature, and global feedback-directed I/O device management.