Mosharaf
TAing for CS162: Operating Systems and Systems Programming
This semester I’m TAing for CS162: Operating Systems and Systems Programming taught by Anthony Joseph and Ion Stoica. Here in Berkeley, we call a TA a GSI (Graduate Student Instructor). This is my first time GSI appointment in Berkeley, and it comes after more than 2 years of break. The last time I TAed, I was in ...
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Spark has been accepted at NSDI’2012
Our paper “Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing” has been accepted at NSDI’2012. This is Matei‘s brainchild and a joint work of a lot of people including, but not limited to, TD, Ankur, Justin, Murphy, and professors Ion Stoica, Scott Shenker, and Michael Franklin. Unlike many other systems papers, Spark is ...
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Memory Management in the Cloud
Stanford, “The Case for RAMClouds: Scalable High-Performance Storage Entirely in DRAM,” SIGOPS Operating Systems Review, Vol. 43, No. 4, December 2009, pp. 92-105. [PDF] AMP Lab, “PACMan: Coordinated Memory Caching for Parallel Jobs,” Secret Draft. Update: PACMan has been accepted at NSDI’2012. Secret draft won’t remain secret anymore :) Summary Cloud applications require storage systems ...
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Confidentiality and Security in the Cloud
Raluca Ada Popa, Catherine M. S. Redfield, Nickolai Zeldovich, Hari Balakrishnan, “CryptDB: Protecting Confidentiality with Encrypted Query Processing,” SOSP, 2011. [PDF] Thomas Ristenpart, Eran Tromer, Hovav Shacham, Stefan Savage, “Hey, You, Get Off of My Cloud: Exploring Information Leakage in Third-Party Compute Clouds,” CCS, 2009. [PDF] Summary With the increase in popularity of cloud computing ...
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Graph-parallel frameworks
Google, “Pregel: A System for Large-Scale Graph Processing,” SIGMOD, 2010. [PDF] Carnegie Mellon, “GraphLab: A New Framework for Parallel Machine Learning,” arXiv:1006.4990, 2010. [PDF] Summary Data-parallel frameworks such as MapReduce and Dryad are good at performing embarrassingly parallel jobs. These frameworks are not ideal for iterative jobs and for jobs where data-dependencies across stages are ...
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Datacenter transport layer protocols
Stanford and Microsoft, “DCTCP: Efficient Packet Transport for the Commoditized Data Center,” SIGCOMM, 2010. [PDF] Raiciu et al, “Improving Datacenter Performance and Robustness with Multipath TCP,” SIGCOMM, 2011. [PDF] MSR Asia, ICTCP: Incast Congestion Control for TCP in Data Center Networks,” CoNEXT, 2010. [PDF] Summary Datacenters pose a different set of challenges than the Internet, ...
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Cloudy operating systems
MIT, An Operating System for Multicore and Clouds: Mechanisms and Implementation,” SOCC, 2010. [PDF] Barret Rhoden, Kevin Klues, David (Yu) Zhu, Eric Brewer, “Improving Per-Node Efficiency in the Datacenter with New OS Abstractions,” SOCC, 2011. [PDF] Summary Factored Operating System The Factored Operating System (FOS) proposes an OS architecture where each core runs individual microkernels ...
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Multi-framework resource managers for datacenters
AMPLab, “Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center,” NSDI, 2011. [PDF] Apache Software Foundation, “Hadoop NextGen”, 2011. [LINK] Summary Traditional cluster resource schedulers fall into two broad categories: some do fine-grained management of resources for individual frameworks (e.g., in Hadoop), but this requires multiple frameworks to run on multiple isolated clusters. ...
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Distributed in-memory datasets
AMPLab, “Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing,” UCB/EECS-2011-82, 2011. [PDF] Russell Power, Jinyang Li, “Piccolo: Building Fast, Distributed Programs with Partitioned Tables,” OSDI, 2010. [PDF] Summary MapReduce and similar frameworks, while widely applicable, are limited to directed acyclic data flow models, do not expose global states, and generally slow due to ...
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Cloud databases
MIT, “Relational Cloud: A Database-as-a-Service for the Cloud,” CIDR, 2011. [PDF] Divyakant Agrawal, Amr El Abbadi, Sudipto Das, Aaron J. Elmore, ”Database Scalability, Elasticity, and Autonomy in the Cloud,” DASFAA, 2011. [PDF] Relational Cloud The key idea of the Relational Cloud project is to define the concept of transactional Database-as-a-Service (DBaaS), identify the key challenges toward materializing ...
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