paper-notebook's People
paper-notebook's Issues
CloudVisor: Retrofitting Protection of Virtual Machines in Multi-tenant Cloud with Nested Virtualization
Mastering the Game of Go with Deep Neural Network sand Tree Search
Alphago
All File Systems Are Not Created Equal: On the Complexity of Crafting Crash-Consistent Applications
Omega: flexible, scalable schedulers for large compute clusters
OSDI 2018: RobinHood: Tail Latency Aware Caching - Dynamic Reallocation from Cache-Rich to Cache-Poor.
In Search of an Understandable Consensus Algorithm
Bigtable: A Distributed Storage System for Structured Data
Paper
Large-scale cluster management at Google with Borg
Apollo: Scalable and Coordinated Scheduling for Cloud-Scale Computing
Apache Hadoop YARN: Yet Another Resource Negotiator
Omega: flexible, scalable schedulers for large compute clusters
Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center
SOSP 2017 My VM is Lighter (and Safer) than your Container
Apache Hadoop YARN: Yet Another Resource Negotiator
The Google File System
Paxos Made Simple
Abstract
The Paxos algorithm, when presented in plain English, is very simple
A Fast File System for Unix
1984年发表,在硬盘block增大时,对文件系统的一些优化。
Apollo: Scalable and Coordinated Scheduling for Cloud-Scale Computing
MapReduce: Simplified DataProcessingonLargeClusters
Large-scale cluster management at Google with Borg
假期里读的一篇paper,描述了Borg怎么做集群管理。
简单易懂,但又没什么干货,不知道怎么做到支持10K这个数量级,这算是一个相当大的集群了。也不知道单点故障怎么转移,尤其是有状态服务。
调度器选择节点时,不会检查所有节点,先随机的选择一些节点,再在这个集合里面找满足条件的节点去 分配任务。
任务是用Paxos一致性存储算法,维护一个任务队列。
Borg是Master/Slave,要支持大量节点,Master的资源需求很大,10~14个cpu core, up to 50 GiB RAM。Master有五个副本,里面会选举leader。
Lisp: Good News, Bad News, How to Win Big
cse课程内容
Dominant Resource Fairness: Fair Allocation of Multiple Resource Types
看调度器的时候,文章里提到的一种算法。
Fast and Concurrent RDF Queries with RDMA- Based Distributed Graph Exploration
Eraser: A Dynamic Data Race Detector for Multithreaded Programs
happens-before
https://blog.csdn.net/zdxiq000/article/details/60874848
Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center
《容器即服务》中关于mesos的部分:
两级调度器,主从架构,Zookeeper做存储(Paxos算法,这个应该相当etcd),
虽然很早就支持了容器,但是之前的设计并未如容器那样独立(磁盘共享)
Marathon是其上一种流行服务框架。
服务框架指“运行在Mesos内核上的一种程序”。
看起来就像是两级调度的第二级,第一级是Mesos master。
可以自己编写服务框架,大体上有调度器和执行器就可以,但它也可以有web界面等一切其他组件。
Marathon读取外部配置,执行任务。(有点像kubelet)
Spark、Kafka、Aurora、Swan都可以作为服务框架使用。
相对来说,Mesos比较笨重,不够容器化,部署也烦琐。
但发展比较久,能统一多种计算框架。
Ekiden: A Platform for Confidentiality-Preserving, Trustworthy, and Performant Smart Contract Execution,
REM: Resource-Efficient Mining for Blockchains
Scaling Multicore Databases via Constrained Parallel Execution
Fast in-memory transaction processing using RDMA and HTM
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