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The case for RAMClouds

John Ousterhout, Mendel Rosenblum, Stephen M. Rumble, Eric Stratmann, Ryan Stutsman, Parag Agrawal, David Erickson, Christos Kozyrakis, Jacob Leverich, David Mazières, Subhasish Mitra, Aravind Narayanan (+1 others)
2010 ACM SIGOPS Operating Systems Review  
This paper argues for a new approach to datacenter storage called RAMCloud, where information is kept entirely in DRAM and large-scale systems are created by aggregating the main memories of thousands  ...  We believe that RAMClouds can provide durable and available storage with 100-1000x the throughput of disk-based systems and 100-1000x lower access latency.  ...  In each case the total requirements are no more than a few terabytes, which would fit in a modestsized RAMCloud.  ... 
doi:10.1145/1713254.1713276 fatcat:vwlxzupmjncujmruqaes4bulee

The case for RAMCloud

John Ousterhout, Guru Parulkar, Mendel Rosenblum, Stephen M. Rumble, Eric Stratmann, Ryan Stutsman, Parag Agrawal, David Erickson, Christos Kozyrakis, Jacob Leverich, David Mazières, Subhasish Mitra (+2 others)
2011 Communications of the ACM  
A new class of storage called RAMCloud will provide the storage substrate for many future applications.  ...  the primary storage location for online information in computer systems.  ...  the case for ramcloud memories of commodity servers and uses hundreds or thousands of these servers to create a large-scale storage system.  ... 
doi:10.1145/1965724.1965751 fatcat:nmp2qlgjfvcivhx3fwegyegvuq

An Empirical Evaluation of How the Network Impacts the Performance and Energy Efficiency in RAMCloud

Yacine Taleb, Shadi Ibrahim, Gabriel Antoniu, Toni Cortes
2017 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)  
Through a study carried on RAMCloud, we focus on two settings: 1) clients are collocated within the same network as the storage servers (with Infiniband interconnects); 2) clients access the servers from  ...  We compare and discuss aspects related to scalability and power consumption for these two scenarios which correspond to different deployment models for applications making use of in-memory cloud storage  ...  for accessing RAMCloud.  ... 
doi:10.1109/ccgrid.2017.127 dblp:conf/ccgrid/TalebIAC17 fatcat:sqfmdzvgcncfffylubnc6zgviy

Large-Scale Merging of Histograms using Distributed In-Memory Computing

Jakob Blomer, Gerardo Ganis
2015 Journal of Physics, Conference Series  
The running time for distributed merging depends not only on the overall number of bins but also on the number partial histogram output files.  ...  Most high-energy physics analysis jobs are embarrassingly parallel except for the final merging of the output objects, which are typically histograms.  ...  Acknowledgments We would like to thank John Ousterhout and the RAMCloud team at Stanford University for hosting one of the authors and for numerous suggestions and stimulating discussions.  ... 
doi:10.1088/1742-6596/664/9/092003 fatcat:vsghcpr6mja7jivslh5vlxldmq

Fast crash recovery in RAMCloud

Diego Ongaro, Stephen M. Rumble, Ryan Stutsman, John Ousterhout, Mendel Rosenblum
2011 Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles - SOSP '11  
The system uses a log-structured approach for all its data, in DRAM as well as on disk; this provides high performance both during normal operation and during recovery.  ...  RAMCloud uses both data parallelism and pipelining to speed up recovery. • Log-structured storage: RAMCloud uses techniques similar to those from log-structured file systems [21] , not just for information  ...  In the configuration used for RAMCloud, the memory overhead for tablet profiles is 0.6% in the worst case (8 levels of bucket array for 8 MB of data).  ... 
doi:10.1145/2043556.2043560 dblp:conf/sosp/OngaroRSOR11 fatcat:iglpm5pr55eajbwylbjhpebxe4

Characterizing Performance and Energy-Efficiency of the RAMCloud Storage System

Yacine Taleb, Shadi Ibrahim, Gabriel Antoniu, Toni Cortes
2017 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS)  
We reveal that although RAMCloud is scalable for read-only applications, it exhibits non-proportional power consumption.  ...  We also find that the current replication scheme implemented in RAMCloud limits the performance and results in high energy consumption.  ...  As we already explained in section II, RAMCloud monopolizes one core for its polling mechanism, which results in our case in a 25% CPU usage even when the system is idle.  ... 
doi:10.1109/icdcs.2017.51 dblp:conf/icdcs/TalebIAC17 fatcat:pa7s2k6v4zgu5oa5ldz6vqqfbi

The RAMCloud Storage System

John Ousterhout, Mendel Rosenblum, Stephen Rumble, Ryan Stutsman, Stephen Yang, Arjun Gopalan, Ashish Gupta, Ankita Kejriwal, Collin Lee, Behnam Montazeri, Diego Ongaro, Seo Jin Park (+1 others)
2015 ACM Transactions on Computer Systems  
In many cases, DRAM is used as a cache for some other storage system, such as a database; this approach forces developers to manage consistency between the cache and the backing store, and its performance  ...  In other cases, DRAM is managed in an application-specific fashion, which provides high performance but at a high complexity cost for developers.  ...  This eliminated the need to write code for the "rejoin" case.  ... 
doi:10.1145/2806887 fatcat:fg3r5yahbjhxhcor6m2w2q6bxy

Implementing linearizability at large scale and low latency

Collin Lee, Seo Jin Park, Ankita Kejriwal, Satoshi Matsushita, John Ousterhout
2015 Proceedings of the 25th Symposium on Operating Systems Principles - SOSP '15  
We have implemented RIFL in the RAMCloud storage system and used it to make basic operations such as writes and atomic increments linearizable; RIFL adds only 530 ns to the 13.5 µs base latency for durable  ...  We also used RIFL to construct a new multi-object transaction mechanism in RAMCloud; RIFL's facilities significantly simplified the transaction implementation.  ...  The presentation in the paper benefited from comments by the anonymous conference reviewers and our shepherd, Steven Hand.  ... 
doi:10.1145/2815400.2815416 dblp:conf/sosp/LeePKMO15 fatcat:scbxjbbosrdg7jxcwirz4vrerm

Stateless Network Functions

Murad Kablan, Blake Caldwell, Richard Han, Hani Jamjoom, Eric Keller
2015 Proceedings of the 2015 ACM SIGCOMM Workshop on Hot Topics in Middleboxes and Network Function Virtualization - HotMiddlebox '15  
Our Click-based prototype integrates with RAMCloud; using NAT as an example network function, we demonstrate that we are able to create stateless network functions that maintain the desired performance  ...  This state separation is enabling these applications to be more agile and support the so-called continuous deployment model.  ...  ACKNOWLEDGEMENTS This work was funded in part by the following grants: NSF NeTS 1320389 and NSF XPS 1337399.  ... 
doi:10.1145/2785989.2785993 dblp:conf/sigcomm/KablanCHJK15 fatcat:grtdkb4xezemlbjymjjifu6kdm


Prapti Panigrahi .
2018 International Journal of Research in Engineering and Technology  
The cloud computing model allows for pay-by-use and thus avoids usage of personal computers or local servers.  ...  It is implemented by a connected network of remote servers, accessed via the internet, for processing, storing and managing data.  ...  Guaranteed Write RAMCloud is not the good choice for such requirement as in case of the main memory crash (DRAM crash), data will not be written.  ... 
doi:10.15623/ijret.2018.0710007 fatcat:q54suv7n6jcanieoqwotohdl7u

Improving Memory Access Performance of In-Memory Key-Value Store Using Data Prefetching Techniques [chapter]

PengFei Zhu, GuangYu Sun, Peng Wang, MingYu Chen
2015 Lecture Notes in Computer Science  
In addition, we also demonstrate the overhead of prefetching on power consumption.  ...  As memory technologies advance, IMKVs become practical for modern Big Data processing, which include financial services, e-commerce, telecommunication network, etc.  ...  For example, the first several bytes of value data in RAMCloud contains the size information.  ... 
doi:10.1007/978-3-319-23216-4_1 fatcat:5d32fhzperd3xkrmo3n5lpa4oa

Exploiting Commutativity For Practical Fast Replication [article]

Seo Jin Park, John Ousterhout
2017 arXiv   pre-print
This strategy allows most operations to complete in 1 RTT (the same as an unreplicated system). We implemented CURP in the Redis and RAMCloud storage systems.  ...  Compared to unreplicated RAMCloud, CURP's latency overhead for 3-way replication is just 0.4 us (6.9 us vs 7.3 us).  ...  Read operations in CURP may have to wait for the backup sync of the value being read. In the worst-case, one update can block multiple concurrent reads on the same object.  ... 
arXiv:1710.09921v1 fatcat:ox5t6b2jmnfi3cy4mvczjwydt4

FluidMem: Memory as a Service for the Datacenter [article]

Blake Caldwell, Youngbin Im, Sangtae Ha, Richard Han, Eric Keller
2017 arXiv   pre-print
Recent work has begun to explore memory disaggregation, but suffers limitations including lack of consideration of the complexity of cloud-based deployment, including heterogeneous hardware and APIs for  ...  We define the requirements of Memory as a Service and build its implementation in Linux as FluidMem.  ...  Additionally, we would like the thank William Mortl, Kannan Subramanian, and Daniel Zurawski for their work on this project.  ... 
arXiv:1707.07780v1 fatcat:thnnbfklg5bmxgnwg4ngtddoly


Djob Mvondo, Mathieu Bacou, Kevin Nguetchouang, Lucien Ngale, Stéphane Pouget, Josiane Kouam, Renaud Lachaize, Jinho Hwang, Tim Wood, Daniel Hagimont, Noël De Palma, Bernabé Batchakui (+1 others)
2021 Proceedings of the Sixteenth European Conference on Computer Systems  
Using machine learning models adjusted for typical function input data categories (e.g., multimedia formats), OFC estimates the actual memory resources required by each function invocation and hoards the  ...  To mitigate this issue, we introduce OFC, a transparent, vertically and horizontally elastic in-memory caching system for FaaS platforms, distributed over the worker nodes.  ...  Acknowledgments We thank our shepherd and the anonymous reviewers for their insightful feedback. Experiments presented in this paper were carried out using the Grid'5000 testbed 5 .  ... 
doi:10.1145/3447786.3456239 fatcat:jdpn6y6ngbgt5bqmkhtbkojnra

Fiber-based architecture for NFV cloud databases

Vaidas Gasiunas, Alexander Nozdrin, Weijie Ou, Nir Pachter, Dima Sivov, Eliezer Levy, David Dominguez-Sal, Ralph Acker, Aharon Avitzur, Ilan Bronshtein, Rushan Chen, Eli Ginot (+2 others)
2017 Proceedings of the VLDB Endowment  
The scalability of the databases (DBs) underlying the virtual network functions is the cornerstone for reaping the benefits from the NFV transformation.  ...  We further show that the fiber-based approach outperforms the approach built using conventional multi-threading and meets the variable deployment needs of the NFV transformation.  ...  We observe that the multithreaded model scales up to a few cores: two in the case of inserts and five for updates.  ... 
doi:10.14778/3137765.3137774 fatcat:tlzqna6ukzdy7f7mfqz3qtsipu
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