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Dive into the research topics where Amar Phanishayee is active.

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Featured researches published by Amar Phanishayee.


symposium on operating systems principles | 2009

FAWN: a fast array of wimpy nodes

David G. Andersen; Jason Franklin; Michael Kaminsky; Amar Phanishayee; Lawrence Tan; Vijay Vasudevan

This paper presents a new cluster architecture for low-power data-intensive computing. FAWN couples low-power embedded CPUs to small amounts of local flash storage, and balances computation and I/O capabilities to enable efficient, massively parallel access to data. The key contributions of this paper are the principles of the FAWN architecture and the design and implementation of FAWN-KV--a consistent, replicated, highly available, and high-performance key-value storage system built on a FAWN prototype. Our design centers around purely log-structured datastores that provide the basis for high performance on flash storage, as well as for replication and consistency obtained using chain replication on a consistent hashing ring. Our evaluation demonstrates that FAWN clusters can handle roughly 350 key-value queries per Joule of energy--two orders of magnitude more than a disk-based system.


acm special interest group on data communication | 2009

Safe and effective fine-grained TCP retransmissions for datacenter communication

Vijay Vasudevan; Amar Phanishayee; Hiral Shah; Elie Krevat; David G. Andersen; Gregory R. Ganger; Garth A. Gibson; Brian Mueller

This paper presents a practical solution to a problem facing high-fan-in, high-bandwidth synchronized TCP workloads in datacenter Ethernets---the TCP incast problem. In these networks, receivers can experience a drastic reduction in application throughput when simultaneously requesting data from many servers using TCP. Inbound data overfills small switch buffers, leading to TCP timeouts lasting hundreds of milliseconds. For many datacenter workloads that have a barrier synchronization requirement (e.g., filesystem reads and parallel data-intensive queries), throughput is reduced by up to 90%. For latency-sensitive applications, TCP timeouts in the datacenter impose delays of hundreds of milliseconds in networks with round-trip-times in microseconds. Our practical solution uses high-resolution timers to enable microsecond-granularity TCP timeouts. We demonstrate that this technique is effective in avoiding TCP incast collapse in simulation and in real-world experiments. We show that eliminating the minimum retransmission timeout bound is safe for all environments, including the wide-area.


acm/ieee international conference on mobile computing and networking | 2008

Ditto: a system for opportunistic caching in multi-hop wireless networks

Fahad R. Dogar; Amar Phanishayee; Himabindu Pucha; Olatunji Ruwase; David G. Andersen

This paper presents the design, implementation, and evaluation of Ditto, a system that opportunistically caches overheard data to improve subsequent transfer throughput in wireless mesh networks. While mesh networks have been proposed as a way to provide cheap, easily deployable Internet access, they must maintain high transfer throughput to be able to compete with other last-mile technologies. Unfortunately, doing so is difficult because multi-hop wireless transmissions interfere with each other, reducing the available capacity on the network. This problem is particularly severe in common gateway-based scenarios in which nearly all transmissions go through one or a few gateways from the mesh network to the Internet. Ditto exploits on-path as well as opportunistic caching based on overhearing to improve the throughput of data transfers and to reduce load on the gateways. It uses content-based naming to provide application independent caching at the granularity of small chunks, a feature that is key to being able to cache partially overheard data transfers. Our evaluation of Ditto shows that it can achieve significant performance gains for cached data, increasing throughput by up to 7x over simpler on-path caching schemes, and by up to an order of magnitude over no caching.


petascale data storage workshop | 2007

On application-level approaches to avoiding TCP throughput collapse in cluster-based storage systems

Elie Krevat; Vijay Vasudevan; Amar Phanishayee; David G. Andersen; Gregory R. Ganger; Garth A. Gibson; Srinivasan Seshan

TCP Incast plagues scalable cluster-based storage built atop standard TCP/IP-over-Ethernet, often resulting in much lower client read bandwidth than can be provided by the available network links. This paper reviews the Incast problem and discusses potential application-level approaches to avoiding it.


acm special interest group on data communication | 2016

ProjecToR: Agile Reconfigurable Data Center Interconnect

Monia Ghobadi; Ratul Mahajan; Amar Phanishayee; Nikhil R. Devanur; Janardhan Kulkarni; Gireeja Ranade; Pierre Alexandre Blanche; Houman Rastegarfar; Madeleine Glick; Daniel C. Kilper

We explore a novel, free-space optics based approach for building data center interconnects. It uses a digital micromirror device (DMD) and mirror assembly combination as a transmitter and a photodetector on top of the rack as a receiver (Figure 1). Our approach enables all pairs of racks to establish direct links, and we can reconfigure such links (i.e., connect different rack pairs) within 12 us. To carry traffic from a source to a destination rack, transmitters and receivers in our interconnect can be dynamically linked in millions of ways. We develop topology construction and routing methods to exploit this flexibility, including a flow scheduling algorithm that is a constant factor approximation to the offline optimal solution. Experiments with a small prototype point to the feasibility of our approach. Simulations using realistic data center workloads show that, compared to the conventional folded-Clos interconnect, our approach can improve mean flow completion time by 30-95% and reduce cost by 25-40%.


ubiquitous computing | 2013

Lab of things: a platform for conducting studies with connected devices in multiple homes

A. J. Bernheim Brush; Evgeni Filippov; Danny Huang; Jaeyeon Jung; Ratul Mahajan; Frank Martinez; Khurshed Mazhar; Amar Phanishayee; Arjmand Samuel; James Scott; Rayman Preet Singh

Researchers who develop new home technologies using connected devices often want to conduct large-scale field studies in homes to evaluate their technology, but conducting such studies today is extremely challenging. Inspired by the success of PlanetLab, which enabled development and evaluation of global network services, we are developing a shared infrastructure for home environments, called Lab of Things. Our goal is to substantially lower the barrier to developing and evaluating new technologies for the home environment.


conference on emerging network experiment and technology | 2009

Scaling all-pairs overlay routing

David Sontag; Yang Zhang; Amar Phanishayee; David G. Andersen; David R. Karger

This paper presents and experimentally evaluates a new algorithm for efficient one-hop link-state routing in full-mesh networks. Prior techniques for this setting scale poorly, as each node incurs quadratic (n2) communication overhead to broadcast its link state to all other nodes. In contrast, in our algorithm each node exchanges routing state with only a small subset of overlay nodes determined by using a quorum system. Using a two round protocol, each node can find an optimal one-hop path to any other node using only n1.5 per-node communication. Our algorithm can also be used to find the optimal shortest path of arbitrary length using only n1.5 logn per-node communication. The algorithm is designed to be resilient to both node and link failures. We apply this algorithm to a Resilient Overlay Network (RON) system, and evaluate the results using a large-scale, globally distributed set of Internet hosts. The reduced communication overhead from using our improved full-mesh algorithm allows the creation of all-pairs routing overlays that scale to hundreds of nodes, without reducing the systems ability to rapidly find optimal routes.


european conference on computer systems | 2017

Atomic In-place Updates for Non-volatile Main Memories with Kamino-Tx

Amirsaman Memaripour; Anirudh Badam; Amar Phanishayee; Yanqi Zhou; Ramnatthan Alagappan; Karin Strauss; Steven Swanson

Data structures for non-volatile memories have to be designed such that they can be atomically modified using transactions. Existing atomicity methods require data to be copied in the critical path which significantly increases the latency of transactions. These overheads are further amplified for transactions on byte-addressable persistent memories where often the byte ranges modified for data structure updates are significantly smaller compared to the granularity at which data can be efficiently copied and logged. We propose Kamino-Tx that provides a new way to perform transactional updates on non-volatile byte-addressable memories (NVM) without requiring any copying of data in the critical path. Kamino-Tx maintains an additional copy of data off the critical path to achieve atomicity. But in doing so Kamino-Tx has to overcome two important challenges of safety and minimizing NVM storage overhead. We propose a more dynamic approach to maintaining the additional copy of data to reduce storage overheads. To further mitigate the storage overhead of using Kamino-Tx in a replicated setting, we develop Kamino-Tx-Chain, a variant of Chain Replication where replicas perform in-place updates and do not maintain data copies locally; replicas in Kamino-Tx-Chain leverage other replicas as copies to roll back or forward for atomicity. Our results show that using Kamino-Tx increases throughput by up to 9.5x for unreplicated systems and up to 2.2x for replicated settings.


communication system software and middleware | 2007

Scalable Multicast Platforms for a New Generation of Robust Distributed Applications

Kenneth P. Birman; Mahesh Balakrishnan; Danny Dolev; Tudor Marian; Krzysztof Ostrowski; Amar Phanishayee

As distributed systems scale up and are deployed into increasingly sensitive settings, demand is rising for a new generation of communications middleware in support of application-level critical-computing uses. Ricochet, Tempest and Quicksilver are multicast-based systems developed to respond to this need. Ricochet and Quicksilver are multicast platforms; both are exceptionally scalable and support fault-tolerance properties that match closely with the needs of high-availability applications. Ricochet was designed to support time-critical applications replicated for scalability on data centers and clusters. These are typically coded in Java and run under Linux. Tempest is layered over Ricochet and automates most tasks of programming services for data centers. In contrast, Quicksilver focuses on high throughput and is targeted towards very large deployments of desktop computing systems, in support of publish-subscribe, event notification or media dissemination applications. In this paper we offer an overview of the systems and some of the new systems embeddings that, we believe, make them far easier to use than was the case in prior multicast platforms.


symposium on reliable distributed systems | 2006

PLATO: Predictive Latency-Aware Total Ordering

Mahesh Balakrishnan; Kenneth P. Birman; Amar Phanishayee

PLATO is a predictive total ordering protocol designed for low-latency multicast in datacenters. It predicts out-of-order arrival of multicast packets by observing their inter-arrival times, and delays packets before passing them up to the application only if it believes the packets to have arrived in the wrong order. We show through experimentation on real datacenter-style networks that the inter-arrival time of consecutive packet pairs is an excellent predictor of out-of-order delivery. We evaluate an implementation of PLATO on the Emulab testbed, and show that it drives down delivery latencies by more than a factor of 2 compared to the fixed-sequencer protocol

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David G. Andersen

Carnegie Mellon University

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Vijay Vasudevan

Carnegie Mellon University

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Elie Krevat

Carnegie Mellon University

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Garth A. Gibson

Carnegie Mellon University

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Gregory R. Ganger

Carnegie Mellon University

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Hiral Shah

Carnegie Mellon University

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