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Marina Lipshteyn

dblp:09/5333 · DBLP profile ↗
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18ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 13 · 1 first-authorComputer networks · 5 · 1 since 2021Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
2 papers
Datacenter networks · 95% Routing and switching · 5%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Storage systems · 77% Cloud and datacenter computing · 23%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Storage systems › networked storage › storage networking
RDMA storage
0.712023
Empowering Azure Storage with RDMA · NSDI 2023
Datacenter networks › lossless ethernet
priority flow control
0.522016
RDMA over Commodity Ethernet at Scale · SIGCOMM 2016
Congestion Control for Large-Scale RDMA Deployments · SIGCOMM 2015
Datacenter networks
RDMA
0.212015
Congestion Control for Large-Scale RDMA Deployments · SIGCOMM 2015
Datacenter networks › RDMA
RDMA congestion control
0.212015
Congestion Control for Large-Scale RDMA Deployments · SIGCOMM 2015
Cloud and datacenter computing
cloud storage
0.212023
Empowering Azure Storage with RDMA · NSDI 2023
Routing and switching › switching networks › multistage interconnection network
clos network
0.112015
Congestion Control for Large-Scale RDMA Deployments · SIGCOMM 2015
Graph algorithms and graph theory › graph classes
chordal graph
0.012004
Two tricks to triangulate chordal probe graphs in polynomial time · SODA 2004

Methods — techniques the papers use, named apart from their topics

monitoring · 0.2DSCP-based PFC · 0.2fluid model · 0.2end-to-end congestion control · 0.2polynomial-time algorithm · 0.0
YearPublicationVenuePosition
2023 Empowering Azure Storage with RDMA
Wei Bai 0001, Shanim Sainul Abdeen, Ankit Agrawal 0013, Krishan Kumar Attre, Paramvir Bahl, Ameya Bhagat, Gowri Bhaskara, Tanya Brokhman, Ahmad Cheema, Rebecca Chow, Jeff Cohen, Mahmoud Elhaddad, Vivek Ette, Igal Figlin, Daniel Firestone, Mathew George, Ilya German, Lakhmeet Ghai, Eric Green, Albert G. Greenberg, Randy Haagens, Matthew Hendel, Ridwan Howlader, Neetha John, Julia Johnstone, Tom Jolly, Greg Kramer, David Kruse, Erica Lan, Avi Levy, Marina Lipshteyn, Guohan Lu, Yuemin Lu, Xiakun Lu, Vadim Makhervaks, Ulad Malashanka, David A. Maltz, Ilias Marinos, Rohan Mehta, Sharda Murthi, Anup Namdhari, Aaron Ogus, Jitendra Padhye, Madhav Pandya, Douglas Phillips, Adrian Power, Suraj Puri, Shachar Raindel, Jordan Rhee, Anthony Russo, Maneesh Sah, Ali Sheriff, Chris Sparacino, Ashutosh Srivastava, Weixiang Sun, Nick Swanson, Fuhou Tian, Lukasz Tomczyk, Vamsi Vadlamuri, Alec Wolman, Joyce Yom, Yanzhao Zhang, Brian Zill
NSDI35
2016 RDMA over Commodity Ethernet at Scale
abstract
Over the past one and half years, we have been using RDMA over commodity Ethernet (RoCEv2) to support some of Microsoft's highly-reliable, latency-sensitive services. This paper describes the challenges we encountered during the process and the solutions we devised to address them. In order to scale RoCEv2 beyond VLAN, we have designed a DSCP-based priority flow-control (PFC) mechanism to ensure large-scale deployment. We have addressed the safety challenges brought by PFC-induced deadlock (yes, it happened!), RDMA transport livelock, and the NIC PFC pause frame storm problem. We have also built the monitoring and management systems to make sure RDMA works as expected. Our experiences show that the safety and scalability issues of running RoCEv2 at scale can all be addressed, and RDMA can replace TCP for intra data center communications and achieve low latency, low CPU overhead, and high throughput.
Chuanxiong Guo, Zhong Deng, Gaurav Soni, Jianxi Ye, Jitendra Padhye, Marina Lipshteyn
SIGCOMM7
2015 Congestion Control for Large-Scale RDMA Deployments
abstract
Modern datacenter applications demand high throughput (40Gbps) and ultra-low latency (< 10 μs per hop) from the network, with low CPU overhead. Standard TCP/IP stacks cannot meet these requirements, but Remote Direct Memory Access (RDMA) can. On IP-routed datacenter networks, RDMA is deployed using RoCEv2 protocol, which relies on Priority-based Flow Control (PFC) to enable a drop-free network. However, PFC can lead to poor application performance due to problems like head-of-line blocking and unfairness. To alleviates these problems, we introduce DCQCN, an end-to-end congestion control scheme for RoCEv2. To optimize DCQCN performance, we build a fluid model, and provide guidelines for tuning switch buffer thresholds, and other protocol parameters. Using a 3-tier Clos network testbed, we show that DCQCN dramatically improves throughput and fairness of RoCEv2 RDMA traffic. DCQCN is implemented in Mellanox NICs, and is being deployed in Microsoft's datacenters.
Yibo Zhu 0001, Haggai Eran, Daniel Firestone, Chuanxiong Guo, Marina Lipshteyn, Yehonatan Liron, Jitendra Padhye, Shachar Raindel, Mohamad Haj Yahia, Ming Zhang 0005
SIGCOMM5
2013 Single bend paths on a grid have strong helly number 4: errata atque emendationes ad "edge intersection graphs of single bend paths on a grid"
abstract
Abstract In this note, we prove that a collection of single bend paths on a grid, the so‐called B1 representations, have strong Helly number 4. This corrects a false claim from Ref. [Golumbic et al., Networks, 54 (2009), 130–138; and other errata are also corrected. © 2013 Wiley Periodicals, Inc. NETWORKS, 2013
Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
Networks2
2011 Foreword
Marina Lipshteyn, Ross M. McConnell, Haim Kaplan, Vadim E. Levit
Discret. Appl. Math.1
2010 On the bi-enhancement of chordal-bipartite probe graphs
Elad Cohen, Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
Inf. Process. Lett.3
2009 Intersection models of weakly chordal graphs
Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
Discret. Appl. Math.2
2009 Edge intersection graphs of single bend paths on a grid
abstract
Abstract We combine the known notion of the edge intersection graphs of paths in a tree with a VLSI grid layout model to introduce the edge intersection graphs of paths on a grid. Let 𝒫 be a collection of nontrivial simple paths on a grid 𝒢. We define the edge intersection graph E P G (𝒫) of 𝒫 to have vertices which correspond to the members of 𝒫, such that two vertices are adjacent in E P G (𝒫) if the corresponding paths in 𝒫 share an edge in 𝒢. An undirected graph G is called an edge intersection graph of paths on a grid (EPG) if G = E P G (𝒫) for some 𝒫 and 𝒢, and 〈𝒫,𝒢〉 is an EPG representation of G . We prove that every graph is an EPG graph. A turn of a path at a grid point is called a bend. We consider here EPG representations in which every path has at most a single bend, called B 1 ‐EPG representations and the corresponding graphs are called B 1 ‐EPG graphs. We prove that any tree is a B 1 ‐EPG graph. Moreover, we give a structural property that enables one to generate non B 1 ‐EPG graphs. Furthermore, we characterize the representation of cliques and chordless 4‐cycles in B 1 ‐EPG graphs. We also prove that single bend paths on a grid have Strong Helly number 3. © 2009 Wiley Periodicals, Inc. NETWORKS, 2009
Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
Networks2
2008 On the Bi-enhancement of Chordal-bipartite Probe Graphs
Elad Cohen, Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
CTW3
2008 What Is between Chordal and Weakly Chordal Graphs?
Elad Cohen, Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
WG3
2008 The k-edge intersection graphs of paths in a tree
Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
Discret. Appl. Math.2
2008 Equivalences and the complete hierarchy of intersection graphs of paths in a tree
Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
Discret. Appl. Math.2
2007 Edge intersection graphs of single bend paths on a grid
Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
CTW2
2007 Recognizing Chordal Probe Graphs and Cycle-Bicolorable Graphs
abstract
A graph $G=(V,E)$ is a chordal probe graph if its vertices can be partitioned into two sets, P (probes) and N (non-probes), where N is a stable set and such that G can be extended to a chordal graph by adding edges between non-probes. We give several characterizations of chordal probe graphs, first, in the case of a fixed given partition of the vertices into probes and non-probes, and second, in the more general case where no partition is given. In both of these cases, our results are obtained by introducing new classes, namely, N-triangulatable graphs and cycle-bicolorable graphs. We give polynomial time recognition algorithms for each class. N-triangulatable graphs have properties similar to chordal graphs, and we characterize them using graph separators and using a vertex elimination ordering. For cycle-bicolorable graphs, which are shown to be perfect, we prove that any cycle-bicoloring of a graph renders it N-triangulatable. The corresponding recognition complexity for chordal probe graphs, given a partition of the vertices into probes and non-probes, is $O(|P||E|)$, thus also providing an interesting tractable subcase of the chordal graph sandwich problem. If no partition is given in advance, the complexity of our recognition algorithm is $O(|E|^2)$.
Anne Berry, Martin Charles Golumbic, Marina Lipshteyn
SIAM J. Discret. Math.3
2006 Finding Intersection Models of Weakly Chordal Graphs
Martin Charles Golumbic, Marina Lipshteyn, Michal Stern
WG2
2004 Two tricks to triangulate chordal probe graphs in polynomial time
Anne Berry, Martin Charles Golumbic, Marina Lipshteyn
SODA3
2004 Chordal probe graphs
Martin Charles Golumbic, Marina Lipshteyn
Discret. Appl. Math.2
2003 Chordal Probe Graphs
Martin Charles Golumbic, Marina Lipshteyn
WG2