Edi Shmueli

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15ranked-venue papers

8as first author

0since 2021 · last 2018

—ORCID · none

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

Systems, architecture and hardware · 10 · 7 first-authorSoftware engineering, systems software and programming languages · 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.

Software engineering, system software, and programming languages 1 paper		Software maintenance and evolution · 50% Empirical software engineering · 50%
Computer architecture, parallel and distributed computing, and storage systems 3 papers		Cloud and datacenter computing · 28% High-performance computing · 22% Performance modeling and evaluation · 22%

Topics — the 10 heaviest of 10, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Software maintenance and evolution › release engineering continuous integration	0.3	1	2017	Screening heuristics for project gating systems · ESEC/SIGSOFT FSE 2017
Empirical software engineering software defect prediction	0.3	1	2017	Screening heuristics for project gating systems · ESEC/SIGSOFT FSE 2017
Cloud and datacenter computing job scheduling	0.1	1	2009	On Simulation and Design of Parallel-Systems Schedulers: Are We Doing the Right Thing? · IEEE Trans. Parallel Distributed Syst. 2009
Performance modeling and evaluation › simulation › discrete-event simulation trace-driven simulation	0.1	1	2009	On Simulation and Design of Parallel-Systems Schedulers: Are We Doing the Right Thing? · IEEE Trans. Parallel Distributed Syst. 2009
Interconnection networks and networks-on-chip network topology	0.1	1	2008	Multitoroidal Interconnects For Tightly Coupled Supercomputers · IEEE Trans. Parallel Distributed Syst. 2008
High-performance computing › supercomputing bluegene/l	0.0	1	2002	An overview of the BlueGene/L Supercomputer · SC 2002
High-performance computing supercomputing	0.0	1	2002	An overview of the BlueGene/L Supercomputer · SC 2002
Integrated circuit design system-on-chip	0.0	1	2002	An overview of the BlueGene/L Supercomputer · SC 2002
Cloud and datacenter computing › cluster resource management and scheduling cluster resource management	0.0	1	2009	On Simulation and Design of Parallel-Systems Schedulers: Are We Doing the Right Thing? · IEEE Trans. Parallel Distributed Syst. 2009
High-performance computing › supercomputing supercomputing systems	0.0	1	2008	Multitoroidal Interconnects For Tightly Coupled Supercomputers · IEEE Trans. Parallel Distributed Syst. 2008

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

project gating heuristics · 0.3bug prediction · 0.3user modeling · 0.1site-level simulation · 0.1simulation · 0.1system architecture design · 0.0performance scaling studies · 0.0

Year	Publication	Venue	Position
2018	Framework for Scalable File System Metadata Crawling and Differencing Edi Shmueli, Ilya Zaides	J. Grid Comput.	1
2017	Screening heuristics for project gating systems abstract Continuous Integration (CI) is a hot topic. Yet, little attention is payed to how CI systems work and what impacts their behavior. In parallel, bug prediction in software is gaining high attention. But this is done mostly in the context of software engineering, and the relation to the realm of CI and CI systems engineering has not been established yet. In this paper we describe how Project Gating systems operate, which are a specific type of CI systems used to keep the mainline of development always clean. We propose and evaluate three heuristics for improving Gating performance and demonstrate their trade-offs. The third heuristic, which leverages state-of-the-art bug prediction achieves the best performance across the entire spectrum of workload conditions. Zahy Volf, Edi Shmueli	ESEC/SIGSOFT FSE	2
2016	Helping Protect Software Distribution with PSWD abstract The success of new technologies depends on whether proper usage models can be found to support them. In this paper we present such a model for Intel's Software Guard Extensions (SGX) -- the leveraging of the technology to provide copy protection to software. We describe the system that we architected, designed and implemented, which transforms, in a fully automated manner, off-the-shelve applications into secured versions that run on top of the enclaves. Our system can be delivered as stand-alone, but also as a layer in existing software copy protection stacks. Edi Shmueli, Sergey Goffman, Yoram Zahavi	SYSTOR	1
2013	Heuristics for Resource Matching in Intel's Compute Farm Ohad Shai, Edi Shmueli, Dror G. Feitelson	JSSPP	2
2009	A case for conservative workload modeling: Parallel job scheduling with daily cycles of activity abstract Computer workloads have many attributes. When modeling these workloads it is often difficult to decide which attributes are important, and which can be abstracted away. In many cases, the modeler only includes attributes that are believed to be important, and ignores the rest. We argue, however, that this can lead to impaired workloads and unreliable system evaluations. Using parallel job scheduling as a case study, and daily cycles of activity as the attribute in dispute, we present two schedulers whose simulated performance seems identical without cycles, but then becomes significantly different when daily cycles are included in the workload. We trace this to the ability of one scheduler to prioritize interactive jobs, which leads to implicitly delaying less critical work to nighttime, when it can utilize resources that otherwise would have been left idle. Notably, this was not a design feature of this scheduler, but rather an emergent property that was not anticipated in advance. Dror G. Feitelson, Edi Shmueli	MASCOTS	2
2009	On Simulation and Design of Parallel-Systems Schedulers: Are We Doing the Right Thing? abstract It is customary to use open-system trace-driven simulations to evaluate the performance of parallel-system schedulers. As a consequence, all schedulers have evolved to optimize the packing of jobs in the schedule, as a means to improve a number of performance metrics that are conjectured to be correlated with user satisfaction, with the premise that this will result in a higher productivity in reality. We argue that these simulations suffer from severe limitations that lead to suboptimal scheduler designs and to even dismissing potentially good design alternatives. We propose an alternative simulation methodology called site-level simulation, in which the workload for the evaluation is generated dynamically by user models that interact with the system. We present a novel scheduler called CREASY that exploits knowledge on user behavior to directly improve user satisfaction and compare its performance to the original packing-based EASY scheduler. We show that user productivity improves by up to 50 percent under the user-aware design, while according to the conventional metrics, performance may actually degrade. Edi Shmueli, Dror G. Feitelson	IEEE Trans. Parallel Distributed Syst.	1
2008	Evaluating the effect of replacing CNK with linux on the compute-nodes of blue gene/l abstract The Blue Gene machines in production today run a small single-user, single-process kernel (CNK) having a limited functionality. Motivated by the desire to provide applications with a much richer operating environment, we evaluate the effect of replacing CNK with a standard Linux kernel on the compute nodes of Blue Gene/L. We show that with a relatively small amount of effort we were able to improve benchmark performance under Linux up to a level that is comparable to CNK. Edi Shmueli, Gheorghe Almási 0001, José R. Brunheroto, José G. Castaños, Gábor Dózsa, Sameer Kumar 0001, Derek Lieber	ICS	1
2008	Multitoroidal Interconnects For Tightly Coupled Supercomputers abstract The processing elements of many modern tightly coupled multicomputers are connected via mesh or toroidal networks. Such interconnects are simple and highly scalable, but suffer from high fragmentation, low utilization, and insufficient fault tolerance when the resources allocated to each job are dedicated. High-dimensional interconnects may be more efficient in certain cases, but are based on complex and expensive components and scale poorly. We present a novel hardware/software architectural approach that detaches the processing elements of the system from the interconnect and augments the traditional toroidal topology to provide additional connectivity options and additional link redundancy. We explore the properties of the new "multitoroidal" topology and the improvements it offers in resource utilization and failure tolerance. We present the results of extensive simulation studies to show that for practically important types of workloads, the resource utilization may be increased by 50 percent and, in certain cases, as much as 100 percent compared to toroidal machines and is, in fact, close to the theoretically optimal case of a full crossbar interconnect. The combined hardware/software architectural innovation is a major significant improvement in resource utilization on top of the state of the art in scheduling algorithm research. Also, multitoroidal multicomputers are able to work under link failure rates of 0.002 failures per week that would shut down toroidal machines. A variant of the multitoroidal architecture is implemented in the Blue Gene/L supercomputer. Yariv Aridor, Tamar Domany, Oleg Goldshmidt, Yevgeny Kliteynik, Edi Shmueli, José E. Moreira	IEEE Trans. Parallel Distributed Syst.	5
2007	Uncovering the Effect of System Performance on User Behavior from Traces of Parallel Systems abstract Intuitively, it seems that understanding how the performance of a system affects its users requires research in psychology and the conducting of live experiments. We demonstrate that it is possible to uncover the effect from traces of the system. In particular, we found that the behavior of users of parallel systems is correlated with the response time of their jobs, not the slowdown as was previously assumed. We show that response times affect the decision of users to continue or abort their interactive session with the system, and that this may relate to expectations the users develop. Although this research was conducted in the context of parallel systems, we believe our results are more general and may pertain to other types of systems as well. Edi Shmueli, Dror G. Feitelson	MASCOTS	1
2006	Using Site-Level Modeling to Evaluate the Performance of Parallel System Schedulers abstract The conventional performance evaluation methodology for parallel system schedulers uses an open model to generate the workloads used in simulations. In many cases recorded workload traces are simply played back, assuming that they are reliable representatives of real workloads, and leading to the expectation that the simulation results actually predict the scheduler’s true performance. We show that the lack of feedback in these workloads results in performance prediction errors, which may reach hundreds of percents. We also show that load scaling, as currently performed, further ruins the representativeness of the workload, by generating conditions which cannot exist in a real environment. As an alternative, we suggest a novel sitelevel modeling evaluation methodology, in which we model not only the actions of the scheduler but also the activity of users who generate the workload dynamically. This advances the simulation in a manner that reliably mimics feedback effects found in real sites. In particular, saturation is avoided because the generation of additional work is throttled when the system is overloaded. While our experiments were conducted in the context of parallel scheduling, the idea of site-level simulation is applicable to many other types of systems. Edi Shmueli, Dror G. Feitelson	MASCOTS	1
2005	Open Job Management Architecture for the Blue Gene/L Supercomputer Yariv Aridor, Tamar Domany, Oleg Goldshmidt, Yevgeny Kliteynik, José E. Moreira, Edi Shmueli	JSSPP	6
2005	Backfilling with lookahead to optimize the packing of parallel jobs Edi Shmueli, Dror G. Feitelson	J. Parallel Distributed Comput.	1
2004	Multi-toroidal Interconnects: Using Additional Communication Links to Improve Utilization of Parallel Computers Yariv Aridor, Tamar Domany, Oleg Goldshmidt, Edi Shmueli, José E. Moreira, Larry Stockmeier	JSSPP	4
2003	Backfilling with Lookahead to Optimize the Performance of Parallel Job Scheduling Edi Shmueli, Dror G. Feitelson	JSSPP	1
2002	An overview of the BlueGene/L Supercomputer abstract This paper gives an overview of the BlueGene/L Supercomputer. This is a jointly funded research partnership between IBM and the Lawrence Livermore National Laboratory as part of the United States Department of Energy ASCI Advanced Architecture Research Program. Application performance and scaling studies have recently been initiated with partners at a number of academic and government institutions,including the San Diego Supercomputer Center and the California Institute of Technology. This massively parallel system of 65,536 nodes is based on a new architecture that exploits system-on-a-chip technology to deliver target peak processing power of 360 teraFLOPS (trillion floating-point operations per second). The machine is scheduled to be operational in the 2004-2005 time frame, at price/performance and power consumption/performance targets unobtainable with conventional architectures. Narasimha R. Adiga, Gheorghe Almási 0001, George S. Almási, Yariv Aridor, Rajkishore Barik, Daniel K. Beece, Ralph Bellofatto, Gyan Bhanot, Randy Bickford, Matthias A. Blumrich, Arthur A. Bright, José R. Brunheroto, Calin Cascaval, José G. Castaños, Waiman Chan, Luis Ceze, Paul Coteus, Siddhartha Chatterjee, Dong Chen 0005, George L.-T. Chiu, Thomas M. Cipolla, Paul Crumley, K. M. Desai, Alina Deutsch, Tamar Domany, Marc Boris Dombrowa, Wilm E. Donath, Maria Eleftheriou, C. Christopher Erway, J. Esch, Blake G. Fitch, Joseph Gagliano, Alan Gara, Rahul Garg 0001, Robert S. Germain, Mark Giampapa, Balaji Gopalsamy, John A. Gunnels, Manish Gupta 0002, Fred G. Gustavson, Shawn Hall, Ruud A. Haring, David F. Heidel, Philip Heidelberger, Lorraine M. Herger, Dirk Hoenicke, R. D. Jackson, T. Jamal-Eddine, Gerard V. Kopcsay, Elie Krevat, Manish P. Kurhekar, Alphonso P. Lanzetta, Derek Lieber, L. K. Liu, M. Lu, Mark P. Mendell, A. Misra, Yosef Moatti, Lawrence S. Mok, José E. Moreira, Ben J. Nathanson, Matthew Newton, Martin Ohmacht, Adam J. Oliner, Vinayaka Pandit, R. B. Pudota, Rick A. Rand, Richard D. Regan, Bradley Rubin, Albert E. Ruehli, Silvius Vasile Rus, Ramendra K. Sahoo, Alda Sanomiya, Eugen Schenfeld, M. Sharma, Edi Shmueli, Sarabjeet Singh, Peilin Song, Vijay Srinivasan, Burkhard D. Steinmacher-Burow, Karin Strauss, Christopher W. Surovic, Richard A. Swetz, Todd Takken, R. Brett Tremaine, Mickey Tsao, Arun R. Umamaheshwaran, P. Verma, Pavlos Vranas, T. J. Christopher Ward, Michael E. Wazlowski, W. Barrett, C. Engel, B. Drehmel, B. Hilgart, D. Hill, F. Kasemkhani, David J. Krolak, Chun-Tao Li 0001, Thomas A. Liebsch, James A. Marcella, A. Muff, A. Okomo, M. Rouse, A. Schram, M. Tubbs, G. Ulsh, Charles D. Wait, J. Wittrup, Myung Bae, Kenneth A. Dockser, Lynn Kissel, Mark K. Seager, Jeffrey S. Vetter, K. Yates	SC	76