Publications
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Saba: Rethinking Datacenter Network Allocation from Application’s PerspectiveMR Siavash Katebzadeh , Paolo Costa , and Boris GrotIn Eighteenth European Conference on Computer Systems (EuroSys) , 2023Today’s datacenter workloads increasingly comprise distributed data-intensive applications, including data analytics, graph processing, and machine-learning training. These applications are bandwidth-hungry and often congest the datacenter network, resulting in poor network performance, which hurts application completion time. Efforts made to address this problem generally aim to achieve max-min fairness at the flow or application level. We observe that splitting the bandwidth equally among workloads is sub-optimal for aggregate application-level performance because various workloads exhibit different sensitivity to network bandwidth: for some workloads, even a small reduction in the available bandwidth yields a significant increase in completion time; for others, the completion time is largely insensitive to the available bandwidth. Building on this insight, we propose Saba, an applicationaware bandwidth allocation framework that distributes network bandwidth based on application-level sensitivity. Saba combines ahead-of-time application profiling to determine bandwidth sensitivity with runtime bandwidth allocation using lightweight software support with no modifications to network hardware or protocols. Experiments with a 32server hardware testbed show that Saba improves average completion time by 1.88× (and by 1.27× in a simulated 1,944server cluster).
@inproceedings{katebzadeh2023saba, title = {Saba: Rethinking Datacenter Network Allocation from Application’s Perspective}, author = {Katebzadeh, MR Siavash and Costa, Paolo and Grot, Boris}, booktitle = {Eighteenth European Conference on Computer Systems (EuroSys)}, year = {2023}, doi = {10.1145/3552326.3587450}, }
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Hermes: A fast, fault-tolerant and linearizable replication protocolAntonios Katsarakis , Vasilis Gavrielatos , MR Siavash Katebzadeh , and 4 more authorsIn Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) , 2020Today’s datacenter applications are underpinned by datastores that are responsible for providing availability, consistency, and performance. For high availability in the presence of failures, these datastores replicate data across several nodes. This is accomplished with the help of a reliable replication protocol that is responsible for maintaining the replicas strongly-consistent even when faults occur. Strong consistency is preferred to weaker consistency models that cannot guarantee an intuitive behavior for the clients. Furthermore, to accommodate high demand at real-time latencies, datastores must deliver high throughput and low latency. This work introduces Hermes1, a broadcast-based reliable replication protocol for in-memory datastores that provides both high throughput and low latency by enabling local reads and fully-concurrent fast writes at all replicas. Hermes couples logical timestamps with cache-coherence-inspired invalidations to guarantee linearizability, avoid write serialization at a centralized ordering point, resolve write conflicts locally at each replica (hence ensuring that writes never abort) and provide fault-tolerance via replayable writes. Our implementation of Hermes over an RDMA-enabled reliable datastore with five replicas shows that Hermes consistently achieves higher throughput than state-of-the-art RDMA-based reliable protocols (ZAB and CRAQ) across all write ratios while also significantly reducing tail latency. At 5% writes, the tail latency of Hermes is 3.6× lower than that of CRAQ and ZAB.
@inproceedings{katsarakis2020hermes, title = {Hermes: A fast, fault-tolerant and linearizable replication protocol}, author = {Katsarakis, Antonios and Gavrielatos, Vasilis and Katebzadeh, MR Siavash and Joshi, Arpit and Dragojevic, Aleksandar and Grot, Boris and Nagarajan, Vijay}, booktitle = {Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)}, pages = {201--217}, year = {2020}, doi = {10.1145/3373376.3378496}, }
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Evaluation of an InfiniBand Switch: Choose Latency or Bandwidth, but Not BothMR Siavash Katebzadeh , Paolo Costa , and Boris GrotIn 2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) , 2020Today’s cloud datacenters feature a large number of concurrently executing applications with diverse intradatacenter latency and bandwidth requirements. To remove the network as a potential performance bottleneck, datacenter operators have begun deploying high-end HPC-grade networks, such as InfiniBand (IB), which offer fully offloaded network stacks, remote direct memory access (RDMA) capability, and non-discarding links. While known to provide both low latency and high bandwidth for a single application, it is not clear how well such networks accommodate a mix of latencyand bandwidth-sensitive traffic that is likely in a real-world deployment. As a step toward answering this question, we develop a performance measurement tool for RDMA-based networks, RPerf, that is capable of precisely measuring the IB switch performance without hardware support. Using RPerf, we benchmark a rack-scale IB cluster in isolated and mixedtraffic scenarios. Our key finding is that the evaluated switch can provide either low latency or high bandwidth, but not both simultaneously in a mixed-traffic scenario. We evaluate several options to improve the latency-bandwidth trade-off and demonstrate that none are ideal.
@inproceedings{katebzadeh2020evaluation, title = {Evaluation of an InfiniBand Switch: Choose Latency or Bandwidth, but Not Both}, author = {Katebzadeh, MR Siavash and Costa, Paolo and Grot, Boris}, booktitle = {2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)}, pages = {180--191}, year = {2020}, doi = {10.13140/RG.2.2.25878.50245}, }
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Bankrupt covert channel: Turning network predictability into vulnerabilityDmitrii Ustiugov , Plamen Petrov , MR Siavash Katebzadeh , and 1 more authorIn 14th USENIX Workshop on Offensive Technologies (WOOT) , 2020Recent years have seen a surge in the number of data leaks despite aggressive information-containment measures deployed by cloud providers. When attackers acquire sensitive data in a secure cloud environment, covert communication channels are a key tool to exfiltrate the data to the outside world. While the bulk of prior work focused on covert channels within a single CPU, they require the spy (transmitter) and the receiver to share the CPU, which might be difficult to achieve in a cloud environment with hundreds or thousands of machines. This work presents Bankrupt, a high-rate highly clandestine channel that enables covert communication between the spy and the receiver running on different nodes in an RDMA network. In Bankrupt, the spy communicates with the receiver by issuing RDMA network packets to a private memory region allocated to it on a different machine (an intermediary). The receiver similarly allocates a separate memory region on the same intermediary, also accessed via RDMA. By steering RDMA packets to a specific set of remote memory addresses, the spy causes deep queuing at one memory bank, which is the finest addressable internal unit of main memory. This exposes a timing channel that the receiver can listen on by issuing probe packets to addresses mapped to the same bank but in its own private memory region. Bankrupt channel delivers 74Kb/s throughput in CloudLab’s public cloud while remaining undetectable to the existing monitoring capabilities, such as CPU and NIC performance counters.
@inproceedings{ustiugov2020bankrupt, title = {Bankrupt covert channel: Turning network predictability into vulnerability}, author = {Ustiugov, Dmitrii and Petrov, Plamen and Katebzadeh, MR Siavash and Grot, Boris}, booktitle = {14th USENIX Workshop on Offensive Technologies (WOOT)}, year = {2020}, }
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PyPerC: Python toolbox for perceptual computingZohreh Amini Ghanavati , MohammadReza Katebzadeh , Hooman Tahayori , and 1 more authorIn 2018 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS) , 2018@inproceedings{ghanavati2018pyperc, title = {PyPerC: Python toolbox for perceptual computing}, author = {Ghanavati, Zohreh Amini and Katebzadeh, MohammadReza and Tahayori, Hooman and Khunjush, Farshad}, booktitle = {2018 6th Iranian Joint Congress on Fuzzy and Intelligent Systems (CFIS)}, pages = {210--214}, year = {2018}, organization = {IEEE}, }
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Persian gulf soccer 2d simulation team description paper 2017Ehsan Asali , Alireza Moravej , Sajad Akbarpoor , and 8 more authorsIn The 21th annual RoboCup International Symposium, Japan, Nagoya , 2017@inproceedings{asali2017persian, title = {Persian gulf soccer 2d simulation team description paper 2017}, author = {Asali, Ehsan and Moravej, Alireza and Akbarpoor, Sajad and Asali, Omid and Katebzadeh, MohammadReza and Tafazol, Saeed and Negahbani, Farzin and Valipour, Mojtaba and Mirian, Shokoofeh and Mehran, Hossein and others}, booktitle = {The 21th annual RoboCup International Symposium, Japan, Nagoya}, year = {2017}, }
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Shiraz soccer 2D simulation team description paper 2016Ehsan Asali , Mojtaba Valipour , Ardavan Afshar , and 7 more authorsIn RoboCup 2016 Symposium and Competitions: Team Description Papers, Leipzig, Germany , 2016@inproceedings{asali2016shiraz, title = {Shiraz soccer 2D simulation team description paper 2016}, author = {Asali, Ehsan and Valipour, Mojtaba and Afshar, Ardavan and Asali, Omid and Katebzadeh, MohammadReza and Tafazol, Saeed and Moravej, Alireza and Salehi, Suhair and Karami, Hosain and Mohammadi, Mahsa}, booktitle = {RoboCup 2016 Symposium and Competitions: Team Description Papers, Leipzig, Germany}, year = {2016}, }
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Using Machine Learning approaches to detect opponent formationEhsan Asali , Mojtaba Valipour , Nader Zare , and 3 more authorsIn 2016 Artificial Intelligence and Robotics (IRANOPEN) , 2016@inproceedings{asali2016using, title = {Using Machine Learning approaches to detect opponent formation}, author = {Asali, Ehsan and Valipour, Mojtaba and Zare, Nader and Afshar, Ardavan and Katebzadeh, MohammadReza and Dastghaibyfard, GH}, booktitle = {2016 Artificial Intelligence and Robotics (IRANOPEN)}, pages = {140--144}, year = {2016}, organization = {IEEE}, }