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    FEASIBILITY STUDIES OF STATISTIC MULTIPLEXED COMPUTING

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    Genre
    Thesis/Dissertation
    Date
    2018
    Author
    Celik, Yasin
    Advisor
    Shi, Justin Y.
    Committee member
    Wu, Jie, 1961-
    Kant, Krishna
    Tan, Chiu C.
    Szymanski, Boleslaw
    Department
    Computer and Information Science
    Subject
    Computer Science
    Distributed Systems
    Fault Tolerance
    Hpc
    Reliability
    Scalability
    Storage
    Permanent link to this record
    http://hdl.handle.net/20.500.12613/927
    
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    DOI
    http://dx.doi.org/10.34944/dspace/909
    Abstract
    In 2012, when Professor Shi introduced me to the concept of Statistic Multiplexed Computing (SMC), I was skeptical. It contradicted everything I have learned and heard about distributed and parallel computing. However, I did believe that unhandled failures in any application will negatively impact its scalability. For that, I agreed to take on the feasibility study of SMC for practical applications. After six+ years research and experimentations, it became clear to me that the most widely believed misconception is “either performance or reliability” when upscaling a distributed application. This conception was the result of the direct use of hop-by-hop communication protocols in distributed application construction. Terminology: Hop-by-hop data protocol is a two-sided reliable lossless data communication protocol for transmitting data between a sender and a receiver. Either the sender or the receiver crash will cause data losses. Examples: MPI, RPC, RMI, OpenMP. End-to-end data protocol is a single-sided reliable lossless data communication protocol for transmitting data between application programs. All runtime available processors, networks and storage will be automatically dispatched to the best effort support of the reliable communication regardless transient and permanent device failures. Examples: HDFS, Blockchain, Fabric and SMC. Active end-to-end data protocol is a single-sided reliable lossless data communication pro- tocol for transmitting data and automatically synchronizing application programs. Example: SMC (AnkaCom, AnkaStore (this dissertation)). Unlike the hop-by-hop protocols, the use of end-to-end protocol forms an application- dependent overlay network. An overlay network for distributed and parallel computing application, such as Blockchain, has been proven to defy the “common wisdom” for two important distributed computing challenges: a) Extreme scale computing without single-point failures is practically feasible. Thus, all transaction or data losses can be eliminated. b) Extreme scale synchronized transaction replication is practically feasible. Thus, the CAP conjecture and theorem become irrelevant. Unlike passive overlay networks, such as the HDFS and Blockchain, this dissertation study proves that an active overlay network can deliver higher performance, higher reliability and security at the same time as the application up scales. Although application-level security is not part of this dissertation, it is easy to see that application-level end-to-end protocols will fundamentally eliminate the “man-in-the-middle” attacks. This will nullify many well-known attacks. With the zero-single-point failure and zero impact synchronous replication features, SMC applications are naturally resistant to DDoS and ransomware attacks. This dissertation explores practical implementations of the SMC concept for compute intensive (CI) and data intensive (DI) applications. This defense will disclose the details of CI and DI runtime implementations and results of inductive computational experiments. The computational environments include the NSF Chameleon bare-metal HPC cloud and Temple’s TCloud cluster.
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