Internet Supercomputing Research Articles

Dealing with undependable workers in decentralized network supercomputing

Internet supercomputing is an approach to solving partitionable, computation-intensive problems by harnessing the power of a vast number of interconnected computers. This paper presents a new algorithm for the problem of using network supercomputing to perform a large collection of independent tasks, while dealing with undependable processors. The adversary may cause the processors to return bogus results for tasks with certain probabilities, and may cause a subset F of the initial set of processors P to crash. The adversary is constrained in two ways. First, for the set of non-crashed processors P−F, the average probability of a processor returning a bogus result is inferior to 12. Second, the adversary may crash a subset of processors F, provided the size of P−F is bounded from below. We consider two models: the first bounds the size of P−F by a fractional polynomial, the second bounds this size by a poly-logarithm. Both models yield adversaries that are much stronger than previously studied. Our randomized synchronous algorithm is formulated for n processors and t tasks, with n≤t, where depending on the number of crashes each live processor is able to terminate dynamically with the knowledge that the problem is solved with high probability. For the adversary constrained by a fractional polynomial, the round complexity of the algorithm is O(tnεlog⁡nlog⁡log⁡n), its work is O(tlog⁡nlog⁡log⁡n) and message complexity is O(nlog⁡nlog⁡log⁡n). For the poly-log constrained adversary, the round complexity is O(t), work is O(tnε), and message complexity is O(n1+ε). All bounds are shown to hold with high probability.

Robust network supercomputing with unreliable workers

Internet supercomputing is becoming a powerful tool for harnessing massive amounts of computational resources. However in typical master–worker settings the correctness of the results of the computation crucially relies on the ability of the master to depend on the computation performed by the workers. We consider a distributed system consisting of a master process and a collection of synchronous worker processes that can execute tasks on behalf of the master and that may act nefariously by deliberately returning fallacious results. The master decides on the correctness of the results by assigning the same task to several workers. For such a setting with n processes and t tasks we study the problem of collectively performing the tasks under two different failure models: model Fa, where some fraction f of workers that are prone to returning arbitrary (e.g., incorrect) results and the probability p of such faulty behavior are not known a priori to the master, and model Fb when these quantities are known to the master. Previous works assume that the number of faulty processes or the probability of a process acting maliciously is known to the master, e.g., as in model Fb. In this paper this assumption is removed in model Fa. First, for model Fa we provide an efficient algorithm-based on the Stopping Rule Algorithm by Dagum et al. (1995)—that can estimate f and p with (ϵ,δ)-approximation, for any 0<δ<1 and ϵ>0. We also provide a randomized algorithm for detecting the faulty processes for model Fa. Finally, we provide algorithms to perform t tasks, with n workers, in models Fa and Fb.

Large-Scale Structural Analysis by Parallel Multifrontal Solver Through Internet-Based Personal Computers

Internet supercomputing methodology is introduced, and the concept is realized for large-scale finite element analysis. This is enabled by an efficient out-of-core parallel solver, which is based on domainwise or elementwise multifrontal approach. The primary resources of Internet supercomputing are numerous idling personal computers connected by the Internet irrespective of their locations. The computing ability of hundreds or thousands personal computers connected by the Internet can be as powerful as that of supercomputer such as the IBM SP system if these personal computers are utilized for solving a problem simultaneously through an efficient parallel computing algorithm. Under the described concept, a virtual supercomputing system InterSup I is constructed and tested. To establish the InterSup I system, 64 personal computer nodes, which are located in several places and connected by the Internet, are conscripted. When the established InterSup I system is used, linear static analyses of a finite element model having around 2 × 10 6 degrees of freedom are done through the developed parallel multifrontal solver. Some numerical tests have been carried out to investigate the affordability and effectiveness of Internet supercomputing. The possibility of Internet supercomputing through Internet personal computers as an alternative supercomputing power for high-performance computing is provided in this research.

Large-scale structural analysis by parallel multifrontal solver through Internet-based personal computers

Internet supercomputing methodology is introduced, and the concept is realized for large-scale finite element analysis. This is enabled by an efficient out-of-core parallel solver, which is based on domainwise or elementwise multifrontal approach. The primary resources of Internet supercomputing are numerous idling personal computers connected by the Internet irrespective of their locations. The computing ability of hundreds or thousands personal computers connected by the Internet can be as powerful as that of supercomputer such as the IBM SP system if these personal computers are utilized for solving a problem simultaneously through an efficient parallel computing algorithm. Under the described concept, a virtual supercomputing system InterSup I is constructed and tested. To establish the InterSup I system, 64 personal computer nodes, which are located in several places and connected by the Internet, are conscripted. When the established InterSup I system is used, linear static analyses of a finite element model having around 2 × 10 6 degrees of freedom are done through the developed parallel multifrontal solver. Some numerical tests have been carried out to investigate the affordability and effectiveness of Internet supercomputing. The possibility of Internet supercomputing through Internet personal computers as an alternative supercomputing power for high-performance computing is provided in this research.