Abstract
The vector clock is a fundamental tool for tracking causality in parallel and distributed applications. Unfortunately, it does not scale well to large systems because each process needs to maintain a vector of size n, where n is the total number of processes in the system. To address this problem, the encoded vector clock (EVC) was recently proposed. The EVC is based on the encoding of the vector clock using prime numbers and uses a single number to represent vector time. The EVC has all the properties of the vector clock and yet uses a single number to represent global time. However, the single number EVC tends to grow fast and may soon exceed the size of the traditional vector clock. In this paper, we evaluate the growth rate of the size of the EVC using a simulation model. The simulations show that the EVC grows relatively fast, and the growth rate depends on the mix of internal events and communication events. To overcome this drawback, the EVC can be used in conjunction with several scalability techniques that can allow the use of the EVC in practical applications. We then present a case study of detecting memory consistency errors in MPI one-sided applications using EVC.
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We thank Rahul Sathe for his help with the simulations.
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Kshemkalyani, A.D., Voleti, B. (2019). On the Growth of the Prime Numbers Based Encoded Vector Clock. In: Fahrnberger, G., Gopinathan, S., Parida, L. (eds) Distributed Computing and Internet Technology. ICDCIT 2019. Lecture Notes in Computer Science(), vol 11319. Springer, Cham. https://doi.org/10.1007/978-3-030-05366-6_14
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