Prime clock: Encoded vector clock to characterize causality in distributed systems

Abstract

The vector clock is a fundamental tool for tracking causality in 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, we propose the prime clock, which is based on the encoding of the vector clock using prime numbers and uses a single number to represent vector time. We propose the operations on the encoded vector clock (EVC). We then show how to timestamp global states and how to perform operations on the global states using the EVC. Using a theoretical analysis and a simulation model, we evaluate the growth rate of the size of the EVC. The EVC is seen to grow very fast and hence it does not appear to offer a general purpose practical replacement of vector clocks. To address this drawback, we propose several scalability techniques for the EVC that can allow the use of the EVC in practical applications. We then present two case studies of detecting memory consistency errors in MPI one-sided applications and of dynamic race detection in multi-threaded environments, that use a combination of two of these scalability techniques. The results show that the EVC is not just a theoretical concept, but it is applicable to practical problems and can compete in terms of both space and time requirements with other known protocols.