Analysis of Event Synchronization in Parallel Programs

The increase in the number and complexity of parallel programs has led to a need for better approaches for synchronization error detection and debugging of parallel programs. This paper presents an efficient and precise algorithm for the detection of nondeterminacy (race conditions) in parallel programs. Nondeterminacy exists in a program when the program yields different outputs for different runs with the same input. We limit our attention to nondeterminacy due to errors in synchronization and to race conditions due to these unsynchronized accesses to shared variables. A directed acyclic graph called a task graph is used to represent the accesses to shared variables in a parallel program with edges representing guaranteed ordering. The algorithm proposed here constructs an augmented task graph, and then uses a modification of depth-first search to classify the edges in the augmented task graph. The edges are analyzed and the nodes that are guaranteed to execute before an event are linked to these events by edges representing guaranteed ordering among events. This ordering is used to detect any race conditions in parallel programs.