TL;DR
PASGAL is a scalable parallel graph library that efficiently handles large-diameter graphs by using vertical granularity control to reduce synchronization overhead, outperforming existing systems especially on large-diameter graphs.
Contribution
PASGAL introduces vertical granularity control and redesigned algorithms to improve parallelism and scalability for large-diameter graphs.
Findings
Significantly faster on large-diameter graphs compared to existing systems.
Achieves competitive performance on small-diameter graphs.
Effectively reduces synchronization overhead in parallel graph processing.
Abstract
In this paper, we introduce PASGAL (Parallel And Scalable Graph Algorithm Library), a parallel graph library that scales to a variety of graph types, many processors, and large graph sizes. One special focus of PASGAL is the efficiency on \textit{large-diameter graphs}, which is a common challenge for many existing parallel graph processing systems: many existing graph processing systems can be even slower than the standard sequential algorithm on large-diameter graphs due to the lack of parallelism. Such performance degeneration is caused by the high overhead in scheduling and synchronizing threads when traversing the graph in the breadth-first order. The core technique in PASGAL to achieve high parallelism is a technique called \textit{vertical granularity control (VGC)} to hide synchronization overhead, as well as careful redesign of parallel graph algorithms and data structures.…
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