Title
SAGA-Bench: Software and Hardware Characterization of Streaming Graph Analytics Workloads
Abstract
Many application scenarios such as social network analysis and real-time financial fraud detection involve performing batched updates and analytics on a time-evolving or streaming graph. Despite their importance, streaming graph analytics workloads have not been systematically studied at either the software or the architecture levels. This paper fills this gap through three contributions. First, we develop and open-source SAGA-Bench, a benchmark for streaming graph analytics, which puts together different data structures and compute models on the same platform for a fair and systematic characterization. Second, we perform software-level characterization using SAGA-Bench. Our profiling reveals that the best data structure for a streaming graph depends on the per-batch degree distribution of the graph. We also observe that the incremental compute model provides performance benefits especially for larger graphs. Finally, we show that the graph update phase contributes at least 40% of the streaming graph processing latency in many cases. Third, we perform workload characterization at the architecture level. Our study reveals that the graph update phase exhibits lower utilization of architecture resources than the compute phase. Furthermore, the hardware resource utilization of the update phase strongly depends on the underlying structure of the batches of the graph. Finally, between compute and update phases, the former exhibits a higher L3 cache hit ratio, whereas the latter shows a higher L2 cache hit ratio.
Year
DOI
Venue
2020
10.1109/ISPASS48437.2020.00012
2020 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)
Keywords
DocType
ISBN
streaming graph analytics,workload characterization,benchmarking
Conference
978-1-7281-4799-4
Citations 
PageRank 
References 
1
0.34
34
Authors
7
Name
Order
Citations
PageRank
Abanti Basak110.34
Jilan Lin221.71
Ryan Lorica310.34
Xinfeng Xie4526.39
Zeshan Chishti572334.65
Alaa R. Alameldeen6167280.06
Yuan Xie76430407.00