Abstract
Graph processing is increasingly used in a variety of domains, from engineering to logistics and from scientific computing to online gaming. To process graphs efficiently, GPU-enabled graph-processing systems such as TOTEM and Medusa exploit the GPU or the combined CPU+GPU capabilities of a single machine. Unlike scalable distributed CPU-based systems such as Pregel and GraphX, existing GPU-enabled systems are restricted to the resources of a single machine, including the limited amount of GPU memory, and thus cannot analyze the increasingly large-scale graphs we see in practice. To address this problem, we design and implement three families of distributed heterogeneous graph-processing systems that can use both the CPUs and GPUs of multiple machines. We further focus on graph partitioning, for which we compare existing graph-partitioning policies and a new policy specifically targeted at heterogeneity. We implement all our distributed heterogeneous systems based on the programming model of the single-machine TOTEM, to which we add (1) a new communication layer for CPUs and GPUs across multiple machines to support distributed graphs, and (2) a workload partitioning method that uses offline profiling to distribute the work on the CPUs and the GPUs. We conduct a comprehensive real-world performance evaluation for all three families. To ensure representative results, we select 3 typical algorithms and 5 datasets with different characteristics. Our results include algorithm run time, performance breakdown, scalability, graph partitioning time, and comparison with other graph-processing systems. They demonstrate the feasibility of distributed heterogeneous graph processing and show evidence of the high performance that can be achieved by combining CPUs and GPUs in a distributed environment.
Original language | English |
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Title of host publication | Proceedings - 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, CCGrid 2016 |
Place of Publication | Los Alamitos, CA |
Publisher | IEEE |
Pages | 1-10 |
Number of pages | 10 |
ISBN (Electronic) | 978-1-5090-2453-7 |
DOIs | |
Publication status | Published - 21 Jul 2016 |
Event | CCGRID 2016: 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing - Cartagena de Indias, Cartagena, Colombia Duration: 16 May 2016 → 19 May 2016 |
Conference
Conference | CCGRID 2016 |
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Abbreviated title | CCGRID 2016 |
Country/Territory | Colombia |
City | Cartagena |
Period | 16/05/16 → 19/05/16 |
Keywords
- Distributed Heterogeneous Systems
- Graph Processing