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GraphPEG
- Source :
- ACM Transactions on Architecture and Code Optimization. 18:1-24
- Publication Year :
- 2021
- Publisher :
- Association for Computing Machinery (ACM), 2021.
-
Abstract
- Due to massive thread-level parallelism, GPUs have become an attractive platform for accelerating large-scale data parallel computations, such as graph processing. However, achieving high performance for graph processing with GPUs is non-trivial. Processing graphs on GPUs introduces several problems, such as load imbalance, low utilization of hardware unit, and memory divergence. Although previous work has proposed several software strategies to optimize graph processing on GPUs, there are several issues beyond the capability of software techniques to address. In this article, we present GraphPEG, a graph processing engine for efficient graph processing on GPUs. Inspired by the observation that many graph algorithms have a common pattern on graph traversal, GraphPEG improves the performance of graph processing by coupling automatic edge gathering with fine-grain work distribution. GraphPEG can also adapt to various input graph datasets and simplify the software design of graph processing with hardware-assisted graph traversal. Simulation results show that, in comparison with two representative highly efficient GPU graph processing software framework Gunrock and SEP-Graph, GraphPEG improves graph processing throughput by 2.8× and 2.5× on average, and up to 7.3× and 7.0× for six graph algorithm benchmarks on six graph datasets, with marginal hardware cost.
- Subjects :
- 010302 applied physics
business.industry
Computer science
Computation
02 engineering and technology
Parallel computing
Processing
01 natural sciences
020202 computer hardware & architecture
Software
Hardware and Architecture
0103 physical sciences
Graph traversal
0202 electrical engineering, electronic engineering, information engineering
Hardware acceleration
Software design
Enhanced Data Rates for GSM Evolution
business
Throughput (business)
computer
MathematicsofComputing_DISCRETEMATHEMATICS
Information Systems
computer.programming_language
Subjects
Details
- ISSN :
- 15443973 and 15443566
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- ACM Transactions on Architecture and Code Optimization
- Accession number :
- edsair.doi...........8fa33ff74f4152c473acabf5800d65bd