Special Issue on Graph Processing: Techniques and Applications
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DOI: 10.1007/s41019-017-0036-2
Abstract: Given the existence of large graphs in many real applications including the web, online social networks, RDF, etc., there is a need to find new approaches to efficiently process such large graphs. This special issue… read more here.
Keywords: issue; graph processing; graph; special issue ... See more keywords
Exploring Core and Cache Hierarchy Bottlenecks in Graph Processing Workloads
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DOI: 10.1109/lca.2018.2864964
Abstract: Graph processing is an important analysis technique for a wide range of big data problems. The ability to explicitly represent relationships between entities gives graph analytics significant performance advantage over traditional relational databases. In this… read more here.
Keywords: core cache; graph processing; cache; cache hierarchy ... See more keywords
PIM-GraphSCC: PIM-Based Graph Processing Using Graph’s Community Structures
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DOI: 10.1109/lca.2020.3039498
Abstract: Graphs are used to store relationships on a variety of topics, such as road map data and social media connections. Processing this data allows one to uncover insights from its structure. However, while analyzing graphs… read more here.
Keywords: graph processing; graph; pim graphscc; pim based ... See more keywords
Accelerating Graph Processing With Lightweight Learning-Based Data Reordering
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DOI: 10.1109/lca.2022.3151087
Abstract: Graph processing is a vital component in various application domains. However, a good graph processing performance is hard to achieve due to its intensive irregular data accesses. Noticing that in real-world graphs, a small portion… read more here.
Keywords: graph processing; processing lightweight; graph; learning based ... See more keywords
HyVE: Hybrid Vertex-Edge Memory Hierarchy for Energy-Efficient Graph Processing
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DOI: 10.1109/tc.2019.2893384
Abstract: High energy consumption of conventional memory modules (e.g., DRAMs) hinders the further improvement of large-scale graph processing’s energy efficiency. The emerging resistive random-access memory (ReRAM) has shown great potential in providing an energy-efficient memory module.… read more here.
Keywords: graph processing; memory; energy efficient; energy ... See more keywords
A Structure-Aware Storage Optimization for Out-of-Core Concurrent Graph Processing
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DOI: 10.1109/tc.2021.3098976
Abstract: With the huge demand for graph analytics in many real-world applications, massive iterative graph processing jobs are concurrently performed on the same graphs and suffer from significant high data access cost. To lower the data… read more here.
Keywords: concurrent; times times; graph processing; graph ... See more keywords
Realizing Memory-Optimized Distributed Graph Processing
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DOI: 10.1109/tkde.2017.2779797
Abstract: A multitude of contemporary applications heavily involve graph data whose size appears to be ever–increasing. This trend shows no signs of subsiding and has caused the emergence of a number of distributed graph processing systems… read more here.
Keywords: memory optimized; graph processing; graph; realizing memory ... See more keywords
HitGraph: High-throughput Graph Processing Framework on FPGA
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DOI: 10.1109/tpds.2019.2910068
Abstract: This paper presents, HitGraph, an FPGA framework to accelerate graph processing based on the edge-centric paradigm. HitGraph takes in an edge-centric graph algorithm and hardware resource constraints, determines design parameters and then generates a Register… read more here.
Keywords: graph processing; design; graph; high throughput ... See more keywords
Cost-Aware Partitioning for Efficient Large Graph Processing in Geo-Distributed Datacenters
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DOI: 10.1109/tpds.2019.2955494
Abstract: Graph processing is an emerging computation model for a wide range of applications and graph partitioning is important for optimizing the cost and performance of graph processing jobs. Recently, many graph applications store their data… read more here.
Keywords: graph partitioning; graph processing; graph; cost ... See more keywords
A Hybrid Update Strategy for I/O-Efficient Out-of-Core Graph Processing
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DOI: 10.1109/tpds.2020.2973143
Abstract: In recent years, a number of out-of-core graph processing systems have been proposed to process graphs with billions of edges on just one commodity computer, due to their high cost efficiency. To obtain a better… read more here.
Keywords: hus graph; efficient core; core graph; graph processing ... See more keywords