In today’s digital landscape, blockchain technology is revolutionizing how we interact with data, leading to the rise of decentralized applications (dApps). These innovative applications are shifting ...

We present a novel framework GraphZoo, that makes learning, using, and designing graph processing pipelines/models systematic by abstraction over the redundant components. The framework contains a ...

Abstract: The key performance bottleneck of large-scale graph processing on memory-limited GPUs is the host-GPU graph data transfer. Existing GPU-accelerated graph processing frameworks address this ...

Abstract: Graph networks can model data observed across different levels of biological systems that span from population graphs (with patients as network nodes) to molecular graphs that involve omics ...

We face increasing needs for efficient processing for diverse cognitive tasks using a vast volume of generated data (Bonomi et al., 2012; Chen and Lin, 2014). Therefore, there is a crucial need for ...

Google Cloud has updated its fully managed distributed SQL database service Spanner to add graph processing capabilities, dubbed Spanner Graph. The update is expected to help developers build ...

Graph processing at hyperscale has historically been a challenge because of the sheer complexity of algorithms and graph workflows. Alibaba has been tackling this issue via a project called GraphScope ...