S
Sungpack Hong
Researcher at Business International Corporation
Publications - 89
Citations - 3055
Sungpack Hong is an academic researcher from Business International Corporation. The author has contributed to research in topics: Graph (abstract data type) & Power graph analysis. The author has an hindex of 19, co-authored 89 publications receiving 2738 citations. Previous affiliations of Sungpack Hong include Oracle Corporation & KAIST.
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Proceedings ArticleDOI
A scalable processing-in-memory accelerator for parallel graph processing
TL;DR: This work argues that the conventional concept of processing-in-memory (PIM) can be a viable solution to achieve memory-capacity-proportional performance and designs a programmable PIM accelerator for large-scale graph processing called Tesseract.
Proceedings ArticleDOI
Accelerating CUDA graph algorithms at maximum warp
TL;DR: A novel virtual warp-centric programming method that exposes the traits of underlying GPU architectures to users and significantly improves the performance of applications with heavily imbalanced workloads, and enables trade-offs between workload imbalance and ALU underutilization for fine-tuning the performance.
Proceedings ArticleDOI
Green-Marl: a DSL for easy and efficient graph analysis
TL;DR: This paper describes Green-Marl, a domain-specific language (DSL) whose high level language constructs allow developers to describe their graph analysis algorithms intuitively, but expose the data-level parallelism inherent in the algorithms.
Proceedings ArticleDOI
Efficient Parallel Graph Exploration on Multi-Core CPU and GPU
TL;DR: A new method for implementing the parallel BFS algorithm on multi-core CPUs which exploits a fundamental property of randomly shaped real-world graph instances and shows improved performance over the current state-of-the-art implementation and increases its advantage as the size of the graph increases.
Proceedings ArticleDOI
PGQL: a property graph query language
TL;DR: A new query language for the popular Property Graph (PG) data model: the Property Graph Query Language (PGQL), based on the paradigm of graph pattern matching, closely follows syntactic structures of SQL, and provides regular path queries with conditions on labels and properties to allow for reachability and path finding queries.