[PDF][PDF] Scalable graph learning for anti-money laundering: A first look

M Weber, J Chen, T Suzumura, A Pareja… - arXiv preprint arXiv …, 2018 - markrweber.com
Organized crime inflicts human suffering on a genocidal scale: the Mexican drug cartels
have murdered 150,000 people since 2006; upwards of 700,000 people per year are …

Gpop: A scalable cache-and memory-efficient framework for graph processing over parts

K Lakhotia, R Kannan, S Pati, V Prasanna - ACM Transactions on …, 2020 - dl.acm.org
The past decade has seen the development of many shared-memory graph processing
frameworks intended to reduce the effort of developing high-performance parallel …

Many sequential iterative algorithms can be parallel and (nearly) work-efficient

Z Shen, Z Wan, Y Gu, Y Sun - Proceedings of the 34th ACM Symposium …, 2022 - dl.acm.org
Some recent papers showed that many sequential iterative algorithms can be directly
parallelized, by identifying the dependences between the input objects. This approach …

GPOP: A cache and memory-efficient framework for graph processing over partitions

K Lakhotia, R Kannan, S Pati, V Prasanna - Proceedings of the 24th …, 2019 - dl.acm.org
Graph analytics frameworks, typically based on Vertex-centric or Edge-centric paradigms
suffer from poor cache utilization, irregular memory accesses, heavy use of synchronization …

[PDF][PDF] Many Sequential Iterative Algorithms Can Be Parallel and Work-efficient

Z Shen, Z Wan, Y Gu, Y Sun - 2022 - cs.ucr.edu
There are two goals in designing efficient parallel algorithms: to reduce work, and to improve
parallelism. Work-efficiency, meaning that the work (total number of operations) is …

[PDF][PDF] GPOP: A scalable cache-and memory-efficient framework for Graph Processing Over Partitions

KLSPR Kannan, V Prasanna - arXiv preprint arXiv:1806.08092, 2018 - academia.edu
Past decade has seen the development of many shared-memory graph processing
frameworks, intended to reduce the effort of developing high performance parallel …