A task-based linear algebra Building Blocks approach for scalable graph analytics

It is challenging to obtain scalable HPC performance on real applications, especially for data science applications with irregular memory access and computation patterns. To drive co-design efforts in architecture, system, and application design, we are developing miniapps representative of data science workloads. These in turn stress the state of the art in Graph BLAS-like Graph Algorithm Building Blocks (GABB). In this work, we outline a Graph BLAS-like, linear algebra based approach to miniTri, one such miniapp. We describe a task-based prototype implementation and give initial scalability results.